Preoperative Diabetes Screening Before Pain Procedures and Surgery

Preoperative diabetes screening means drawing an HbA1c before a pain procedure or surgery, and it belongs on every patient: universal screening in one arthroplasty program found diabetes or prediabetes in more than half, with 40.9% of the diabetic patients undiagnosed. An HbA1c above 8% before lumbar surgery was tied to more complications and readmissions.

Pain care escalates from pills to needles to the operating room, usually without one metabolic number drawn. Screening everyone shows what that omission hides.

Preoperative diabetes screening is standard in some arthroplasty programs and missing from most pain pathways, even though the unmeasured glycemia that complicates a fusion also shapes what an epidural, a drug trial or a lifestyle program delivers. The escalation ladder in pain care usually climbs from medication to injection to surgery without a single metabolic measurement on the way up.

Pain Is Not a Diagnosis, the Chapter 2 video of The Pained Brain by Dr. Gurpreet Singh Padda, MD, MBA, MHP, and Dr. KrisJay Fucanan, MD, frames pain as a signal that raises three questions before anyone treats it: which structure, which mechanism, which terrain. For a referring or treating physician, the third question is a measurement problem, and part of the second is one too.

How the label replaced the workup

ICD-11 codes chronic primary pain when pain has lasted beyond three months with distress or disability and is not better accounted for by another condition. It works as a coding instrument, yet no biological criterion separates primary from secondary pain; the category is defined by what was not found. A label built from exclusion gives a clinician nowhere to go next.

For about two decades the field, Dr. Padda’s own specialty among them, treated the pain score as the endpoint. The numeric rating became a vital sign, and a review of 600 VA visits found no quality indicator improved afterward. The incentives reinforced it: 83% of academic pain-center leaders reported administrative pressure tied to satisfaction scores, while in 51,946 nationally representative adults the most-satisfied quartile carried an adjusted mortality hazard of 1.26. A metric that rewards a quiet patient does not reward a measured one.

How often does preoperative screening find undiagnosed diabetes?

Screen every patient and the prevalence stops being theoretical. In a Philadelphia arthroplasty population of 1,461, diabetes was present in 20.6% and prediabetes in 38.3%, and 40.9% of the diabetic patients carried no prior diagnosis. Universal HbA1c testing before knee replacement in Hong Kong added undiagnosed prediabetes in 36.4% and undiagnosed diabetes in 1.6%. Most of those patients had been through primary care and a surgical referral without the number being drawn.

The value predicts the result. In 4,778 elective lumbar operations, preoperative HbA1c above 8% was associated with an odds ratio of 1.81 for any complication, 1.66 for 90-day readmission and 0.64 for reaching a meaningful functional gain. In a matched analysis of 7,336 arthrodesis patients with diabetes, 30-day readmission ran 6.5% against 4.4% and 90-day reoperation 4.3% against 3.2%, with no difference after decompression alone. Across more than 3 million spine operations, metabolic syndrome carried relative risks of 1.5 for readmission and 1.6 for wound complications.

The evidence is observational, diabetes is often a registry checkbox rather than a measured value, and one cohort of 587 hip and knee replacements found similar 12-month pain and function once BMI and comorbidity were adjusted. That study supports obesity plus multimorbidity as the operative terrain rather than HbA1c alone, which is still an argument for measuring the terrain.

Do steroid injections raise blood sugar?

The same body receives the injections. In a multicenter cervical epidural cohort, 92% of diabetic patients developed transient hyperglycemia, and in 18 patients measured serially, fasting glucose was elevated on day 1 and back to baseline by day 7. Bone density reductions appeared at a cumulative methylprednisolone-equivalent dose of 200 mg in a year, against real-world exposure averaging 14.7 injections per patient. An epidural used as a bridge on a patient with known metabolic status is a defensible plan. The same injection repeated on an unmeasured body is exposure without a denominator.

Practically, a known HbA1c before a steroid procedure lets the team set a glucose-monitoring plan for the following week and track cumulative steroid dose against a bone-health baseline, instead of discovering the diabetes after the second or third injection.

Mechanism is also unmeasured

Physical examination alone is Level IV evidence for identifying a spinal pain generator and MRI or CT Level V, so a structural answer needs a controlled block. Mechanism is skipped even more often. Of 27 trials of neuropathic-pain drugs for back and spine-related leg pain, 59% excluded neuropathic pain or never assessed it, and only 22% enrolled patients at the probable-or-definite level. Where neuropathic pain was probable, pain fell 10.45 points on a 100-point scale; where merely possible, 5.50, though subgroup differences were not significant. In one clinic sample of 1,957 patients, 13.0% screened positive for a neuropathic component, with no correlation to pain duration.

A validated screening questionnaire belongs in the intake. Where small-fiber involvement is suspected, sudomotor testing adds an objective read on the sweat response driven by small distal nerve fibers, which helps separate a neuropathic contribution from a purely structural one before drug selection.

Why measure a metabolic baseline before treating pain?

The terrain trials show pain responding in proportion to metabolic change. In 407 adults with obesity and knee osteoarthritis, semaglutide reduced knee pain by 41.7 points against 27.5 for placebo over 68 weeks with weight loss of 13.7% against 3.2%. Metformin in 107 adults with knee osteoarthritis and overweight reduced pain by 11.4 mm more than placebo. Intensive diet and exercise produced 10.6 kg of weight loss with a fall in IL-6, while the community version of the same program moved pain by only 0.6 points, and a telephone referral that changed weight by 0.4 kg changed pain not at all.

The less obvious consequence is diagnostic. Without a baseline body composition and metabolic panel, a patient who fails a lifestyle or pharmacologic plan cannot be classified: the terrain may not have changed, or it changed and the pain generator lies elsewhere. Repeat measurement is what distinguishes a failed intervention from a failed dose. Serial values also support between-visit monitoring in chronic care.

What should a preoperative diabetes screening order set include?

Guidelines will not supply it. The 2022 CDC opioid-prescribing guideline runs 95 pages without mentioning HbA1c, insulin or an inflammatory marker, and the NICE chronic pain assessment section sets out 23 recommendations naming no blood test. Neither prohibits testing; both leave a vacancy that a practice has to fill with its own protocol.

A workable protocol attaches a standing order to any referral for fusion, arthroplasty or repeated steroid injection: HbA1c and fasting glucose against the published thresholds of 6.5% and 126 mg/dL for diabetes and 5.7-6.4% and 100-125 mg/dL for prediabetes, fasting insulin and lipids through laboratory panels, bioimpedance body composition, a mood screen and a neuropathic screen. Measura [Cardiometabolic and Autonomic Health Analysis] performs and reports those measurements under physician medical direction; interpretation and management remain with the ordering and treating physicians, and results should travel to the surgeon through structured record integration. The study-level evidence is in the Chapter 2 supplement, and the mortality case for screening pain patients at all is in the physician article on metabolic screening in chronic pain. Excess weight can hide depleted muscle and micronutrients before an operation, the focus of malnutrition in obesity.

Frequently asked questions

References

• Shohat, N., Goswami, K., Tarabichi, M., Sterbis, E., Tan, T. L., & Parvizi, J. (2018). All Patients Should Be Screened for Diabetes Before Total Joint Arthroplasty. The Journal of Arthroplasty, 33(7), 2057–2061. https://doi.org/10.1016/j.arth.2018.02.047
• Lim, S., Yeh, H. H., Macki, M., Mansour, T., Schultz, L., Telemi, E., Haider, S., Nerenz, D. R., Schwalb, J. M., Abdulhak, M., Park, P., Aleem, I., Easton, R., Khalil, J., Perez-Cruet, M., & Chang, V. (2021). Preoperative HbA1c > 8% Is Associated With Poor Outcomes in Lumbar Spine Surgery: A Michigan Spine Surgery Improvement Collaborative Study. Neurosurgery, 89(5), 819–826. https://doi.org/10.1093/neuros/nyab294
• Mooney, J., Nathani, K. R., Zeitouni, D., Michalopoulos, G. D., Wang, M. Y., Coric, D., Chan, A. K., Lu, D. C., Sherrod, B. A., Gottfried, O. N., Shaffrey, C. I., Than, K. D., Goldberg, J. L., Hussain, I., Virk, M. S., Agarwal, N., Glassman, S. D., Shaffrey, M. E., Park, P., … Bydon, M. (2023). Does diabetes affect outcome or reoperation rate after lumbar decompression or arthrodesis? A matched analysis of the Quality Outcomes Database data set. Journal of Neurosurgery: Spine, 40(3), 331-342. https://doi.org/10.3171/2023.9.SPINE23522
• Lenguerrand, E., Beswick, A. D., Whitehouse, M. R., Wylde, V., & Blom, A. W. (2018). Outcomes following hip and knee replacement in diabetic versus nondiabetic patients and well versus poorly controlled diabetic patients: a prospective cohort study. Acta Orthopaedica, 89(4), 399-405. https://doi.org/10.1080/17453674.2018.1473327
• Gogol, P., Pasztaleniec, R., Szczepaniak, R., Wiśniewski, R., Staszkiewicz, R., Sobstyl, M., Wąsik, P., & Grabarek, B. O. (2026). Clinical Outcomes of Two Institution-Specific Cervicothoracic Interlaminar Epidural Steroid Injection Protocols (C7/T1-6 mL vs. T1/T2-8 mL) in Cervical Radiculopathy: A Multicenter Retrospective Cohort Study. Journal of Clinical Medicine, 15(15), 5900. https://doi.org/10.3390/jcm15155900
• Ward, J., Grinstead, A., Kemp, A., Kersten, P., Schmid, A. B., & Ridehalgh, C. (2024). A Meta-analysis Exploring the Efficacy of Neuropathic Pain Medication for Low Back Pain or Spine-Related Leg Pain: Is Efficacy Dependent on the Presence of Neuropathic Pain? Drugs, 84(12), 1603–1636. https://doi.org/10.1007/s40265-024-02085-6
• Bliddal, H., Bays, H., Czernichow, S., Uddén Hemmingsson, J., Hjelmesæth, J., Hoffmann Morville, T., Koroleva, A., Skov Neergaard, J., Vélez Sánchez, P., Wharton, S., Wizert, A., & Kristensen, L. E. (2024). Once-Weekly Semaglutide in Persons with Obesity and Knee Osteoarthritis. The New England Journal of Medicine, 391(17), 1573–1583. https://doi.org/10.1056/NEJMoa2403664
• Messier, S. P., Beavers, D. P., Queen, K., Mihalko, S. L., Miller, G. D., Losina, E., Katz, J. N., Loeser, R. F., DeVita, P., Hunter, D. J., Newman, J. J., Quandt, S. A., Lyles, M. F., Jordan, J. M., & Callahan, L. F. (2022). Effect of Diet and Exercise on Knee Pain in Patients With Osteoarthritis and Overweight or Obesity: A Randomized Clinical Trial. JAMA, 328(22), 2242–2251. https://doi.org/10.1001/jama.2022.21893
• Dowell, D., Ragan, K. R., Jones, C. M., Baldwin, G. T., & Chou, R. (2022). CDC Clinical Practice Guideline for Prescribing Opioids for Pain – United States, 2022. MMWR. Recommendations and Reports, 71(3), 1–95. https://doi.org/10.15585/mmwr.rr7103a1

Related reading

• Metabolic Screening in Chronic Pain: Who to Test and What Changes
• Imaging for Low Back Pain and the Metabolic Workup the MRI Skips
• Laboratory Panels

Metabolic Screening in Chronic Pain: Who to Test and What Changes

Screen chronic pain patients whose pain limits work, self-care or activity, or who hurt at multiple sites: that pain history predicts cardiometabolic death. Fasting insulin, the triglyceride-glucose index and body composition find the risk that glucose and CRP miss.

Pain that limits function and spreads across several sites carries mortality risk that survives adjustment. That turns the pain history into a screening trigger, not only a treatment problem.

The case for metabolic screening with chronic pain as the trigger rests on an epidemiologic finding most workups ignore: the pain history itself predicts cardiometabolic death, while the standard pain evaluation measures almost none of the cardiometabolic terrain. In most practices the back is managed in one silo and the glucose in another, and neither silo owns the patient.

The Cost of Pain Is Paid in Years, the Chapter 1 video of The Pained Brain by Dr. Gurpreet Singh Padda, MD, MBA, MHP, and Dr. KrisJay Fucanan, MD, makes that case for patients. For clinicians the translation is operational: which pain patients to screen, what the measurements add beyond glucose and CRP, what a finding changes, and how it is documented.

Does chronic pain raise the risk of early death?

In UK Biobank participants aged 40 to 69, chronic widespread pain was associated with all-cause mortality of 2.28 in men and 2.31 in women against no chronic pain, attenuating to 1.47 once body mass, activity, smoking, alcohol and diet entered the model. In an American cohort of 19,487 adults over 50 followed for two decades, activity-limiting pain carried a hazard of 1.64 unadjusted and 1.52 after sociodemographic adjustment. With cardiac, oncologic, pulmonary and diabetic disease plus BMI added, it still carried 1.33. Severe pain without functional limitation, by contrast, sat at 1.05, not significant. Interference, not intensity, is the variable worth charting.

Site count behaves like a dose. Across 384,367 UK adults, the mortality hazard rose from 1.09 with one chronic musculoskeletal pain site to 1.46 with four. Neck or shoulder pain alone carried 1.99 for death from endocrine, nutritional and metabolic disease, in a model adjusted for age, sex, ethnicity and deprivation but not for BMI or diabetes.

Read the attenuation carefully. When adjustment for weight, diabetes and heart disease shrinks the pain association, the absorbed variance sits in the metabolic disease. Arithmetic cannot say whether those variables confound or mediate. Clinically, the answer is the same either way: the risk lives where it can be measured.

A Danish interdisciplinary pain center linked 6,142 patients to the national death register and found a standardized mortality ratio of 6.2, with circulatory deaths at 5.7, adjusted only for age and sex.

Who needs metabolic screening for chronic pain?

A practical selection rule follows from those cohorts. Consider cardiometabolic measurement in chronic pain patients who have:

• pain that limits work, self-care or activity, regardless of the intensity score;
• pain at multiple sites, recorded as a count rather than as the worst site;
• central adiposity with a glucose and A1c that have been called normal;
• a normal BMI with East Asian or South Asian ancestry, where visceral and hepatic fat run ahead of weight;
• depression or anxiety alongside the pain, given that 39.3% of adults with chronic pain carry clinically significant depressive symptoms and 40.2% anxiety symptoms across pooled studies.

These criteria map onto existing selection criteria and can be written as a standing order for screening, so the pain history triggers the measurement without a separate decision at every visit.

Which blood tests find metabolic risk in chronic pain?

Glucose is a late signal. Hyperinsulinemia, defined as fasting insulin above 10 µU/mL, was present in 41.4% of nondiabetic NHANES adults in 2017-2018, and HOMA-IR insulin resistance in 38.4%. The HOMA-IR threshold of 2.6 behind those figures is a population percentile; no consensus diagnostic cutoff exists, so serial values within one laboratory are more informative than a single reading.

The triglyceride-glucose index is computable from labs already on file. In 3,546 Chinese adults with a mean BMI of 23.76 followed nine years, each one-unit rise predicted new severe chronic pain at 1.51, and baseline BMI did not differ between those who developed pain and those who did not, 24.06 against 23.75. In American survey data the index stayed associated with chronic pain after adjustment for BMI and diabetes status, at 1.25, and within the chronic pain group the top tertile carried 2.05 times the all-cause mortality of the bottom.

CRP is a weak screening anchor. A visceral-fat score predicted chronic pain in 5,905 NHANES adults, with CRP mediating 7.4% of the effect, and Mendelian randomization finds no causal effect of CRP on spinal pain. Prospectively, hs-CRP alone did not predict incident chronic musculoskeletal pain, yet hs-CRP at or above 3 mg/L combined with sleeplessness carried 2.47. The marker means more read against the sleep history than read alone. The underlying model is inflammation that fails to resolve, metaflammation, supported by gene-expression work in acute low back pain whose human arm remains observational.

What changes when a pain patient’s metabolic screen is abnormal?

A normoglycemic patient with hyperinsulinemia, a high triglyceride-glucose index or a visceral-predominant body composition is reclassified from a pain problem with normal labs to a pain problem inside metabolic disease. That changes the plan: lifestyle and behavioral work moves from discharge advice to the core of treatment, the interval for repeat measurement is set in advance, and procedures are framed as a bridge to terrain repair rather than the whole plan.

The evidence base for pain treatment rarely describes this patient. Half of 168 randomized trials in nonspecific low back pain excluded prior or scheduled surgery, while among 500,295 UK adults, 69.1% of those with chronic pain had at least one long-term condition and 36.2% had two or more. Guideline-derived care was built on somebody else, which is the argument for measuring the person in front of you. It takes some humility for pain medicine, Dr. Padda’s own specialty, to admit that of the twelve chronic pain modalities the American Society of Anesthesiologists lists, none addresses systemic inflammation.

The drivers are not only biological. At age 52, pain was reported by 40% of Americans born in 1965 without a bachelor’s degree against 32% of the 1955 cohort, rising 0.6 percentage points per birth year without a degree and 0.2 with one; body mass explained about a quarter. Pain prevalence reaches 31.4% in nonmetropolitan counties. Screening that follows only symptoms will miss the populations where the gradient is steepest.

Where Measura fits in the workflow

Measura [Cardiometabolic and Autonomic Health Analysis] is a testing service under physician medical direction. It performs and reports measurements; diagnosis and management stay with the ordering physician. For this indication the relevant tests are laboratory panels that add fasting insulin and the lipid pattern to glucose and A1c, bioimpedance body composition to separate fat and lean compartments that BMI conflates, and arterial stiffness and endothelial function for the vascular consequence of sustained hyperinsulinemia.

Documentation should carry the variables the cohorts validated: pain site count, whether pain limits activity, waist circumference in centimeters, fasting insulin with glucose and lipids, and a mood screen. Structured fields make those values reportable and trendable, and getting results into the record keeps them in front of the next clinician. For context, under 12.2% of US adults met full metabolic-health criteria on NHANES 2009–2016 and under 7% on the tighter post-2021 criteria; in Dr. Padda’s practice, under 1% of chronic pain patients do, practice-reported figures from our own population, not trial outcomes, with individual results that vary. The study-level detail is in the Chapter 1 supplement, and the diagnostic framework that follows is in the physician article on screening the terrain before escalating care.

Frequently asked questions

References

• Ruan, H., Yang, Y., & Grol-Prokopczyk, H. (2026). Which is More Predictive of Mortality-Pain Severity or Pain Interference? Evidence from 20-Year Longitudinal Data. The Journal of Pain, 40, 106192. https://doi.org/10.1016/j.jpain.2026.106192
• Chen, L., Ferreira, M. L., Nassar, N., Preen, D. B., Hopper, J. L., Li, S., Bui, M., Beckenkamp, P. R., Shi, B., Arden, N. K., & Ferreira, P. H. (2021). Association of chronic musculoskeletal pain with mortality among UK adults: A population-based cohort study with mediation analysis. EClinicalMedicine, 42, 101202. https://doi.org/10.1016/j.eclinm.2021.101202
• Macfarlane, G. J., Beasley, M., & Jones, G. T. (2023). Chronic pain and premature mortality in men and women, using data from UK Biobank. The Journal of Clinical Investigation, 133(5), e166949. https://doi.org/10.1172/JCI166949
• Vaegter, H. B., Støten, M., Silseth, S. L., Erlangsen, A., Handberg, G., Sondergaard, S., & Stenager, E. (2019). Cause-specific mortality of patients with severe chronic pain referred to a multidisciplinary pain clinic: a cohort register-linkage study. Scandinavian Journal of Pain, 19(1), 93–99. https://doi.org/10.1515/sjpain-2018-0094
• Zhou, D., Jin, F., Zhang, L., Chen, J., Tian, L., & Li, J. (2026). The Mediating Role of WBC in the Relationship Between Triglyceride-Glucose Index and Chronic Pain: Evidence From NHANES 2001-2004 Data. Pain Research & Management, 2026(1), e3793191. https://doi.org/10.1155/prm/3793191
• Skarpsno, E. S., Mork, P. J., Nilsen, T. I. L., Steingrímsdóttir, Ó. A., Zwart, J. A., & Nilsen, K. B. (2019). The interplay between sleeplessness and high-sensitivity C-reactive protein on risk of chronic musculoskeletal pain: longitudinal data from the Tromsø Study. Sleep, 42(9), zsz127. https://doi.org/10.1093/sleep/zsz127
• McQueenie, R., Jani, B. D., Siebert, S., McLoone, P., McCowan, C., Macdonald, S., Mair, F. S., & Nicholl, B. I. (2021). Prevalence of chronic pain in LTCs and multimorbidity: A cross-sectional study using UK Biobank. Journal of Multimorbidity and Comorbidity, 11, Article 26335565211005870. https://doi.org/10.1177/26335565211005870
• McMasters, M., & Mora, J. (2025). Addressing Meta-Inflammation in the Comprehensive Management of Chronic Pain. Cureus, 17(10), e94863. https://doi.org/10.7759/cureus.94863
• Aaron, R. V., Ravyts, S. G., Carnahan, N. D., Bhattiprolu, K., Harte, N., McCaulley, C. C., Vitalicia, L., Rogers, A. B., Wegener, S. T., & Dudeney, J. (2025). Prevalence of Depression and Anxiety Among Adults With Chronic Pain: A Systematic Review and Meta-Analysis. JAMA Network Open, 8(3), Article e250268. https://doi.org/10.1001/jamanetworkopen.2025.0268
• Case, A., Deaton, A., & Stone, A. A. (2020). Decoding the mystery of American pain reveals a warning for the future. Proceedings of the National Academy of Sciences of the United States of America, 117(40), 24785-24789. https://doi.org/10.1073/pnas.2012350117

Related reading

• Preoperative Diabetes Screening Before Pain Procedures and Surgery
• Laboratory Panels

Low-Carb Diet Safety: A Physician’s Baseline and Re-Measure Plan

Low-carb diet safety is a baseline problem: flag patients on insulin, sulfonylureas, meglitinides, SGLT2 inhibitors or two or more antihypertensives, record autonomic, balance, cognitive and body-composition baselines, and schedule a repeat measurement. Hypoglycemia, euglycemic ketoacidosis and orthostatic falls are the predictable risks.

The patient who quietly cuts carbohydrate arrives at the next visit with a lower glucose, a lower pressure and the same prescriptions. The workup belongs before the diet, not after the first event.

Low-carb diet safety is a primary care problem before it is a nutrition problem. Patients read about carbohydrate restriction for metabolic and brain health, start without telling anyone, and the medication list written for their old diet keeps running. The Starved Brain by Dr. Gurpreet Singh Padda, MD, MBA, MHP, closes with a chapter, and a video, You Can Protect a Struggling Neuron, that put the safety evidence ahead of the protocol for exactly that reason. For the screening physician the lesson is a sequence: identify who is at risk, record the baseline that makes adverse effects visible, and schedule the repeat that shows whether the correction is working. Measura [Cardiometabolic and Autonomic Health Analysis] supplies measurement for that sequence; it does not prescribe diet or manage medication.

What are the risks of a low-carb diet for patients on medication?

• Hypoglycemia on insulin, sulfonylureas and meglitinides. The 2025 ADA Standards call for consistent medical oversight of very-low-carbohydrate eating and recognize that diabetes medications may need adjustment to prevent hypoglycemia. Practical guides published in 2019 and 2021 describe dose reductions at initiation rather than after the first low reading. In a remotely supervised cohort of 262 adults with type 2 diabetes, sulfonylurea use went from 23.7% to 0% in a year under daily glucose review. No study has put a clock on the first hypoglycemic event; Dr. Padda reports seeing it within days in his own patients.
• Euglycemic ketoacidosis on SGLT2 inhibitors. The FDA relabeled the class in December 2015 after 73 reports; median reported glucose was 211 mg/dL, and a low-carbohydrate diet was named among the risk factors. In FAERS, 71% of reports with laboratory data were euglycemic. Among 208,757 new users, ketoacidosis carried HR 2.85 against DPP-4 inhibitors. Published cases include patients sent home because hyperglycemia was not marked.
• Orthostatic symptoms on antihypertensives. Sodium loss dominates the first week. On a metabolic ward, symptomatic orthostatic hypotension occurred in 7 of 7 obese adults on a ketogenic protein diet. In DiRECT, among 69 participants who stopped all antihypertensives at the start of a formula diet, dizziness affected 36% and 27.5% needed a drug restarted, most of them previously on two or more.

Who should be flagged before starting a low-carb diet?

The list is short: patients on insulin, a sulfonylurea or a meglitinide; anyone on an SGLT2 inhibitor; two or more antihypertensives; pregnancy or lactation; kidney, liver, gallbladder or pancreatic disease; a history of disordered eating; a suspected inherited disorder of fat metabolism, where the diet is contraindicated; and moderate or advanced dementia. The 2025 ADA Standards state that very-low-carbohydrate plans are not currently recommended in pregnancy or lactation, in children, in kidney disease, or in people with or at risk for disordered eating. A flag raised at the metabolic or cognitive workup is easier to act on than one raised in the emergency department, and standing orders make that flag reproducible across a panel.

Why does a low-carb diet cause dizziness and falls?

The orthostatic data expose a measurement gap. A seated blood pressure at a routine visit says little about how an older patient on two or three antihypertensives will tolerate a week of sodium and water loss. Cardiac autonomic reflex tests and heart rate variability characterize autonomic regulation of heart rate and blood pressure, and vestibular and balance testing documents balance before a change known to produce dizziness on standing. A patient who already has impaired autonomic regulation or a balance deficit is the one in whom a predictable orthostatic drop is most likely to end on the floor. Recording that baseline ties the metabolic plan to fall prevention, the pairing outlined in cognitive assessment and fall prevention.

Cognitive and body-composition anchors

The USPSTF grades cognitive screening of asymptomatic adults over 65 as insufficient evidence, and the AAN guideline that recommended validated assessment has since been retired. Neither addresses a personal baseline in a patient with a concern who is about to change a major metabolic input. Cognitive assessment in that setting is not population screening; it is the comparison point for the next score.

Stage changes the calculation. In the KDRAFT pilot, 1 of 7 participants with very mild Alzheimer’s withdrew, and all 4 with moderate disease withdrew, each citing caregiver burden. The 2024 ESPEN guideline does not recommend routine ketogenic diets in dementia and treats malnutrition screening as essential. In 37,717 Korean adults newly diagnosed with dementia, being underweight after diagnosis carried HR 1.57 for death. Bioimpedance body composition gives a lean-mass reference, so weight loss in an older patient is read by compartment rather than by the scale.

When should labs be rechecked after starting a low-carb diet?

Laboratory panels drawn before the change should report fasting insulin as a number. In Whitehall II, modeled insulin sensitivity fell steeply over the five years before diabetes while glucose inflected only three years before. A single fasting value has limits: in 4,185 people with normal glucose tolerance it was of limited value for detecting dynamic hyperinsulinemia. The triglyceride-to-HDL ratio performed poorly in 98 overweight African American adults, AUC 0.56 against 0.85 for fasting insulin, so cut-points derived in white cohorts should not be transferred. Every marker then keeps its own clock:

• About ten weeks. In the supervised cohort, 84% of the one-year HbA1c fall, 90% of the fasting-glucose fall and 73% of the fasting-insulin fall were present by day 70.
• Months. Homocysteine; no trial has defined a weeks-scale course.
• About six months. Red-cell EPA reaches steady state after 180 days, so the omega-3 index plateaus late.
• Slowest. hs-CRP did not change significantly across 44 randomized ketogenic trials. A flat CRP at three months is not a failed intervention.

Documentation and workflow

The sequence documents cleanly. A metabolic panel, cognitive score and autonomic or balance baseline recorded before dietary counseling sit naturally within the annual wellness visit and chronic care follow-up, and repeats at ten weeks and six months give the chart a dated trajectory rather than a single value. Findings route to the ordering physician; see getting results into the record. The deeper failure is structural: carbohydrate restriction spreads through patient communities faster than medication plans are rewritten, and a regimen dosed for the old diet keeps working against the new one. The full safety evidence, with case reports and declared industry ties, is in the Chapter 10 companion evidence guide; the cognitive trial evidence is in ketogenic therapy in mild cognitive impairment.

Frequently asked questions

References

• American Diabetes Association Professional Practice Committee. (2025a). 5. Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes: Standards of Care in Diabetes—2025. Diabetes Care, 48(Suppl. 1), S86–S127. https://doi.org/10.2337/dc25-S005
• Blau, J. E., Tella, S. H., Taylor, S. I., & Rother, K. I. (2017). Ketoacidosis associated with SGLT2 inhibitor treatment: Analysis of FAERS data. Diabetes/Metabolism Research and Reviews, 33(8), Article e2924. https://doi.org/10.1002/dmrr.2924
• Douros, A., Lix, L. M., Fralick, M., Dell’Aniello, S., Shah, B. R., Ronksley, P. E., Tremblay, É., Hu, N., Alessi-Severini, S., Fisher, A., Bugden, S. C., Ernst, P., Filion, K. B., & the Canadian Network for Observational Drug Effect Studies (CNODES) Investigators. (2020). Sodium–glucose cotransporter-2 inhibitors and the risk for diabetic ketoacidosis: A multicenter cohort study. Annals of Internal Medicine, 173(6), 417–425. https://doi.org/10.7326/M20-0289
• DeHaven, J., Sherwin, R., Hendler, R., & Felig, P. (1980). Nitrogen and sodium balance and sympathetic-nervous-system activity in obese subjects treated with a low-calorie protein or mixed diet. The New England Journal of Medicine, 302(9), 477–482. https://doi.org/10.1056/NEJM198002283020901
• Leslie, W. S., Ali, E., Harris, L., Messow, C. M., Brosnahan, N. T., Thom, G., McCombie, E. L., Barnes, A. C., Sattar, N., Taylor, R., & Lean, M. E. J. (2021). Antihypertensive medication needs and blood pressure control with weight loss in the Diabetes Remission Clinical Trial (DiRECT). Diabetologia, 64(9), 1927–1938. https://doi.org/10.1007/s00125-021-05471-x
• Taylor, M. K., Sullivan, D. K., Mahnken, J. D., Burns, J. M., & Swerdlow, R. H. (2018). Feasibility and efficacy data from a ketogenic diet intervention in Alzheimer’s disease. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 4, 28–36. https://doi.org/10.1016/j.trci.2017.11.002
• Huh, Y., Nam, G. E., Han, K., Jung, J.-H., Kim, B. S., Lee, D., Park, H. J., Yoo, M. Y., Yoon, S. Y., Kang, S. H., Kim, C. K., Kim, S. M., & Park, H. S. (2026). Body mass index levels and changes before and after dementia diagnosis and risk of all-cause mortality: A nationwide cohort study. Alzheimer’s Research & Therapy, 18(1), article 10.1186/s13195–026–02002–x (page not assigned in PubMed record). https://doi.org/10.1186/s13195-026-02002-x
• Hallberg, S. J., McKenzie, A. L., Williams, P. T., Bhanpuri, N. H., Peters, A. L., Campbell, W. W., Hazbun, T. L., Volk, B. M., McCarter, J. P., Phinney, S. D., & Volek, J. S. (2018). Effectiveness and safety of a novel care model for the management of type 2 diabetes at 1 year: An open-label, non-randomized, controlled study. Diabetes Therapy, 9(2), 583–612. https://doi.org/10.1007/s13300-018-0373-9
• Ji, J., Fotros, D., Sohouli, M. H., Velu, P., Fatahi, S., & Liu, Y. (2025). The effect of a ketogenic diet on inflammation-related markers: A systematic review and meta-analysis of randomized controlled trials. Nutrition Reviews, 83(1), 40–58. https://doi.org/10.1093/nutrit/nuad175
• US Preventive Services Task Force (Owens, D. K., Davidson, K. W., Krist, A. H., Barry, M. J., Cabana, M., Caughey, A. B., Doubeni, C. A., Epling, J. W., Kubik, M., Landefeld, C. S., Mangione, C. M., Pbert, L., Silverstein, M., Simon, M. A., Tseng, C.-W., & Wong, J. B.). (2020). Screening for cognitive impairment in older adults: US Preventive Services Task Force recommendation statement. JAMA, 323(8), 757–763. https://doi.org/10.1001/jama.2020.0435

Related reading

• Ketogenic Diet, Mild Cognitive Impairment and the Screening Workup
• Cardiac Autonomic Reflex Tests

Ketogenic Diet, Mild Cognitive Impairment and the Screening Workup

The ketogenic diet produces modest, reproducible cognitive gains in mild cognitive impairment, MMSE up 1.25 points across ten pooled trials with daily function unchanged, but those trials excluded the insulin-resistant patient most panels carry. The screening workup is a metabolic and cognitive baseline before any supervised trial.

Patients with memory complaints now arrive asking about ketones. The evidence is modest, specific and built on exclusions, and it names the baseline numbers a supervised trial needs.

Questions that pair the ketogenic diet, mild cognitive impairment and memory now reach primary care before physicians raise the subject, and most of what patients have read is either promotion or dismissal. The evidence reviewed in The Starved Brain by Dr. Gurpreet Singh Padda, MD, MBA, MHP, and in its chapter video, One Correction, Many Diseases, supports a narrower position: guideline-level therapy in drug-resistant epilepsy, modest reproducible cognitive effects in MCI and early Alzheimer’s disease, and an unresolved signal in Parkinson’s disease. For the screening physician the useful question is not whether to endorse a diet. It is who warrants a metabolic and cognitive baseline, and what that baseline changes. Measura [Cardiometabolic and Autonomic Health Analysis] provides that measurement layer and does not treat.

Does a ketogenic diet help mild cognitive impairment? Effect sizes at their true size

• BENEFIC randomized 122 adults aged 55 and older with MCI to 30 g a day of ketogenic MCT emulsion or calorie-matched placebo for six months; 83 completed. Word recall, verbal fluency, naming and Trail-Making errors improved after adjustment, and the change in blood ketones correlated with cognitive change (r = +0.325 for fluency). Discontinuation was 32%, gastrointestinal adverse events occurred in 74% of drink completers against 40% on placebo, and no Alzheimer’s biomarker moved.
• Rong 2024 pooled ten randomized trials, 691 participants, 12 to 60 weeks: MMSE +1.25 (95% CI 0.46 to 2.04), ADAS-Cog −3.43, activities of daily living unchanged (P = 0.95). Eight trials used MCT, and the funnel plot suggested publication bias for MMSE.
• The whole-diet crossover (Phillips 2021) in 26 people with probable Alzheimer’s: daily function +3.13 against a prespecified meaningful difference of 2, quality of life +3.37, cognition unchanged (P = 0.24).

For context, lecanemab slowed decline by 0.45 points on an 18-point scale over 18 months with imaging edema in 12.6%, and donanemab by 0.70 points over 76 weeks with edema in 24.0%. Scales, durations and constructs differ, so these are not head-to-head comparisons, and improvement is a different quantity from slowed decline. They do set the backdrop for a modest nutritional signal, following a registry record in which 99.6% of Alzheimer’s drug trials registered between 2002 and 2012 failed.

Who did the ketogenic diet trials exclude?

BENEFIC excluded uncontrolled diabetes, cardiac, hepatic and renal disease, uncontrolled hypertension and dyslipidemia, and B12 deficiency. The Alzheimer’s diet trial excluded moderate or severe depression, substantial cerebrovascular disease, and abnormal B12, folate or thyroid values. The PET studies establishing preserved ketone uptake selected participants for a similar metabolic phenotype. The insulin-resistant older adult with hepatic steatosis who dominates a primary care panel was, by design, absent.

Two consequences follow. First, the nutrient hypothesis, that a whole-food ketogenic diet repletes B12, choline and DHA as well as correcting fuel supply, was screened out rather than tested; a trial that excludes deficiency cannot detect a repletion effect. Second, response in the metabolically complex patient is uncertain in both directions. The BENEFIC authors anticipated a reduced response in prediabetic older adults, while the 2026 Washington University trial in prediabetes with fatty liver, holding weight loss at 10% in every arm, found hepatic insulin sensitivity improved two to three times more on the ketogenic diet than on the Mediterranean diet (p < 0.001), with no between-group difference in LDL cholesterol or apoB. That trial is so far reported in abstract. Uncertainty of that shape argues for baseline measurement, not for a blanket recommendation in either direction.

Does APOE4 status predict response to a ketogenic diet?

Carrier status is the objection patients raise most, and the data do not run one way. In a Stockholm cohort of 2,157 adults aged 60 and over without dementia at entry, 569 of them carriers, the highest meat-intake quintile carried a dementia subhazard of 0.45 (95% CI 0.21 to 0.95) among carriers, with a non-significant genotype interaction for dementia and a clearer interaction on global cognition. Against that, pooled MCT trials favored non-carriers (SMD 1.87), and an umbrella review found dietary interventions other than the Mediterranean pattern generally ineffective in older carriers, while small exploratory BENEFIC subgroups pointed the other way. The defensible reading is heterogeneity: carriers appear more sensitive to metabolic inputs, and the direction in an individual has to be observed rather than assumed.

The baseline that makes a supervised trial interpretable

For a patient with MCI, subjective decline or a strong family history who is considering supervised ketogenic therapy, a defensible pre-intervention set looks like this:

• Cognitive assessment, because every positive trial reported change on a scored instrument, and an individual needs the same anchor. Pairing it with fall-risk work is covered in cognitive assessment and fall prevention.
• Laboratory panels with fasting insulin reported as a number, lipids including apoB or particle measures, and a plan for beta-hydroxybutyrate monitoring through the supervising clinician. Across 62 randomized trials in adults, triglycerides fell 19.96 mg/dL while LDL cholesterol rose 8.49 mg/dL; the Parkinson’s pilot saw LDL rise 0.70 mmol/L in eight weeks. The diet trials that separated ran beta-hydroxybutyrate between 0.95 and 1.3 mmol/L, and the 2026 Parkinson’s crossover defined nutritional ketosis as above 0.5 mM.
• Bioimpedance body composition, since weight fell 2.62 kg in the Alzheimer’s diet trial, and an older adult losing lean mass is a different outcome from one losing visceral fat.

Dr. Padda’s threshold for concern is a fasting insulin above 10 µIU/mL, stated as his clinic cutoff; the published neighbor is a level above 9.0 that identified 80% of prediabetes in one practice. In 683 older Manhattan adults, hyperinsulinemia carried HR 2.1 for Alzheimer’s disease.

What safety signals come before ordering a ketogenic diet?

The Parkinson’s pilot reported transient worsening of tremor or rigidity in 12 of 24 ketogenic patients during weeks one to four. A 2026 case series described nine cases of hypomania or mania within two months of starting a ketogenic diet, seven without prior bipolar history, with no denominator. A bipolar pilot recorded euglycemic ketoacidosis in a participant taking an SGLT2 inhibitor. Diabetes, antihypertensive and cholinesterase-inhibitor regimens were excluded from the MCI trial rather than managed within it. Those are prescriber conversations that precede any dietary counseling, and measurement ordered under standing orders for screening makes the sequence reproducible.

Documentation and workflow

A cognitive baseline and metabolic panel fit structures practices already run. The annual wellness visit is a natural home for a documented cognitive score that becomes the comparison point for the next visit, and findings can be recorded against the quality concepts described in MIPS and quality reporting. The system failure is familiar: nutrition is delegated to a handout while visit time goes to prescriptions, and a diet nobody measures cannot be told apart from a diet that failed. Adherence is the other constraint; a modified Atkins pilot found 27 willing patients in two and a half years. A repeat panel at three months tells physician and patient whether the correction is happening at all. Primary studies, methods, sponsorship and limits are laid out in the Chapter 9 companion evidence guide, and the pre-diet safety workup and re-measure schedule continue in low-carb diet safety for physicians.

Frequently asked questions

References

• Fortier, M., Castellano, C.-A., St-Pierre, V., Myette-Côté, É., Langlois, F., Roy, M., Morin, M.-C., Bocti, C., Fulop, T., Godin, J.-P., Delannoy, C., Cuenoud, B., & Cunnane, S. C. (2021). A ketogenic drink improves cognition in mild cognitive impairment: Results of a 6-month RCT. Alzheimer’s & Dementia, 17(3), 543–552. https://doi.org/10.1002/alz.12206
• Rong, L., Peng, Y., Shen, Q., Chen, K., Fang, B., & Li, W. (2024). Effects of ketogenic diet on cognitive function of patients with Alzheimer’s disease: A systematic review and meta-analysis. The Journal of Nutrition, Health and Aging, 28(8), 100306. https://doi.org/10.1016/j.jnha.2024.100306
• Phillips, M. C. L., Deprez, L. M., Mortimer, G. M. N., Murtagh, D. K. J., McCoy, S., Mylchreest, R., Gilbertson, L. J., Clark, K. M., Simpson, P. V., McManus, E. J., Oh, J.-E., Yadavaraj, S., King, V. M., Pillai, A., Sequeira, B., Rodgers, B., Wiltshire, C., Tanner, S., & Tisch, S. (2021). Randomized crossover trial of a modified ketogenic diet in Alzheimer’s disease. Alzheimer’s Research & Therapy, 13(1), 51. https://doi.org/10.1186/s13195-021-00783-x
• van Dyck, C. H., Swanson, C. J., Aisen, P., Bateman, R. J., Chen, C., Gee, M., Kanekiyo, M., Li, D., Reyderman, L., Cohen, S., Froelich, L., Katayama, S., Sabbagh, M., Vellas, B., Watson, D., Dhadda, S., Irizarry, M., Kramer, L. D., & Iwatsubo, T. (2023). Lecanemab in early Alzheimer’s disease. The New England Journal of Medicine, 388(1), 9–21. https://doi.org/10.1056/NEJMoa2212948
• Sims, J. R., Zimmer, J. A., Evans, C. D., Lu, M., Ardayfio, P., Sparks, J., Wessels, A. M., Shcherbinin, S., Wang, H., Monkul Nery, E. S., Collins, E. C., Solomon, P., Salloway, S., Apostolova, L. G., Hansson, O., Ritchie, C., Brooks, D. A., Mintun, M., Skovronsky, D. M., & TRAILBLAZER-ALZ 2 Investigators. (2023). Donanemab in early symptomatic Alzheimer disease: The TRAILBLAZER-ALZ 2 randomized clinical trial. JAMA, 330(6), 512–527. https://doi.org/10.1001/jama.2023.13239
• Cummings, J. L., Morstorf, T., & Zhong, K. (2014). Alzheimer’s disease drug-development pipeline: Few candidates, frequent failures. Alzheimer’s Research & Therapy, 6(4), 37. https://doi.org/10.1186/alzrt269
• Norgren, J., Carballo-Casla, A., Grande, G., Börjesson-Hanson, A., Xu, H., Eriksdotter, M., Laukka, E. J., & Garcia-Ptacek, S. (2026). Meat consumption and cognitive health by APOE genotype. JAMA Network Open, 9(3), Article e266489. https://doi.org/10.1001/jamanetworkopen.2026.6489
• Sun, L., Ye, K. X., Wong, H. L. K., Wang, L., Lim, S. L., Chao, Y. X., Zhang, C., Yap, K. Z., & Feng, L. (2023). The effects of medium chain triglyceride for Alzheimer’s disease related cognitive impairment: A systematic review and meta-analysis. Journal of Alzheimer’s Disease, 94(2), 441–456. https://doi.org/10.3233/JAD-230406
• Petersen, M. C., Smith, G. I., Farabi, S. S., Palacios, H. H., Shankaran, M., Hellerstein, M. K., Patterson, B. W., & Klein, S. (2026). Effect of diet macronutrient content on the cardiometabolic response to weight loss: A randomized clinical trial. Cell Metabolism. Advance online publication. https://doi.org/10.1016/j.cmet.2026.07.020
• Chang, C., Liu, Y., Rohani, P., Khodadadi, N., Prabahar, K., & Sohouli, M. H. (2026). The impact of the ketogenic diet on the lipid profile in adults: A comprehensive review and meta-regression analysis of randomized controlled trials. Endocrine Practice, 32(5), 819–828. https://doi.org/10.1016/j.eprac.2026.01.009

Related reading

• Periodontal Disease and Dementia: A Screening Workflow
• Low-Carb Diet Safety: A Physician’s Baseline and Re-Measure Plan
• Cognitive Assessment

Periodontal Disease and Dementia: A Screening Workflow

The oral exposure tied to dementia risk is severe periodontitis, and it lives in a dental chart that most medical records never import. Closing that gap is a workflow decision before it is a research question.

The periodontal disease dementia literature has matured past the point where it can be dismissed, and not to the point where it supports an intervention claim. Dr. Padda’s companion video for the book, The Gum Bacterium in 96% of Alzheimer’s Brains, reviews the argument from The Starved Brain by Dr. Gurpreet Singh Padda, MD, MBA, MHP, including a correction of a claim his own side repeats. For a practice, the usable output is narrower than the headline: which patients carry the exposure, what documentation connects it to the cognitive and metabolic workup, and what a finding changes. Measura [Cardiometabolic and Autonomic Health Analysis] performs no dental, salivary or microbial testing. Its role here is the metabolic, vascular and cognitive measurement in the same patient.

Is periodontal disease a risk factor for dementia?

Five syntheses from independent teams land in a narrow band. Nadim pooled cohorts at RR 1.18 (1.06–1.31). Larvin reported dementia RR 1.22 and cognitive decline RR 1.33. Dibello reproduced dementia RR 1.22 and ran depression as a negative control, which came back null at RR 1.07 (0.95–1.21). The 2025 umbrella review gives cohorts RR 1.26 (1.20–1.32), low to moderate certainty by GRADE. Measurement quality points the right way: self-reported periodontitis produced weaker estimates than clinically examined disease, the pattern expected from a real exposure measured imperfectly.

The clinically decisive finding is severity. Pooling 13 case-control and 11 cohort studies, severe periodontitis carried OR 2.85 (2.16–3.74), while less-than-moderate disease carried OR 0.94 (0.64–1.40). Screening should therefore ask for staging, not a yes or no. The largest single estimate, HR 1.79 in 56,018 Taiwanese adults from claims data, partly measures who seeks care: people who see a dentist also see physicians.

Can periodontal bacteria reach the brain? Mechanism, with provenance

Dominy and colleagues found arginine-gingipain B in 51 of 53 Alzheimer’s temporal cortex samples, and lysine-gingipain in 91%, with RgpB tracking tau at r = 0.674 and ubiquitin at 0.786. The control column is less often quoted: RgpB in 18 of 46 non-demented samples, Kgp in 52%, and the bacterial gene in five of six control brains by qPCR. Twelve of twenty-five authors were employees of the company developing the inhibitor, and independent replication of the brain immunohistochemistry has not appeared. Ilievski’s wild-type mouse study, 10 exposed and 10 controls over 22 weeks, showed that oral inoculation can produce hippocampal inflammation, Aβ1–42 and phospho-tau. It reported pathology, not cognition. And a prospective human serology study of 158 cognitively intact adults found baseline antibodies in future cases to Fusobacterium nucleatum and Prevotella intermedia, not P. gingivalis. A 2026 review still judges that confounding, reverse causation and dental-care access preclude causal inference.

Does targeting P. gingivalis slow Alzheimer’s? GAIN and the genetic nulls

GAIN randomized 643 patients with mild-to-moderate Alzheimer’s at 93 sites to two doses of atuzaginstat or placebo for 48 weeks and missed both co-primary endpoints, ADAS-Cog11 and ADCS-ADL. Liver enzymes above three times the upper limit of normal occurred in 2% on placebo, 7% at 40 mg and 15% at 80 mg; FDA holds followed and the program closed in August 2022. In the pre-specified subgroup of 242 with salivary P. gingivalis DNA, ADAS-Cog11 decline was 57% slower at the higher dose, with no functional effect. The successor enrolls only organism-positive patients and reports in 2029. Two Mendelian randomization studies are null or unstable: Sun found OR 1.10 on one instrument set and 0.97 on a second, and Hu found no causal relationship.

The exclusion that matters to a primary care or endocrine panel: GAIN excluded HbA1c above 8 and BMI of 38 or more. The insulin-resistant, centrally obese patient whose inflammatory burden is highest never entered the one randomized test. A 48-week trial in established dementia may also be testing a decades-long exposure at the wrong end. That is a criticism of the design, not evidence for the drug.

Which patients should be screened for periodontal disease, and what does a finding change?

Ask about periodontal status, and request staging, in patients undergoing cognitive assessment, in patients with diabetes or insulin resistance, and in older adults with known severe disease or heavy tooth loss. The CDC full-mouth survey of 10,683 dentate adults found periodontitis in 42% of those 30 to 79 and severe disease in 7.8%, and partial-mouth protocols can underestimate prevalence by more than 50%, so a full-mouth chart with periodontal inflamed surface area is the document worth requesting. The structural driver is that the dental and medical records sit in different buildings, maintained by different systems, and neither side is prompted to ask for the other’s chart (selection criteria).

A finding of severe periodontitis changes management in concrete ways. It supports referral for periodontal treatment on its own merits: across 30 studies with 2,443 analyzed participants with diabetes, subgingival instrumentation lowered HbA1c by 0.43% at three to four months, moderate certainty, though 33 of 35 studies carried high or unclear risk of bias. It changes lab timing: in 120 patients with severe periodontitis, intensive treatment lowered flow-mediated dilatation and raised CRP and IL-6 at 24 hours, then improved dilatation by 180 days, so an hs-CRP drawn the day after treatment reads the procedure. And it argues for a cognitive assessment baseline, repeatable on the same instrument, rather than waiting for a complaint.

Where Measura measurement fits

Measura cannot stage the gums or detect the organism. It measures the terrain around the exposure. Laboratory panels put HbA1c, fasting insulin and inflammatory markers next to the dental chart; the Puerto Rico cohort of 1,206 overweight adults found that progression of attachment loss, IRR 1.25, rather than baseline periodontitis, tracked incident dysglycemia, so trending both charts together is more informative than either snapshot. Arterial stiffness and endothelial function testing covers the vascular domain in which the Tonetti trial documented systemic effects, without claiming to replicate its method. Bioimpedance body composition characterizes the adiposity that excluded patients from GAIN. Pair the cognitive baseline with fall-risk work where the patient population overlaps (cognitive assessment and fall prevention).

Documentation and workflow

Add periodontal staging to the history captured at the annual wellness visit, with the date of the dental chart it came from (annual wellness visit integration). Build the request for the dental chart into standing orders for patients meeting criteria, so it happens without depending on memory at the point of care (standing orders that make screening reproducible). A patient version of this material is written separately (the patient article on gum disease and dementia), the referenced evidence sits in the book companion (Chapter 8 companion), and the preceding physician article covers the metabolic inflammation that this oral source adds to (metaflammation screening).

Frequently asked questions

References

• Qadir, B. H., Mahmood, M. K., Amin, Y. M. M., Kurda, H. A., Rasheed, T. A., Noori, A. H., Noori, Z. F., Abdulghafor, M. A., Fadhil, H. N. M., Fatih, M. T., Tardivo, D., Tassery, H., & Lan, R. (2025). Periodontitis and tooth loss are associated with higher risks of cognitive disorders: A systematic umbrella meta-analysis. Clinical and Experimental Dental Research, 11(6), Article e70240. https://doi.org/10.1002/cre2.70240
• Kim, D.-H., & Han, G.-S. (2025). Periodontitis as a risk factor for dementia: A systematic review and meta-analysis. The Journal of Evidence-Based Dental Practice, 25(2), Article 102094. https://doi.org/10.1016/j.jebdp.2025.102094
• Larvin, H., Gao, C., Kang, J., Aggarwal, V. R., Pavitt, S., & Wu, J. (2023). The impact of study factors in the association of periodontal disease and cognitive disorders: Systematic review and meta-analysis. Age and Ageing, 52(2), Article afad015. https://doi.org/10.1093/ageing/afad015
• Dominy, S. S., Lynch, C., Ermini, F., Benedyk, M., Marczyk, A., Konradi, A., Nguyen, M., Haditsch, U., Raha, D., Griffin, C., Holsinger, L. J., Arastu-Kapur, S., Kaba, S., Lee, A., Ryder, M. I., Potempa, B., Mydel, P., Hellvard, A., Adamowicz, K., … Potempa, J. (2019). Porphyromonas gingivalis in Alzheimer’s disease brains: Evidence for disease causation and treatment with small-molecule inhibitors. Science Advances, 5(1), Article eaau3333. https://doi.org/10.1126/sciadv.aau3333
• Sparks Stein, P., Steffen, M. J., Smith, C., Jicha, G., Ebersole, J. L., Abner, E., & Dawson, D. (2012). Serum antibodies to periodontal pathogens are a risk factor for Alzheimer’s disease. Alzheimer’s & Dementia, 8(3), 196–203. https://doi.org/10.1016/j.jalz.2011.04.006
• Sun, Y.-Q., Richmond, R. C., Chen, Y., & Mai, X.-M. (2020). Mixed evidence for the relationship between periodontitis and Alzheimer’s disease: A bidirectional Mendelian randomization study. PLoS ONE, 15(1), Article e0228206. https://doi.org/10.1371/journal.pone.0228206
• Eke, P. I., Thornton-Evans, G. O., Wei, L., Borgnakke, W. S., Dye, B. A., & Genco, R. J. (2018). Periodontitis in US adults: National Health and Nutrition Examination Survey 2009–2014. Journal of the American Dental Association, 149(7), 576–588.e6. https://doi.org/10.1016/j.adaj.2018.04.023
• Simpson, T. C., Clarkson, J. E., Worthington, H. V., MacDonald, L., Weldon, J. C., Needleman, I., Iheozor-Ejiofor, Z., Wild, S. H., Qureshi, A., Walker, A., Patel, V. A., Boyers, D., & Twigg, J. (2022). Treatment of periodontitis for glycaemic control in people with diabetes mellitus. Cochrane Database of Systematic Reviews, 4(4), Article CD004714. https://doi.org/10.1002/14651858.CD004714.pub4
• Tonetti, M. S., D’Aiuto, F., Nibali, L., Donald, A., Storry, C., Parkar, M., Suvan, J., Hingorani, A. D., Vallance, P., & Deanfield, J. (2007). Treatment of periodontitis and endothelial function. New England Journal of Medicine, 356(9), 911–920. https://doi.org/10.1056/NEJMoa063186
• Joshipura, K. J., Muñoz-Torres, F. J., Dye, B. A., Leroux, B. G., Ramírez-Vick, M., & Pérez, C. M. (2018). Longitudinal association between periodontitis and development of diabetes. Diabetes Research and Clinical Practice, 141, 284–293. https://doi.org/10.1016/j.diabres.2018.04.028

Related reading

• Metaflammation Screening: What the Standard Panel Misses
• Ketogenic Diet, Mild Cognitive Impairment and the Screening Workup
• Cognitive Assessment

Metaflammation Screening: What the Standard Panel Misses

Metaflammation screening in primary care measures what the standard panel misses: fasting glucose and HbA1c flag only the patient whose compensation has already failed. Waist circumference, body composition, measured resting energy expenditure, fasting insulin, uric acid, hs-CRP and oxidized LDL fill the gap, starting with patients who carry central adiposity at any BMI.

Chronic metabolic inflammation is clinically silent, and the panel most practices order was never designed to find it. The practical questions are who to measure, with what, and what a result changes.

Metaflammation, Hotamisligil’s term for chronic inflammation driven by metabolic excess, has a screening problem built into its definition: it produces no findings on examination and no complaint at the front desk. The chapter video, Fructose Turns the Famine Signal On, lays out the case from The Starved Brain by Dr. Gurpreet Singh Padda, MD, MBA, MHP that fructose load, visceral fat and diet-related endotoxin keep that inflammation running, with consequences reaching the brain. Measura [Cardiometabolic and Autonomic Health Analysis] is a testing protocol, not a treatment service, so the relevant question for a practice is operational. Which patients should be measured, which measurements add information the routine panel does not, and what does a result change?

The evidence tier, stated once

The fructose argument is a hypothesis. Johnson’s 2020 paper reports no trial and no new cohort, and four of its eight authors declared equity in a company developing inhibitors of fructose metabolism. The human data underneath it come from liver, not brain: in 25 obese adults with type 2 diabetes studied by phosphorus spectroscopy, those eating 15 g of fructose a day or more showed a greater fall in hepatic ATP, and those with uric acid at or above 5.5 mg/dL reached a lower nadir. The brain chain is thinner still. Two links are human: systemic inflammatory events in 222 community patients with Alzheimer’s disease meant 3.5 ADAS-Cog points lost over six months against 1.6, and synapse loss tracks cognition in small autopsy series. The middle, metabolic excess priming microglia that then strip synapses, is mouse work, and the human imaging is split: HOMA-IR tracked cortical TSPO binding in 57 unimpaired elders, while 12 BMI-discordant identical twin pairs showed no excess in the heavier twin. That tier does not argue against measuring. It argues against promising what a measurement predicts.

What does a standard metabolic panel miss?

Fasting glucose and HbA1c identify the patient whose compensation has already failed. They say nothing about fat distribution, lean mass, resting energy expenditure or inflammatory tone. The more interesting gap is in data already on the chart. Across 23 cohorts and 947,020 participants, a higher neutrophil-to-lymphocyte ratio predicted incident dementia, HR 1.24 (1.15–1.34), with heterogeneity high at I² of 95%. In 161,968 UK Biobank adults, the neutrophil count carried HR 1.08 while the linear CRP hazard sat at 0.95. Cell counts associate with dementia more consistently than CRP does, and a CBC is drawn at nearly every visit for some other reason. Reverse causation is excluded by none of these cohorts, so the ratio is a flag for a closer look, not a result to act on alone.

High-sensitivity CRP still has a place, read on the scale it was built for: the AHA/CDC bands of under 1 mg/L, 1 to 3 and above 3 are cardiovascular risk tertiles, and a value above 10 calls for a repeat and a search for infection. Pooled data put high CRP ahead of conversion to dementia, HR 1.473, without predicting decline on cognitive tests.

Who should be screened for metaflammation?

The selection logic follows the mechanism rather than the diagnosis list. Central adiposity at any BMI qualifies, because waist circumference was associated with mortality within every BMI band from 20 to 50 kg/m², rising 17% in men and 13% in women per 5 cm at a given BMI. So does the patient with normal glucose but a family history, a rising waist or an elevated uric acid, which reads fructose load and is not a validated dementia marker in either direction. Cognitive complaints in a patient carrying that metabolic picture belong on the list too. There is a structural driver worth naming: added sugars supply roughly 15% of energy in the U.S. food supply, and up to 20% or more in some groups, so exposure is set by what is on the shelf, not by a patient’s individual choices. And one non-obvious point on evidence: the fifteen randomized trials that cleared linoleic acid of raising inflammatory markers enrolled healthy people. None enrolled the insulin-resistant patient most practices are trying to screen. The criteria page sets this out in operational form (selection criteria).

Which tests measure metaflammation?

Bioimpedance body composition separates fat from lean mass, the distinction BMI erases and the one that matters when visceral fat is the IL-6 source: in 25 extremely obese adults sampled during bypass surgery, portal IL-6 ran about 50% above arterial levels and correlated with CRP. Indirect calorimetry replaces a predicted resting energy expenditure with a measured one. Laboratory panels carry the chemistry: fasting insulin reported on its own, uric acid, hs-CRP, and oxidized LDL with the omega-6 to omega-3 ratio. In CARDIA, among 1,889 adults without metabolic syndrome at baseline, the top quintile of oxidized LDL carried OR 3.5 (1.9–6.6) for developing it within five years, and LDL cholesterol predicted nothing once oxidized LDL entered the model. Assays differ in antibodies and units, so values from different methods cannot be compared directly; pick one method and trend it.

Where the metabolic picture is abnormal and cognition is part of the concern, a cognitive assessment gives a documented baseline. That pairing also feeds fall prevention, since cognitive and balance workups share a patient population and a visit structure (cognitive assessment and fall prevention).

What a finding changes

Measura does not diagnose on its own, and results return to the ordering physician. What a finding changes is the specificity of the conversation. A patient told the A1C is fine hears permission; a patient shown visceral fat, a measured resting energy expenditure and an oxidized LDL in the top of its assay’s range hears a problem with coordinates. It changes follow-up: a defined interval to repeat the same measurements on the same method, so dietary change aimed at added sugar and processed food can be checked against numbers rather than weight alone. It also changes how a CRP above 10 is handled, as a repeat and an infection search, not as metabolic inflammation. None of it requires a medication decision to be useful.

Documentation and workflow

Record waist circumference as a vital sign next to BMI. Place the cognitive baseline in the annual wellness visit note where it can be compared year over year, and let standing orders define eligibility so screening does not depend on who had time that afternoon (standing orders for screening). Structured results that land in discrete fields support MIPS and HEDIS documentation far better than scanned reports (MIPS and quality reporting). The patient-facing version of this material is written separately (the patient article on sugar and inflammation), the full referenced evidence sits in the book companion (Chapter 7 companion), and the next physician article takes the same inflammatory argument into periodontal disease (periodontal disease and dementia).

Frequently asked questions

References

• Johnson, R. J., Gomez-Pinilla, F., Nagel, M., Nakagawa, T., Rodriguez-Iturbe, B., Sanchez-Lozada, L. G., Tolan, D. R., & Lanaspa, M. A. (2020). Cerebral fructose metabolism as a potential mechanism driving Alzheimer’s disease. Frontiers in Aging Neuroscience, 12, Article 560865. https://doi.org/10.3389/fnagi.2020.560865
• Abdelmalek, M. F., Lazo, M., Horska, A., Bonekamp, S., Lipkin, E. W., Balasubramanyam, A., Bantle, J. P., Johnson, R. J., Diehl, A. M., Clark, J. M., & the Fatty Liver Subgroup of the Look AHEAD Research Group (2012). Higher dietary fructose is associated with impaired hepatic adenosine triphosphate homeostasis in obese individuals with type 2 diabetes. Hepatology, 56(3), 952–960. https://doi.org/10.1002/hep.25741
• Holmes, C., Cunningham, C., Zotova, E., Woolford, J., Dean, C., Kerr, S., Culliford, D., & Perry, V. H. (2009). Systemic inflammation and disease progression in Alzheimer disease. Neurology, 73(10), 768–774. https://doi.org/10.1212/WNL.0b013e3181b6bb95
• Toubasi, A. A., & Al-Sayegh, T. N. (2026). Peripheral immune markers in dementia: A systematic review and meta-analysis of risk, severity, and pathological correlates. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 12(2), e70270. https://doi.org/10.1002/trc2.70270
• Zhong, X., Qiang, Y., Wang, L., Zhang, Y., Li, J., Feng, J., Cheng, W., Tan, L., & Yu, J. (2023). Peripheral immunity and risk of incident brain disorders: a prospective cohort study of 161,968 participants. Translational Psychiatry, 13(1), 382. https://doi.org/10.1038/s41398-023-02683-0
• Ross, R., Neeland, I. J., Yamashita, S., Shai, I., Seidell, J., Magni, P., Santos, R. D., Arsenault, B., Cuevas, A., Hu, F. B., Griffin, B. A., Zambon, A., Barter, P., Fruchart, J.-C., Eckel, R. H., Matsuzawa, Y., & Després, J.-P. (2020). Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity. Nature Reviews Endocrinology, 16(3), 177–189. https://doi.org/10.1038/s41574-019-0310-7
• Holvoet, P., Lee, D.-H., Steffes, M., Gross, M., & Jacobs, D. R. (2008). Association between circulating oxidized low-density lipoprotein and incidence of the metabolic syndrome. JAMA, 299(19), 2287–2293. https://doi.org/10.1001/jama.299.19.2287
• Ekblad, L. L., Tuisku, J., Koivumäki, M., Helin, S., Rinne, J. O., & Snellman, A. (2023). Insulin resistance and body mass index are associated with TSPO PET in cognitively unimpaired elderly. Journal of Cerebral Blood Flow and Metabolism, 43(9), 1588–1600. https://doi.org/10.1177/0271678X231172519
• Fontana, L., Eagon, J. C., Trujillo, M. E., Scherer, P. E., & Klein, S. (2007). Visceral fat adipokine secretion is associated with systemic inflammation in obese humans. Diabetes, 56(4), 1010–1013. https://doi.org/10.2337/db06-1656
• Pearson, T. A., Mensah, G. A., Alexander, R. W., Anderson, J. L., Cannon, R. O., Criqui, M., Fadl, Y. Y., Fortmann, S. P., Hong, Y., Myers, G. L., Rifai, N., Smith, S. C., Taubert, K., Tracy, R. P., & Vinicor, F. (2003). Markers of inflammation and cardiovascular disease: Application to clinical and public health practice: A statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation, 107(3), 499–511. https://doi.org/10.1161/01.CIR.0000052939.59093.45

Related reading

• B Vitamins in Mild Cognitive Impairment: Measure Before It Is Late
• Periodontal Disease and Dementia: A Screening Workflow
• Laboratory Panels

B Vitamins in Mild Cognitive Impairment: Measure Before It Is Late

Test B12 status in mild cognitive impairment before reaching for B vitamins: in VITACOG, high-dose B vitamins slowed brain atrophy most in people whose homocysteine was high at entry. In anyone over 60, serum B12 goes on the order with methylmalonic acid or holotranscobalamin.

Nearly the same B-vitamin doses slowed brain atrophy in mild cognitive impairment and did nothing in established Alzheimer’s disease. The variable was not the capsule. It was who was depleted, and when.

The chapter video, Two Windows That Never Reopen, frames B12 across two irreversible windows, the first thousand days and the last. For primary care, geriatrics and neurology-adjacent practice, the clinically useful half is the second. On B vitamins, mild cognitive impairment and established Alzheimer’s disease give opposite trial answers with nearly the same capsules, and the difference is who was enrolled and when. That is a screening argument before it is a treatment argument.

Do B vitamins help mild cognitive impairment or Alzheimer’s?

VITACOG randomized 271 people over 70 with mild cognitive impairment to two years of high-dose B vitamins or placebo; 168 completed paired MRI. Whole-brain atrophy ran 0.76% a year on treatment versus 1.08% on placebo (P = 0.001), and above a baseline homocysteine of 13 µmol/L it was 53% lower. A later analysis reported a cognitive benefit in participants whose homocysteine was high at entry.

The Alzheimer’s disease trial ran the other direction. It randomized 409 people with mild to moderate disease, MMSE 14–26, to folate 5 mg, B6 25 mg and B12 1 mg or placebo for 18 months. Homocysteine fell 2.42 versus 0.86 µmol/L. The ADAS-cog worsened 0.401 points a month on vitamins and 0.372 on placebo (P = .52), and depression was reported in 28% on vitamins against 18%.

Two readings fit, and the trial cannot separate them. Too late: the tissue was already lost. Wrong patients: everyone entered with normal folate, B12 and homocysteine, the subgroup VITACOG suggests does not respond. Both readings point to the same clinical move. A struggling neuron can be protected, a lost one cannot be rebuilt, and a patient who is not depleted cannot be repleted. Status has to be measured while the window is open, and treatment follows the measurement rather than the diagnosis.

Why do older adults become low in B12?

The common teaching that aging stomachs stop making acid does not hold up. Among 248 independently living older adults, basal gastric contents were acidic in 84%, and the authors noted that nearly 90% could acidify. The deficit concentrates in a subgroup: 31.5% of 359 adults aged 60 to 99 had atrophic gastritis by pepsinogen ratio, with low serum B12 rising stepwise with severity. Food-cobalamin malabsorption accounts for more than 60% of deficiency in older adults and pernicious anemia for 15–20%. After 60, roughly 6% are deficient by plasma B12 and closer to 20% are marginal.

Serum values understate the problem. In 548 Framingham survivors, methylmalonic acid was markedly raised in 11.3%, and the authors estimated metabolic deficiency at 12% or more, many with normal serum concentrations. The practice position is not to order serum B12 alone in anyone over 60; methylmalonic acid or holotranscobalamin goes on the same order.

Which medications lower B12 in older patients?

Acid suppression has a modest but real signal. In Kaiser Permanente data, two or more years of proton pump inhibitor supply carried OR 1.65, H2 blockers alone OR 1.25, and more than 1.5 pills a day OR 1.95, a dose gradient. Pooled data are less certain: one called its pooled OR too low to imply a clear association, and a 2025 meta-analysis of six studies found no difference in serum B12. The average effect is small, but an individual patient with atrophic gastritis is not an average.

The metformin question is settled by randomization. The Diabetes Prevention Program assigned 1,073 people to metformin and 1,082 to placebo. At five years, B12 at or below 203 pg/mL occurred in 4.3% versus 2.3%, low-plus-borderline in 19.1% versus 9.5%, and each year of use carried OR 1.13. Pooled meta-analytic odds came to 2.45 across 29 studies and 2.95 across 17 later studies in type 2 diabetes.

Intake, protein and the muscle compartment

Supply falls on the intake side too. Appetite declines, meat is often dropped first for dental reasons, the effort of cooking for one, or longstanding advice to limit red meat, and the anorexia of aging resists late correction once weight loss is established. Social isolation is a nutritional exposure in this population, not a footnote to it.

Demand moves the other way. PROT-AGE recommends at least 1.0–1.2 g/kg/day of protein for healthy adults over 65 and 1.2–1.5 g/kg/day in acute or chronic disease, excepting severe kidney disease with eGFR below 30, because older muscle shows declining anabolic response. Sarcopenia is defined as muscle failure that accrues across a lifetime. Chronic low-grade inflammation rises with age, and the same machinery driven by overnutrition is metaflammation, which is why the overfed, insulin-resistant adult runs this program early. Bioimpedance body composition quantifies the lean and fat compartments that weight and BMI blur together.

Who to test and what to pair it with

Measura [Cardiometabolic and Autonomic Health Analysis] is a measurement layer that reports to the ordering physician and leaves management with that physician. For this population the useful set is compact: laboratory panels specified to include methylmalonic acid or holotranscobalamin, homocysteine and folate; a cognitive assessment to document a baseline while the patient is still in the “normal for age” zone; and, because sarcopenia and cognitive change travel with falls, vestibular and balance testing as part of fall-risk work. The pairing logic is set out in cognitive assessment and fall prevention.

One gap is worth naming plainly. VITACOG had four participants with diabetes, so the insulin-resistant patient is effectively missing from the trial that worked. An absence from a trial is a blank, not a finding, and the blank is filled with a measurement rather than an assumption. The first window, preconception and pregnancy status, is assessed through obstetric and primary care; it is not part of Measura’s test library.

Documentation and workflow

Trigger criteria that follow from this evidence: age over 60, mild cognitive impairment or subjective cognitive complaint, “age-appropriate atrophy” on imaging, metformin at any duration, and two or more years of acid suppression. Encode them once so that screening does not depend on who is seeing the patient that day. The cognitive baseline, medication review and functional B12 result fit annual wellness visit integration, and the pattern behind a written baseline is discussed in what a cognitive baseline is for. The companion piece on functional B12 screening in metformin users covers the serum-marker evidence in depth, and every lifespan study, pregnancy data included, is collected in the Starved Brain evidence briefing for Chapter 6.

Frequently asked questions

References

• Smith, A. D., Smith, S. M., de Jager, C. A., Whitbread, P., Johnston, C., Agacinski, G., Oulhaj, A., Bradley, K. M., Jacoby, R., & Refsum, H. (2010). Homocysteine-lowering by B vitamins slows the rate of accelerated brain atrophy in mild cognitive impairment: A randomized controlled trial. PLoS ONE, 5(9), Article e12244. https://doi.org/10.1371/journal.pone.0012244
• Aisen, P. S., Schneider, L. S., Sano, M., Diaz-Arrastia, R., van Dyck, C. H., Weiner, M. F., Bottiglieri, T., Jin, S., Stokes, K. T., Thomas, R. G., Thal, L. J., & Alzheimer Disease Cooperative Study. (2008). High-dose B vitamin supplementation and cognitive decline in Alzheimer disease: A randomized controlled trial. JAMA, 300(15), 1774–1783. https://doi.org/10.1001/jama.300.15.1774
• Hurwitz, A., Brady, D. A., Schaal, S. E., Samloff, I. M., Dedon, J., & Ruhl, C. E. (1997). Gastric acidity in older adults. JAMA, 278(8), 659–662. https://doi.org/10.1001/jama.1997.03550080069041
• Krasinski, S. D., Russell, R. M., Samloff, I. M., Jacob, R. A., Dallal, G. E., McGandy, R. B., & Hartz, S. C. (1986). Fundic atrophic gastritis in an elderly population: Effect on hemoglobin and several serum nutritional indicators. Journal of the American Geriatrics Society, 34(11), 800–806. https://doi.org/10.1111/j.1532-5415.1986.tb03985.x
• Andrès, E., Loukili, N. H., Noel, E., Kaltenbach, G., Abdelgheni, M. B., Perrin, A. E., Noblet-Dick, M., Maloisel, F., Schlienger, J.-L., & Blicklé, J.-F. (2004). Vitamin B12 (cobalamin) deficiency in elderly patients. CMAJ, 171(3), 251–259. https://doi.org/10.1503/cmaj.1031155
• Lindenbaum, J., Rosenberg, I. H., Wilson, P. W., Stabler, S. P., & Allen, R. H. (1994). Prevalence of cobalamin deficiency in the Framingham elderly population. The American Journal of Clinical Nutrition, 60(1), 2–11. https://doi.org/10.1093/ajcn/60.1.2
• Lam, J. R., Schneider, J. L., Zhao, W., & Corley, D. A. (2013). Proton pump inhibitor and histamine 2 receptor antagonist use and vitamin B12 deficiency. JAMA, 310(22), 2435–2442. https://doi.org/10.1001/jama.2013.280490
• Aroda, V. R., Edelstein, S. L., Goldberg, R. B., Knowler, W. C., Marcovina, S. M., Orchard, T. J., Bray, G. A., Schade, D. S., Temprosa, M. G., White, N. H., Crandall, J. P., & Diabetes Prevention Program Research Group. (2016). Long-term metformin use and vitamin B12 deficiency in the Diabetes Prevention Program Outcomes Study. The Journal of Clinical Endocrinology & Metabolism, 101(4), 1754–1761. https://doi.org/10.1210/jc.2015-3754
• Bauer, J., Biolo, G., Cederholm, T., Cesari, M., Cruz-Jentoft, A. J., Morley, J. E., Phillips, S., Sieber, C., Stehle, P., Teta, D., Visvanathan, R., Volpi, E., & Boirie, Y. (2013). Evidence-based recommendations for optimal dietary protein intake in older people: A position paper from the PROT-AGE Study Group. Journal of the American Medical Directors Association, 14(8), 542–559. https://doi.org/10.1016/j.jamda.2013.05.021
• Franceschi, C., Garagnani, P., Parini, P., Giuliani, C., & Santoro, A. (2018). Inflammaging: A new immune-metabolic viewpoint for age-related diseases. Nature Reviews Endocrinology, 14(10), 576–590. https://doi.org/10.1038/s41574-018-0059-4

Related reading

• Metformin B12 Deficiency: Screening Beyond the Serum Level
• Metaflammation Screening: What the Standard Panel Misses
• Laboratory Panels

Metformin B12 Deficiency: Screening Beyond the Serum Level

Metformin roughly doubles the risk of B12 deficiency, and serum B12 alone routinely misses it. Screening metformin users with a functional marker such as methylmalonic acid or homocysteine, or with holotranscobalamin, closes that gap.

The patient most likely to be losing B12 is the metformin user, and that patient was nearly absent from the trial showing B vitamins slow brain atrophy.

The chapter video, Your Lab Says Normal. Your Brain Is Shrinking., is aimed at patients, but its sharpest implication is for the clinician holding the requisition. Metformin B12 deficiency is common, dose- and duration-dependent, and routinely missed when serum B12 is the only marker ordered. The insulin-resistant patient on metformin is also nearly absent from the one randomized trial showing that B vitamins slow brain atrophy. That combination is a screening gap, and it closes with better ordering, not new technology.

Is a normal serum B12 enough to rule out deficiency?

In Oxford’s OPTIMA cohort, 107 cognitively normal adults aged 61–87 were scanned annually for five years. None had plasma B12 below 150 pmol/L. The bottom tertile, below 308 pmol/L, carried an adjusted OR of 6.17 (95% CI 1.25–30.47) for membership in the fastest-atrophying third; low holotranscobalamin, below 54 pmol/L, gave OR 5.99. Methylmalonic acid and homocysteine trended higher in fast losers but did not survive adjustment in a sample that small. In the Stockholm cohort of 501 adults aged 60 and over, each SD of higher B12 and holotranscobalamin predicted slower whole-brain loss and each SD of homocysteine predicted faster loss.

The nulls deserve equal space. An Austrian cohort found no association between any B12 marker and atrophy, and the Dutch B-PROOF substudy found none with volume, though it scanned once and so measured volume rather than rate. The practice position is that the low-normal band matters clinically. That rests on the rate cohorts, not on any settled consensus, and it is stated here as a position.

The size of that band in the general population is not trivial. Among 12,335 U.S. adults, 2.2% had serum B12 below 148 pmol/L and a further 13% sat between 148 and 222 pmol/L. For cognitive complaints specifically, total B12 discriminated deficiency with an AUC of 0.54, while holotranscobalamin reached 0.69. The test most often accepted as the answer performed close to chance for the indication that brings older patients in.

How much does metformin lower B12, and do acid blockers add to it?

Across 31 studies, metformin roughly doubled the risk of biochemical B12 deficiency (RR 2.09, 95% CI 1.49–2.93), with a mean fall of 63.70 pmol/L that scaled with dose and duration. In a randomized trial of 390 insulin-treated patients followed 4.3 years, metformin lowered B12 19% against placebo, one new deficiency per 13.8 patients treated. Five-year DPP follow-up put low-or-borderline status at 19.1% with metformin against 9.5% with placebo, each year of use carried OR 1.13, and neuropathy was more common in users with low levels.

Acid suppression layers on top. In Kaiser Permanente data, two or more years of a proton pump inhibitor carried OR 1.65 for a deficiency diagnosis; a 2023 meta-analysis pooled a smaller 1.42 and judged the association unclear. Treat it as a contributor that stacks with metformin in the same older patient. None of this argues against metformin. It argues that a functional B12 result belongs on every metformin chart.

The upstream driver is the food environment. A diet built on refined energy is low in both B12 and preformed EPA and DHA while it drives the insulin resistance that earns the metformin prescription. The system produces the deficiency, then prescribes the drug that deepens it, and the visit length leaves no room to connect the two.

What VITACOG does and does not tell you

In VITACOG, 271 patients with mild cognitive impairment, all aged 70 and over, were randomized to folic acid 0.8 mg, B12 0.5 mg and B6 20 mg daily or placebo for two years. Whole-brain atrophy ran 0.76% a year on treatment against 1.08% on placebo, 29.6% slower. Above a baseline homocysteine of 13.0 µmol/L the slowing was 53.3%; at or below 9.5 µmol/L there was none. Voxel-based analysis localized the protection to Alzheimer-vulnerable gray matter.

The limits matter for your panel. Diabetes was rare: 10 placebo and 4 active participants in the imaging group, with faster atrophy that looked unresponsive on numbers too small to read. The trial was powered for atrophy, not cognition. The closest replication, in 279 Hong Kong outpatients, found no difference in its cognitive primary outcome and had no MRI endpoint. The investigators hold declared patents on this indication. And a retrospective subgroup analysis found the vitamins slowed atrophy 40.0% only in the top omega-3 tertile, with no significant effect in the bottom tertile.

Dr. Padda treats B vitamins and omega-3 as a pair on the strength of those subgroups, a mirror-image result in the OmegAD trial and a tracer study, against one contradicting trial and no trial that randomized both. That is practicing ahead of the evidence, and the practice says so in writing rather than presenting the pairing as proven.

What does an abnormal functional B12 result change?

A raised methylmalonic acid or low holotranscobalamin with a normal serum B12 reclassifies the patient from reassured to insufficient, which changes the next decision. Homocysteine sorts who is likely to respond: the VITACOG investigators propose at or below 10 µmol/L as probably safe and 11 or above as possibly justifying intervention, a proposal from the same patent-holding group. Folate status has to be read beside B12. Once B12 fell below 148 pmol/L in national survey data, rising serum folate went with higher homocysteine and methylmalonic acid, and low B12 with high folate carried OR 2.6 for cognitive impairment in 1,459 older Americans. Across 25 trials, folic acid lowered homocysteine 23% and added B12 a further 7%, while three trials using 15 mg a day saw more cardiovascular events. More vitamin is not more benefit.

Pairing the panel with cognition and nerve function

Measura [Cardiometabolic and Autonomic Health Analysis] supplies the measurement layer and returns findings to the ordering physician; interpretation and management stay in your hands. Three pieces fit this patient. Laboratory panels carry whatever markers you specify, so the order can name methylmalonic acid, holotranscobalamin, homocysteine and folate beside serum B12. A cognitive assessment sets a documented baseline before any decline is clinically obvious, which is the only way to show later that a trajectory changed. Sudomotor testing quantifies small-fiber sudomotor output at the hands and feet, a distal autonomic readout that matters here because neuropathy tracked with low B12 among metformin users. It does not measure B12; it shows the nerve terrain in the same patient. The pairing with gait and falls risk is covered under cognitive assessment and fall prevention.

Making it reproducible in the workflow

Screening that depends on memory does not happen. A written protocol does. A reasonable trigger list from this evidence: any patient on metformin, two or more years of acid suppression, age over 60 with a cognitive complaint, and anyone whose serum B12 sits in the low-normal band. Build those into standing orders for screening so staff can queue functional markers without a separate decision each time; the rationale for that approach is laid out in making screening reproducible. The cognitive baseline and medication review both belong in annual wellness visit documentation. The companion post on B vitamins and the timing of mild cognitive impairment carries the argument into later life, and every cited study, with its limits, is collected in the Starved Brain evidence briefing for Chapter 5.

Frequently asked questions

References

• Vogiatzoglou, A., Refsum, H., Johnston, C., Smith, S. M., Bradley, K. M., de Jager, C., Budge, M. M., & Smith, A. D. (2008). Vitamin B12 status and rate of brain volume loss in community-dwelling elderly. Neurology, 71(11), 826–832. https://doi.org/10.1212/01.wnl.0000325581.26991.f2
• Mineva, E. M., Sternberg, M. R., Bailey, R. L., Storandt, R. J., & Pfeiffer, C. M. (2021). Fewer US adults had low or transitional vitamin B12 status based on the novel combined indicator of vitamin B12 status compared with individual, conventional markers, NHANES 1999-2004. The American Journal of Clinical Nutrition, 114(3), 1070-1079. https://doi.org/10.1093/ajcn/nqab122
• Yang, W., Cai, X., Wu, H., & Ji, L. (2019b). Associations between metformin use and vitamin B12 levels, anemia, and neuropathy in patients with diabetes: A meta-analysis. Journal of Diabetes, 11(9), 729–743. https://doi.org/10.1111/1753-0407.12900
• de Jager, J., Kooy, A., Lehert, P., Wulffelé, M. G., van der Kolk, J., Bets, D., Verburg, J., Donker, A. J. M., & Stehouwer, C. D. A. (2010). Long term treatment with metformin in patients with type 2 diabetes and risk of vitamin B-12 deficiency: Randomised placebo controlled trial. BMJ, 340, c2181. https://doi.org/10.1136/bmj.c2181
• Aroda, V. R., Edelstein, S. L., Goldberg, R. B., Knowler, W. C., Marcovina, S. M., Orchard, T. J., Bray, G. A., Schade, D. S., Temprosa, M. G., White, N. H., & Crandall, J. P., for the Diabetes Prevention Program Research Group (2016). Long-term metformin use and vitamin B12 deficiency in the Diabetes Prevention Program Outcomes Study. The Journal of Clinical Endocrinology & Metabolism, 101(4), 1754–1761. https://doi.org/10.1210/jc.2015-3754
• Smith, A. D., Smith, S. M., de Jager, C. A., Whitbread, P., Johnston, C., Agacinski, G., Oulhaj, A., Bradley, K. M., Jacoby, R., & Refsum, H. (2010). Homocysteine-lowering by B vitamins slows the rate of accelerated brain atrophy in mild cognitive impairment: A randomized controlled trial. PLoS ONE, 5(9), e12244. https://doi.org/10.1371/journal.pone.0012244
• Jernerén, F., Elshorbagy, A. K., Oulhaj, A., Smith, S. M., Refsum, H., & Smith, A. D. (2015). Brain atrophy in cognitively impaired elderly: The importance of long-chain ω-3 fatty acids and B vitamin status in a randomized controlled trial. The American Journal of Clinical Nutrition, 102(1), 215–221. https://doi.org/10.3945/ajcn.114.103283
• Murphy, M. J., Brandie, F., Ebare, M., Harrison, M., Dow, E., Bartlett, W. A., & Craig, D. (2021). Personalising laboratory medicine in the ‘real world’: Assessing clinical utility, by clinical indication, of serum total B12 and Active-B12 (holotranscobalamin) in the diagnosis of vitamin B12 deficiency. Annals of Clinical Biochemistry, 58(5), 445–451. https://doi.org/10.1177/00045632211003605
• Morris, M. S., Jacques, P. F., Rosenberg, I. H., & Selhub, J. (2007). Folate and vitamin B-12 status in relation to anemia, macrocytosis, and cognitive impairment in older Americans in the age of folic acid fortification. The American Journal of Clinical Nutrition, 85(1), 193–200. https://doi.org/10.1093/ajcn/85.1.193
• Lam, J. R., Schneider, J. L., Zhao, W., & Corley, D. A. (2013). Proton pump inhibitor and histamine 2 receptor antagonist use and vitamin B12 deficiency. JAMA, 310(22), 2435–2442. https://doi.org/10.1001/jama.2013.280490

Related reading

• Statins and Dementia: Measuring Cognition in Patients on Statins
• B Vitamins in Mild Cognitive Impairment: Measure Before It Is Late
• Laboratory Panels

Statins and Dementia: Measuring Cognition in Patients on Statins

In patients on statins, trials find no cognitive harm on average, but a small, reversible effect in a susceptible few can only be tested in the individual. A documented cognitive baseline makes that question answerable by measurement rather than recall.

Population data and the individual patient answer different questions. Only one of them can be settled in the exam room, and only with a baseline recorded first.

On statins and dementia, the population answer is settled enough to state plainly: randomized trials find no cognitive harm on average, and observational cohorts find less dementia among users. What remains is smaller and harder. Chapter 4 of The Starved Brain by Dr. Gurpreet Singh Padda, MD, MBA, MHP, and its video, frame it as an individual question: in a given patient with new cognitive complaints on a statin, is the drug involved? Measura [Cardiometabolic and Autonomic Health Analysis] does not answer that for the clinician. It makes the question answerable by measurement rather than recall.

How do statins affect cholesterol in the brain?

The central nervous system is about 2.1% of body weight and holds about 23% of the body’s sterol pool, essentially all of it synthesized locally behind the blood–brain barrier. Lipoprotein cholesterol does not supply it, which is why a serum lipid panel is nearly silent on brain cholesterol status. Myelin is lipid-dense, and when mice lacked cholesterol synthesis in oligodendrocytes, myelination slowed and thinned without stopping. Glia supply the cholesterol that synapse formation depends on.

HMG-CoA reductase is not a hepatic monopoly. Lipophilic agents cross the barrier more readily, and the brain’s exit marker, 24S-hydroxycholesterol, fell 45% at six weeks and 53% at 24 weeks on simvastatin 80 mg in 18 hypercholesterolemic patients. In Alzheimer’s patients the marker also fell on regimens that included pravastatin, though part of that fall tracks LDL clearance rather than brain synthesis. Hydrophilic does not mean invisible to the brain pool.

Do statins cause dementia? What the outcome data show, and what they could not see

Solubility has not predicted harm. ASPREE, with 18,846 participants aged 65 and over, found no association between statin use and dementia, MCI or cognitive change, and no difference by solubility; 36 observational studies agreed on the solubility point. On the randomized side, 25 placebo-controlled trials in 46,836 people showed no cognitive effect, and the 2026 individual-participant analysis of 19 blinded trials and 123,940 people concluded the data do not support a causal link to cognitive impairment.

The design limits are what matter clinically. Cognition was not a primary or secondary outcome in the large cardiovascular trials. Adverse-event capture was spontaneous reporting rather than testing. ASPREE excluded dementia, the population the withdrawal signal came from, and the cohorts carry reverse causation because patients developing dementia stop their statins. Neither design could detect a small, reversible effect confined to a susceptible minority, and that is what the 2012 class labeling describes: rare, generally nonserious, reversible, with onset from a day to years and resolution at a median of three weeks.

There is an admission worth making here. The mechanism is strong enough that one would expect a population signal, and the populations have declined to produce one. Dr. Padda says so directly rather than bending the data, and the honest consequence is a narrower claim: one that can be tested in a single patient.

Padala, read at its actual size

The withdrawal and rechallenge pilot enrolled 18 older veterans with Alzheimer’s dementia. MMSE rose 1.9 points during six weeks off the statin (P = 0.014) and fell 1.9 points on rechallenge (P = 0.007); the CERAD battery did not change (P = 0.31). It was open-label and single-arm, with no control, and the change was smaller than its own standard deviation. Cochrane’s pooling of four double-blind trials in 1,154 Alzheimer’s patients found MMSE 0.32 points lower on statin, not significant. The one blinded withdrawal phase ever run, inside LEADe, was never reported.

What Padala contributes is design, not proof: onset after exposure, resolution off it, recurrence on it, measured with the same instrument each time. That is ordinary adverse drug reaction logic, and it works only if the first measurement exists before the question is asked.

How should cognition be measured in patients on statins?

All of this points to one workflow change: document cognition before it becomes a complaint.

1. Baseline at initiation or the next wellness visit. A structured cognitive assessment for older patients on or starting a lipophilic statin, and for any patient with existing cognitive impairment, recorded as a comparable score rather than a narrative. The annual wellness visit is the natural home for it.
2. Repeat with the same instrument when a complaint appears. Comparison with the patient’s own baseline separates a change from a lifelong pattern, and avoids reading an MMSE against a battery that behaves differently.
3. If the treating physician elects a supervised off-and-on trial, the same assessment at each phase gives it a readable outcome. The label’s median three-week resolution and Padala’s six-week phases frame the timing. Whether to interrupt therapy, and in whom, stays with the treating physician and the patient; after a myocardial infarction the calculus is different.
4. Measure the metabolic side as well. In the 2024 CTT analysis of 23 blinded trials, high-intensity therapy carried new-onset diabetes at 4.8% a year against 3.5%, and about 62% of new cases arose in the top quarter of baseline glycemia. Laboratory panels characterizing insulin resistance identify that quarter explicitly.

For older patients, the same visit can pair the cognitive baseline with vestibular and balance testing, so cognitive and fall-risk findings enter one plan, as outlined in cognitive assessment and fall prevention. Arterial stiffness and endothelial function keeps the vascular indication, the reason the statin was started, documented on its own terms.

The barrier is structural: a short visit, a medication list reconciled from memory, and a cognitive complaint that defaults to age. A documented baseline makes the complaint auditable. Written into a standing order, the protocol does not depend on which clinician is in the room, and cognitive plus cardiometabolic findings in one encounter serve MIPS and quality reporting.

The wider point for practice

The brain builds and maintains itself from lipids for decades, and for fifty years dietary guidance steered patients away from the foods densest in them. That is context, not a prescription. The instrument that matters in the exam room is the one that makes an individual effect visible. The grading of each claim, including the trial record against the hypothesis, is in the Chapter 4 book companion, and the metabolic precursor is covered in insulin resistance and dementia screening.

Frequently asked questions

References

• Dietschy, J. M., & Turley, S. D. (2004). Thematic review series: Brain lipids. Cholesterol metabolism in the central nervous system during early development and in the mature animal. Journal of Lipid Research, 45(8), 1375–1397. https://doi.org/10.1194/jlr.R400004-JLR200
• Saher, G., Brügger, B., Lappe-Siefke, C., Möbius, W., Tozawa, R., Wehr, M. C., Wieland, F., Ishibashi, S., & Nave, K.-A. (2005). High cholesterol level is essential for myelin membrane growth. Nature Neuroscience, 8(4), 468–475. https://doi.org/10.1038/nn1426
• Locatelli, S., Lütjohann, D., Schmidt, H. H. J., Otto, C., Beisiegel, U., & von Bergmann, K. (2002). Reduction of plasma 24S-hydroxycholesterol (cerebrosterol) levels using high-dosage simvastatin in patients with hypercholesterolemia: Evidence that simvastatin affects cholesterol metabolism in the human brain. Archives of Neurology, 59(2), 213–216. https://doi.org/10.1001/archneur.59.2.213
• Zhou, Z., Ryan, J., Ernst, M. E., Zoungas, S., Tonkin, A. M., Woods, R. L., McNeil, J. J., Reid, C. M., Curtis, A. J., Wolfe, R., Wrigglesworth, J., Shah, R. C., Storey, E., Murray, A., Orchard, S. G., Nelson, M. R., & ASPREE Investigator Group. (2021). Effect of statin therapy on cognitive decline and incident dementia in older adults. Journal of the American College of Cardiology, 77(25), 3145–3156. https://doi.org/10.1016/j.jacc.2021.04.075
• Olmastroni, E., Molari, G., De Beni, N., Colpani, O., Galimberti, F., Gazzotti, M., Zambon, A., Catapano, A. L., & Casula, M. (2022). Statin use and risk of dementia or Alzheimer’s disease: A systematic review and meta-analysis of observational studies. European Journal of Preventive Cardiology, 29(5), 804–814. https://doi.org/10.1093/eurjpc/zwab208
• Ott, B. R., Daiello, L. A., Dahabreh, I. J., Springate, B. A., Bixby, K., Murali, M., & Trikalinos, T. A. (2015). Do statins impair cognition? A systematic review and meta-analysis of randomized controlled trials. Journal of General Internal Medicine, 30(3), 348–358. https://doi.org/10.1007/s11606-014-3115-3
• Cholesterol Treatment Trialists’ Collaboration. (2026). Assessment of adverse effects attributed to statin therapy in product labels: A meta-analysis of double-blind randomised controlled trials. The Lancet, 407(10529), 689–703. https://doi.org/10.1016/S0140-6736(25)01578-8
• Padala, K. P., Padala, P. R., McNeilly, D. P., Geske, J. A., Sullivan, D. H., & Potter, J. F. (2012). The effect of HMG-CoA reductase inhibitors on cognition in patients with Alzheimer’s dementia: A prospective withdrawal and rechallenge pilot study. The American Journal of Geriatric Pharmacotherapy, 10(5), 296–302. https://doi.org/10.1016/j.amjopharm.2012.08.002
• McGuinness, B., Craig, D., Bullock, R., Malouf, R., & Passmore, P. (2014). Statins for the treatment of dementia. Cochrane Database of Systematic Reviews, 2014(7), Article CD007514. https://doi.org/10.1002/14651858.CD007514.pub3
• Cholesterol Treatment Trialists’ (CTT) Collaboration. (2024). Effects of statin therapy on diagnoses of new-onset diabetes and worsening glycaemia in large-scale randomised blinded statin trials: An individual participant data meta-analysis. The Lancet Diabetes & Endocrinology, 12(5), 306–319. https://doi.org/10.1016/S2213-8587(24)00040-8

Related reading

• Insulin Resistance and Dementia: Screening Past the Glucose
• Metformin B12 Deficiency: Screening Beyond the Serum Level
• Cognitive Assessment

Insulin Resistance and Dementia: Screening Past the Glucose

Screening for insulin resistance in patients at dementia risk has to go past fasting glucose and A1c. In Whitehall II, insulin sensitivity declined for about five years before a diabetes diagnosis, while fasting glucose accelerated only in the last three.

Glucose-based screening finds the metabolic failure after years of compensation. For the brain, those compensating years are the ones that matter.

The link between insulin resistance and dementia is usually taught as a diabetes statistic, and screening follows the teaching: order a fasting glucose or an A1c and act when it crosses a threshold. The evidence assembled for Chapter 3 of The Starved Brain by Dr. Gurpreet Singh Padda, MD, MBA, MHP, and its accompanying video, argues that this sequence catches the problem at the wrong end. For a practice using Measura [Cardiometabolic and Autonomic Health Analysis], the clinical question is narrower and more useful: which measurements describe the compensating years, and what does a finding change?

How much does insulin resistance raise dementia risk?

The pooled figures are familiar. Across 2,310,330 people and 102,174 dementia cases, type 2 diabetes carried a relative risk of 1.62 in women and 1.58 in men, with a larger estimate for vascular dementia. Whenever a pool is divided by subtype, the vascular number is the bigger one. Measured insulin resistance, pooled across ten prospective cohorts, gives a hazard ratio of 1.11 for all-cause dementia and 1.23 for Alzheimer’s disease: smaller than the diabetes figures, which suggests much of the risk is carried downstream by glycemia, vessels and years of exposure.

The null side deserves equal reading. In the Baltimore Longitudinal Study of Aging, 197 autopsied participants showed no correlation between glucose intolerance or insulin resistance and plaque or tangle scores. Mendelian randomization in 17,008 Alzheimer’s cases found no causal signal from genetically predicted insulin resistance. Type 3 diabetes remains a hypothesis with substantial support, not an established mechanism. Two caveats temper those nulls: peripheral markers in cohorts with little metabolic disease contain little exposure, and a genetic lifetime nudge is not a decade of dietary hyperinsulinemia.

Why is fasting glucose a late screen for insulin resistance?

Whitehall II gives the cleanest timeline. Among the civil servants who progressed to diabetes, insulin sensitivity declined steeply for about five years before diagnosis, beta-cell output climbed between years four and three as compensation, and fasting glucose accelerated only in the last three years. The chart records the failure of compensation, not its onset.

Most of us were trained to reassure the patient whose A1c sat just under the diabetes line. Dr. Padda describes doing exactly that for years before the physiology changed his practice. The error was not carelessness; it was screening with an instrument designed to detect the end state.

The brain data sit on the same clock. In 150 cognitively normal adults with a mean age of 60.7, higher HOMA-IR predicted lower whole-brain glucose uptake and, in the medial temporal lobe, poorer memory. In the Framingham Offspring cohort, with diabetes excluded, fasting insulin was associated with smaller total brain volume where A1c showed no association. In 683 older Manhattan adults, hyperinsulinemia carried a hazard ratio of 2.1 for Alzheimer’s disease, highest among those without diabetes. All observational, and all pointing at insulin rather than glucose as the earlier signal.

What does an insulin resistance finding change in management?

A glucose-only workup leaves a binary: diabetic or not. A broader measurement set produces a gradient, and the gradient changes three decisions.

1. Who gets a cognitive baseline. The insulin-resistant patient with normal cognition is precisely the phenotype in which brain glucose hypometabolism has been shown before symptoms. A documented cognitive assessment converts a future complaint into a comparison, and the annual wellness visit is the natural place to record it.
2. How the vascular route is worked up. The diabetes and dementia association is strongest for vascular dementia, and across 2,365 autopsied brains diabetes tracked infarcts and lacunes rather than plaques or Braak stage. Arterial stiffness and endothelial function belongs in the same encounter as the metabolic workup.
3. What the metabolic conversation is anchored to. Laboratory panels that go past a fasting glucose, read alongside bioimpedance body composition, show the patient the terrain rather than a pass mark.

The obstacle is rarely knowledge. It is a visit built around the numbers the quality dashboard already tracks, a food environment that supplies carbohydrate continuously, and a referral structure that routes one upstream failure to endocrinology, hepatology, gynecology and neurology under four separate names.

Workflow: selection, orders and documentation

Selection does not have to be elaborate. The evidence names its own triggers: prediabetes or a family history of diabetes, central adiposity or midlife obesity, fatty liver, polycystic ovary syndrome, and a family history of Alzheimer’s disease, since the cohorts that showed early hypometabolism were enriched for it. Normal glucose is not an exclusion; it is the population in which the compensating phase hides.

Written as a standing order, the protocol runs the same way regardless of which clinician sees the patient, with the criteria set out under selection criteria. Cognitive and cardiometabolic findings documented in one encounter also support MIPS and quality reporting without a parallel workflow.

What does an insulin resistance finding not prove?

Three limits belong in the chart note as much as in the literature. PET hypometabolism is a research measurement; Measura does not perform imaging, and no peripheral marker is a validated stand-in for regional brain glucose uptake. The cause-versus-consequence question is open, since amyloid oligomers can induce neuronal insulin resistance as well as follow it. And the cleanest direct test of the brain insulin hypothesis, intranasal insulin in the SNIFF trial of 289 participants, returned a null primary result. None of that weakens the case for measuring insulin resistance early. It defines what a finding means: a terrain risk to manage and a baseline to follow, not a diagnosis of neurodegeneration. The full grading, trial by trial, is in the Chapter 3 book companion, and the structural counterpart, cholesterol and cognition on statins, is in statins and dementia. Where fat and muscle sit, not just body weight, tracks neurodegenerative risk; see body fat distribution and dementia risk.

Frequently asked questions

References

• Chatterjee, S., Peters, S. A. E., Woodward, M., Mejia Arango, S., Batty, G. D., Beckett, N., Beiser, A., Borenstein, A. R., Crane, P. K., Haan, M., Hassing, L. B., Hayden, K. M., Kiyohara, Y., Larson, E. B., Li, C.-Y., Ninomiya, T., Ohara, T., Peters, R., Russ, T. C., … Huxley, R. R. (2016). Type 2 diabetes as a risk factor for dementia in women compared with men: A pooled analysis of 2.3 million people comprising more than 100,000 cases of dementia. Diabetes Care, 39(2), 300–307. https://doi.org/10.2337/dc15-1588
• Xu, X., Li, J., Pan, H., Zhao, B., & Wang, D. (2026). Insulin resistance and the risk of dementia: A systematic review and meta-analysis of prospective cohort studies. BMC Neurology, Article in press (DOI assigned); PMID 42387430. https://doi.org/10.1186/s12883-026-05079-x
• Thambisetty, M., Jeffrey Metter, E., Yang, A., Dolan, H., Marano, C., Zonderman, A. B., Troncoso, J. C., Zhou, Y., Wong, D. F., Ferrucci, L., Egan, J., Resnick, S. M., & O’Brien, R. J. (2013). Glucose intolerance, insulin resistance, and pathological features of Alzheimer disease in the Baltimore Longitudinal Study of Aging. JAMA Neurology, 70(9), 1167–1172. https://doi.org/10.1001/jamaneurol.2013.284
• Østergaard, S. D., Mukherjee, S., Sharp, S. J., Proitsi, P., Lotta, L. A., Day, F., Perry, J. R. B., Boehme, K. L., Walter, S., Kauwe, J. S., Gibbons, L. E., … Scott, R. A. (2015). Associations between potentially modifiable risk factors and Alzheimer disease: A Mendelian randomization study. PLoS Medicine, 12(6), e1001841. https://doi.org/10.1371/journal.pmed.1001841
• Tabák, A. G., Jokela, M., Akbaraly, T. N., Brunner, E. J., Kivimäki, M., & Witte, D. R. (2009). Trajectories of glycaemia, insulin sensitivity, and insulin secretion before diagnosis of type 2 diabetes: An analysis from the Whitehall II study. The Lancet, 373(9682), 2215–2221. https://doi.org/10.1016/S0140-6736(09)60619-X
• Willette, A. A., Bendlin, B. B., Starks, E. J., Birdsill, A. C., Johnson, S. C., Christian, B. T., Okonkwo, O. C., La Rue, A., Hermann, B. P., Koscik, R. L., Jonaitis, E. M., Sager, M. A., & Asthana, S. (2015). Association of insulin resistance with cerebral glucose uptake in late middle-aged adults at risk for Alzheimer disease. JAMA Neurology, 72(9), 1013–1020. https://doi.org/10.1001/jamaneurol.2015.0613
• Tan, Z. S., Beiser, A. S., Fox, C. S., Au, R., Himali, J. J., Debette, S., DeCarli, C., Vasan, R. S., Wolf, P. A., & Seshadri, S. (2011). Association of metabolic dysregulation with volumetric brain magnetic resonance imaging and cognitive markers of subclinical brain aging in middle-aged adults: The Framingham Offspring Study. Diabetes Care, 34(8), 1766–1770. https://doi.org/10.2337/dc11-0308
• Luchsinger, J. A., Tang, M.-X., Shea, S., & Mayeux, R. (2004). Hyperinsulinemia and risk of Alzheimer disease. Neurology, 63(7), 1187–1192. https://doi.org/10.1212/01.wnl.0000140292.04932.87
• Abner, E. L., Nelson, P. T., Kryscio, R. J., Schmitt, F. A., Fardo, D. W., Woltjer, R. L., Cairns, N. J., Yu, L., Dodge, H. H., Xiong, C., Masaki, K., Tyas, S. L., Bennett, D. A., Schneider, J. A., & Arvanitakis, Z. (2016). Diabetes is associated with cerebrovascular but not Alzheimer’s disease neuropathology. Alzheimer’s & Dementia, 12(8), 882–889. https://doi.org/10.1016/j.jalz.2015.12.006
• Craft, S., Raman, R., Chow, T. W., Rafii, M. S., Sun, C.-K., Rissman, R. A., Donohue, M. C., Brewer, J. B., Jenkins, C., Harless, K., Gessert, D., & Aisen, P. S. (2020). Safety, efficacy, and feasibility of intranasal insulin for the treatment of mild cognitive impairment and Alzheimer disease dementia: A randomized clinical trial. JAMA Neurology, 77(9), 1099–1109. https://doi.org/10.1001/jamaneurol.2020.1840

Related reading

• Fasting Insulin Screening: The Gate on the Brain’s Second Fuel
• Statins and Dementia: Measuring Cognition in Patients on Statins
• Cognitive Assessment