Outcomes and clinical implications of intranasal insulin on cognition in humans: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Aberrant brain insulin signaling has been posited to lie at the crossroads of several metabolic and cognitive disorders. Intranasal insulin (INI) is a non-invasive approach that allows investigation and modulation of insulin signaling in the brain while limiting peripheral side effects. OBJECTIVES: The objective of this systematic review and meta-analysis is to evaluate the effects of INI on cognition in diverse patient populations and healthy individuals. METHODS: MEDLINE, EMBASE, PsycINFO, and Cochrane CENTRAL were systematically searched from 2000 to July 2021. Eligible studies were randomized controlled trials that studied the effects of INI on cognition. Two independent reviewers determined study eligibility and extracted relevant descriptive and outcome data. RESULTS: Twenty-nine studies (pooled N = 1,726) in healthy individuals as well as those with Alzheimer's disease (AD)/mild cognitive impairment (MCI), mental health disorders, metabolic disorders, among others, were included in the quantitative meta-analysis. Patients with AD/MCI treated with INI were more likely to show an improvement in global cognition (SMD = 0.22, 95% CI: 0.05-0.38 p = <0.00001, N = 12 studies). Among studies with healthy individuals and other patient populations, no significant effects of INI were found for global cognition. CONCLUSIONS: This review demonstrates that INI may be associated with pro-cognitive benefits for global cognition, specifically for individuals with AD/MCI. Further studies are required to better understand the neurobiological mechanisms and differences in etiology to dissect the intrinsic and extrinsic factors contributing to the treatment response of INI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".