Relationship between glycemic control and cognitive impairment: A systematic review and meta-analysis
Bibliographic record
Abstract
Background Diabetes mellitus, or hyperglycemia, is an independent risk factor for cognitive impairment. Here we systematically analyzed whether glycemic control could improve cognitive impairment in patients with diabetes mellitus (DM), hyperglycemia, or insulin resistance. Methods Three databases (PubMed, EMBASE, and Cochrane Library) and ClinicalTrials.gov were searched for randomized controlled trials analyzing the relationship between glycemic control and cognitive function assessments, published from database inception to June 2022. Patients in experimental groups were treated with antidiabetic drugs, while control groups were treated with a placebo or alternative antidiabetic drugs. Data analysis was conducted using RevMan 5.3 and StataSE-64, and standardized mean difference (SMD) and 95% confidence intervals (CIs) were calculated. Results Thirteen studies comprising 19,314 participants were included. Analysis revealed that glycemic control significantly attenuated the degree of decline in cognitive function assessment scores (SMD = 0.15; 95% CI 0.05, 0.26; p < 0.00001), and funnel plots confirmed no publication bias. Seven studies used Mini-Mental State Examination as the primary cognitive function assessment, showing that glycemic control significantly delayed the degree of decline in cognitive function assessment scores (SMD = 0.18; 95% CI 0.03, 0.34; p = 0.02). Similar results were seen in two studies using the Montreal Cognitive Assessment scale, but without significant difference (SMD = 0.05; 95% CI-0.10, 0.21; p = 0.51). One study using Auditory Word Learning Test (AVLT) showed that glycemic control significantly delayed the decline in cognitive function assessment scores (SMD = 0.52; 95% CI 0.11,0.93; p = 0.01), and another used Wechsler Memory Scale Revised, showing similar results (SMD = 1.45; 95% CI 0.86, 2.04; p < 0.00001). Likewise, a study that used Modified Mini-Mental State scale showed that glycemic control significantly delayed the decline in cognitive function assessment scores (SMD = -0.10; 95% CI-0.16, −0.03; p = 0.005). Lastly, one study used AVLT subtests to show that glycemic control delayed the decline in cognitive function assessment scores, although not statistically significant (SMD = 0.09; 95% CI-0.53, 0.71; p = 0.78). Conclusion Glycemic control through antidiabetic treatment correlates with the improvement of cognitive impairment in patients with DM, hyperglycemia or insulin resistance. However, further studies are needed to validate the results of this study. Systematic Review Registration PROSPERO , identifier CRD42022342260.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".