MON-636 The Relationship Between Glucose Control & Cognitive Function in People with Diabetes After a Lacunar Stroke
Bibliographic record
Abstract
Abstract Background & Objective Both lacunar strokes and diabetes are risk factors for dementia and cognitive dysfunction. Thus, elucidating modifiable risk factors for cognitive dysfunction in people with type 2 diabetes who experienced a lacunar infarct has large public health implications. One such factor may be glycemic status, as measured by glycosylated hemoglobin (A1C). Thus, the aim of this study was to assess the relationship between A1C and cognitive function in people with diabetes after a lacunar stroke. Research Design & Methods The effect of baseline and follow-up A1C on the baseline and the change in Cognitive Assessment Screening Instrument (CASI) score over time among participants with a median of 2 cognitive assessments (range 1-5) was examined in of 942 individuals with diabetes and a lacunar stroke who participated in the Secondary Prevention of Small Subcortical Strokes (SPS3) trial (ClinicalTrials.gov number, NCT00059306). Results Every 1 % higher baseline A1C was associated with a 0.06 lower standardized CASI z-score (95% CI -0.101, -0.018). Higher baseline A1C values were associated with lower CASI z-score over time (p for interaction=0.037). A 1% increase in A1C over time, corresponded with a CASI score decrease of 0.021 (95% CI -0.0043, -0.038) during follow-up. All these remained statistically significant after adjustment for age, sex, education, race, depression, hypertension, hyperlipidemia, BMI, CVD, OSA, diabetic retinopathy, nephropathy insulin use and White Matter Abnormalities. Conclusion This analysis of 942 individuals with diabetes after a lacunar stroke demonstrates a relationship between A1C and change in cognitive scores over time. Intervention studies are needed in order to delineate if better glucose control could slow the rate of cognitive decline in this high risk population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".