Hypoglycemia and Incident Cognitive Dysfunction: A Post Hoc Analysis From the ORIGIN Trial
Bibliographic record
Abstract
OBJECTIVE: Epidemiological studies have reported a relationship between severe hypoglycemia, cognitive dysfunction, and dementia in middle-aged and older people with type 2 diabetes. However, whether severe or nonsevere hypoglycemia precedes cognitive dysfunction is unclear. Thus, the aim of this study was to analyze the relationship between hypoglycemia and incident cognitive dysfunction in a group of carefully followed patients using prospectively collected data in the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial. RESEARCH DESIGN AND METHODS: = 11,495). Severe and nonsevere hypoglycemic events were collected prospectively during a median follow-up time of 6.2 years. Incident cognitive dysfunction was defined as either reported dementia or an MMSE score of <24. The hazard of at least one episode of severe or nonsevere hypoglycemia for incident cognitive dysfunction (i.e., the dependent variable) from the time of randomization was estimated using a Cox proportional hazards model after adjusting for baseline cardiovascular disease, diabetes status, treatment allocation, and a propensity score for either form of hypoglycemia. RESULTS: This analysis did not demonstrate an association between severe hypoglycemia and incident cognitive impairment either before (hazard ratio [HR] 1.16; 95% CI 0.89, 1.52) or after (HR 1.00; 95% CI 0.76, 1.31) adjusting for the severe hypoglycemia propensities. Conversely, nonsevere hypoglycemia was inversely related to incident cognitive impairment both before (HR 0.59; 95% CI 0.52, 0.68) and after (HR 0.58; 95% CI 0.51, 0.67) adjustment. CONCLUSIONS: Hypoglycemia did not increase the risk of incident cognitive dysfunction in 11,495 middle-aged individuals with dysglycemia.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".