The Impact of Frequent and Unrecognized Hypoglycemia on Mortality in the ACCORD Study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to examine the relationship between frequent and unrecognized hypoglycemia and mortality in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study cohort. RESEARCH DESIGN AND METHODS: A total of 10,096 ACCORD study participants with follow-up for both hypoglycemia and mortality were included. Hazard ratios (95% CIs) relating the risk of death to the updated annualized number of hypoglycemic episodes and the updated annualized number of intervals with unrecognized hypoglycemia were obtained using Cox proportional hazards regression models, allowing for these hypoglycemia variables as time-dependent covariates and controlling for the baseline covariates. RESULTS: Participants in the intensive group reported a mean of 1.06 hypoglycemic episodes (self-monitored blood glucose <70 mg/dL or <3.9 mmol/L) in the 7 days preceding their regular 4-month visit, whereas participants in the standard group reported an average of 0.29 episodes. Unrecognized hypoglycemia was reported, on average, at 5.8% of the intensive group 4-month visits and 2.6% of the standard group visits. Hazard ratios for mortality in models including frequency of hypoglycemic episodes were 0.93 (95% CI 0.9-0.97; P < 0.001) for participants in the intensive group and 0.98 (0.91-1.06; P = 0.615) for participants in the standard group. The hazard ratios for mortality in models, including unrecognized hypoglycemia, were not statistically significant for either group. CONCLUSIONS: Recognized and unrecognized hypoglycemia was more common in the intensive group than in the standard group. In the intensive group of the ACCORD study, a small but statistically significant inverse relationship of uncertain clinical importance was identified between the number of hypoglycemic episodes and the risk of death among participants.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".