Abstract 9147: Undiagnosed Diabetes Mellitus, Pre-Diabetes, and Outcomes in Patients with Non-ST-Segment Elevation Acute Coronary Syndromes
Bibliographic record
Abstract
Background: Diabetes mellitus (DM) is associated with in-hospital and post-discharge morbidity and mortality in ACS patients. Little is known about the prevalence and outcomes of DM first diagnosed during hospitalization (undiagnosed DM) and pre-diabetes (preDM) among non-ST-segment elevation (NSTE) ACS patients. Methods: We used the EARLY ACS trial database to explore the prevalence and outcomes of previously undiagnosed DM and preDM among high-risk NSTE ACS patients. Known DM was a baseline characteristic on the case report form. Undiagnosed DM was defined as fasting glucose >=126 mg/dL or HbA1c >=6.5% in patients without a history of DM, and preDM as fasting glucose >=110 to <126 mg/dL. Associations between undiagnosed DM, preDM, and known DM and 30-day death or MI and 1-year death were assessed by logistic regression and Cox proportional hazards modeling, respectively, with adjustment for baseline characteristics previously associated with these events in EARLY ACS models. Results: Of 9406 patients, 1069 (11.4%) had undiagnosed DM, 947 (10.1%) had preDM, and 2860 (30.4%) had known DM. In general, patients with undiagnosed DM and preDM were similar in age and had similar prevalence of comorbidities as patients without DM; each of these groups was younger, had higher eCrCl, and fewer comorbidities than patients with known DM. Compared with patients without DM, the risk of 30-day death or MI was higher among patients with undiagnosed DM, but neither preDM nor known DM patients had elevated adjusted 30-day risk (Table). After adjustment, 1-year death was similar for patients with preDM and undiagnosed DM to those without DM. However, known DM patients had 32% higher 1-year mortality. Conclusions: Undiagnosed DM and preDM are common in high-risk NSTE ACS patients. Although patients with previously undiagnosed DM and preDM had 1-year survival similar to non-diabetic patients, the presence of previously undiagnosed DM identified patients at elevated 30-day risk.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".