Diabetes association with self‐reported health, resource utilization, and prognosis post‐myocardial infarction
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus (DM) is associated with increased cardiovascular (CV) risk. We compared health-related quality of life (HRQoL), healthcare resource utilization (HRU), and clinical outcomes of stable post-myocardial infarction (MI) patients with and without DM. HYPOTHESIS: In post-MI patients, DM is associated with worse HRQoL, increased HRU, and worse clinical outcomes. METHODS: The prospective, observational long-term risk, clinical management, and healthcare Resource utilization of stable coronary artery disease study obtained data from 8968 patients aged ≥50 years 1 to 3 years post-MI (369 centers; 25 countries). Patients with ≥1 of the following risk factors were included: age ≥65 years, history of a second MI >1 year before enrollment, multivessel coronary artery disease, creatinine clearance ≥15 and <60 mL/min, and DM treated with medication. Self-reported health status was assessed at baseline, 1 and 2 years and converted to EQ-5D scores. The main outcome measures were baseline HRQoL and HRU during follow-up. RESULTS: DM at enrollment was 33% (2959 patients, 869 insulin treated). Mean baseline EQ-5D score (0.86 vs 0.82; P < .0001) was higher; mean number of hospitalizations (0.38 vs 0.50, P < .0001) and mean length of stay (LoS; 9.3 vs 11.5; P = .001) were lower in patients without vs with DM. All-cause death and the composite of CV death, MI, and stroke were significantly higher in DM patients, with adjusted 2-year rate ratios of 1.43 (P < .01) and 1.55 (P < .001), respectively. CONCLUSIONS: Stable post-MI patients with DM (especially insulin treated) had poorer EQ-5D scores, higher hospitalization rates and LoS, and worse clinical outcomes vs those without DM. Strategies focusing specifically on this high-risk population should be developed to improve outcomes. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01866904 (https://clinicaltrials.gov).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".