Differences in the profile and risk of acute coronary syndrome patients stratified by country-level human development index: results from the global TRILOGY ACS trial
Bibliographic record
Abstract
Purpose: Variations in treatment and outcomes of ACS have been reported among different countries, and most studies include developed countries only. However, regional differences in enrollment and outcomes of global ACS trials may be influenced by economic status and human development of individual countries. Methods: We analyzed the global TRILOGY ACS trial database to study 9301 medically managed (no revascularization performed for index ACS events) patients with unstable angina or NSTEMI enrolled in 51 countries to compare baseline clinical characteristics and clinical outcomes through 30 mos by country-level human development indices (HDI) determined by the UN Development Programme. Results: There were 27, 18, and 6 countries classified as very high (HDI 0.937-0.795), high (HDI 0.783-0.679), and medium (HDI 0.663-0.519) human development countries, respectively. Baseline characteristics and cardiovascular outcomes within each country category are shown in the table. Baseline characteristics and CV outcomes Conclusions: Clinical profiles of patients enrolled in medium-developed countries differ substantially compared to very-high and high-HDI countries. Lower unadjusted event rates in medium-HDI countries may be explained by younger age and lower burden of comorbidities of patients in these countries, as these differences, except for lower MI rates, did not persist after adjustment. These findings have important implications for future global ACS trials.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".