Long-term outcomes among stable post-acute myocardial infarction patients living in rural versus urban areas: insights from the prospective, observational TIGRIS registry
Bibliographic record
Abstract
BACKGROUND: Insights on the differences in clinical outcomes, quality of life (QoL) and health resource utilisation (HRU) with different levels of care available to post-acute myocardial infarction (AMI) populations in rural and urban settings are limited. METHODS: The long-Term rIsk, clinical manaGement, and healthcare Resource utilisation of stable coronary artery dISease (TIGRIS), a prospective, observational registry, enrolled 8452 patients aged ≥50 years 1-3 years post-AMI from June 2013 to November 2014 from 24 countries in Asia Pacific/Australia, Europe, North America and South America. Differences in QoL (measured using the EuroQol Research Foundation instrument) and HRU between patients in rural and urban settings were evaluated in this post hoc analysis. The incidence of clinical endpoints (cardiovascular (CV) death, AMI, unstable angina with urgent revascularisation and stroke; bleeding; and all-cause mortality) was analysed. Data were collected at baseline and every 6 months for 24 months. RESULTS: There were fewer hospitalisations and visits to general practitioners (GPs) and cardiologists in the rural versus urban populations (adjusted event rate ratio (ERR)=0.90 (95% CI, 0.82 to 1.00, p=0.04); ERR=0.84 (95% CI, 0.78 to 0.92, p<0.001); ERR=0.86 (95% CI, 0.81 to 0.92, p<0.001), respectively). No statistically significant differences were observed between rural and urban populations in all-cause death, AMI, unstable angina with urgent revascularisation, CV death, stroke, major bleeding events and health-related QoL. The adjusted incidence rate ratio was 0.92 (95% CI, 0.74 to 1.15) for the composite of CV death, AMI and stroke. CONCLUSIONS: Living in rural areas was associated with fewer GP/cardiologist visits and hospitalisations; no significant differences in clinical outcomes and QoL were observed. TRIAL REGISTRATION NUMBER: NCT01866904.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".