Outcomes from the REACH Registry for Australian general practice patients with or at high risk of atherothrombosis
Bibliographic record
Abstract
OBJECTIVE: To report on 1-year cardiovascular (CV) event rates in patients with established cardiovascular disease (CVD) or with multiple cardiovascular risk factors. DESIGN, PATIENTS AND SETTING: Prospective cohort study of 2873 patients at high risk of atherothrombosis based on the presence of multiple risk factors and overt coronary artery disease (CAD), cerebrovascular disease (CerVD) or peripheral arterial disease (PAD) presenting to 273 Australian general practitioners; this study was conducted as part of the international REACH Registry. MAIN OUTCOME MEASURES: One-year rates of cardiovascular death, myocardial infarction, stroke, and hospitalisation for cardiovascular procedures. RESULTS: The cardiovascular death rate at 1 year was 1.4%. The combined cardiovascular death, non-fatal MI, stroke and hospitalisation rate for vascular disease affecting one location at 1 year was 11%. Even for patients with no overt disease, but with multiple risk factors, the 1-year combined event rate was 4.2%. The highest combined event rate was in patients with PAD (21.0%), and in patients with atherothrombotic disease identified in all three locations (coronary arteries, cerebrovascular system and peripheral arteries) at 39%. CONCLUSION: The rate of clinical events in community-based patients with stable atherothrombotic disease increases dramatically with the severity of disease and the number of vascular beds involved. Where disease was evident in all three locations, and for patients with PAD alone, the 1-year risk of cardiovascular events was substantially increased. Poor adherence to statin therapy in the secondary preventive setting is a major treatment gap that needs to be closed; the influences of obesity and diabetes warrant further investigation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".