Use of risk scores to identify lower and higher risk subsets among <scp>COMPASS‐eligible</scp> patients with chronic coronary syndromes. Insights from the <scp>CLARIFY</scp> registry
Bibliographic record
Abstract
Abstract Background The COMPASS trial showed a reduction of ischemic events with low‐dose rivaroxaban and aspirin in chronic coronary syndromes (CCS) compared with aspirin alone, at the expense of increased bleeding. Hypothesis The CHA2DS2VaSc Score, REACH Recurrent Ischemic (RIS), and REACH Bleeding Risk Score (BRS) could identify patients with a favorable trade‐off between ischemic and bleeding events, among COMPASS‐eligible patients. Methods We identified the COMPASS‐eligible population within the CLARIFY registry (>30.000 patients with CCS). High‐bleeding risk patients (REACH BRS > 10) were excluded, as in the COMPASS trial. Patients were categorized as low (0–1) or high (≥ 2) CHA2DS2VaSc; low (0–12) or intermediate (13–19) REACH RIS, and low (0–6) or intermediate (7–10) REACH BRS. Ischemic outcome was the composite of cardiovascular death, myocardial infarction or stroke. Bleeding was defined as serious bleeding (haemorrhagic stroke, hospitalization for bleeding, transfusion). Results The COMPASS‐eligible population comprised 5.142 patients with ischemic and bleeding outcome of 2.3 (2.1–2.5) and 0.5 (0.4–0.6) per 100 patient‐years, respectively. Patients with intermediate REACH RIS (n = 1934 [37.6%]) had the higher ischemic risk (3.0 [2.6–3.4]) with similar bleeding risk (0.5 [0.4–0.7]) as the overall population. Patients with low CHA2DS2VaSc (n = 229 [4.4%]) had a very low ischemic risk (0.6 [0.3–1.3]) with similar bleeding risk (0.5 [0.2–1.1]). Conclusions Intermediate REACH RIS identified potential optimal candidates for adjunction of low‐dose rivaroxaban while patients with low CHA2DS2VaSc score .appears unlikely to benefit from the COMPASS regimen. None of the three risk scores predicted the occurrence of serious bleeding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".