Risk scores for risk stratification in acute coronary syndromes: useful but simpler is not necessarily better
Bibliographic record
Abstract
AIMS: Our objectives were (i) to compare the discriminatory performance of the Thrombolysis in Myocardial Infarction risk score (TIMI RS), Platelet glycoprotein IIb/IIIa in Unstable angina: Receptor Suppression Using Integrilin Therapy risk score (PURSUIT RS), and Global Registry of Acute Cardiac Events risk score (GRACE RS) for in-hospital and 1 year mortality across the broad spectrum of non-ST-elevation acute coronary syndromes (ACS) and (ii) to determine their incremental prognostic utility beyond overall risk assessment by physicians. METHODS AND RESULTS: We calculated the TIMI RS, PURSUIT RS, and GRACE RS for 1,728 patients with non-ST-elevation ACS in the prospective, multicentre, Canadian ACS II Registry. Discriminatory performance was measured by the c-statistic (area under receiver-operating characteristic curve) and compared by the method described by DeLong. TIMI RS, PURSUIT RS, and GRACE RS all demonstrated good discrimination for in-hospital death (c-statistics = 0.68, 0.80, 0.81, respectively, all P < 0.001) and 1 year mortality (c-statistics = 0.69, 0.77, 0.79, respectively, all P < 0.0001). However, PURSUIT RS and GRACE RS performed significantly better than the TIMI RS in predicting in-hospital (P = 0.036 and 0.02, respectively) and 1 year (P = 0.006 and 0.001, respectively) outcomes. In multivariable analysis adjusting for the use of in-hospital revascularization, stratification by tertiles of risk scores (into low, intermediate, and high-risk groups) furnished independent and greater prognostic information compared with risk assessment by treating physicians for 1 year outcome. CONCLUSION: Compared with TIMI RS, both PURSUIT RS and GRACE RS allow better discrimination for in-hospital and 1 year mortality in patients presenting with a wide range of ACS. All three risk scores confer additional important prognostic value beyond global risk assessment by physicians. These validated risk scores may refine risk stratification, thereby improving patient care in routine clinical practice.
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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 | 0.032 | 0.066 |
| Meta-epidemiology (narrow) | 0.003 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".