External validation of the ProACS score for risk stratication of patients with acute coronary
Bibliographic record
Abstract
Introduction: The ProACS risk score is an early and simple risk stratication score developed for all-cause in-hospital mortality in acute coronary syndromes (ACS) from a Portuguese nationwide ACS registry. Our center only recently participated in the registry and was not included in the cohort used for developing the score. Our objective was to perform an external validation of this risk score for short- and long-term follow-up. Methods: Consecutive patients admitted to our center with ACS were included. Demographic and admission characteristics, as well as treatment and outcome data were collected. The ProACS risk score variables are age (≥72 years), systolic blood pressure (≤116 mmHg), Killip class (2/3 or 4) and ST-segment elevation. We calculated ProACS, Global Registry of Acute Coronary Events (GRACE) and Canada Acute Coronary Syndrome risk score (C-ACS) risk scores for each patient. Results: A total of 3170 patients were included, with a mean age of 64± 13 years, 62% with ST-segment elevation myocardial infarction. All-cause in-hospital mortality was 5.7% and 10.3% at one-year follow-up. The ProACS risk score showed good discriminative ability for all considered outcomes (area under the receiver operating characteristic curve >0.75) and a good t, similar to C-ACS, but lower than the GRACE risk score and slightly lower than in the original development cohort. The ProACS risk score provided good differentiation between patients at low, intermediate and high mortality risk in both short- and long-term follow-up (p<0.001 for all comparisons).
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 | 0.017 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".