Prognostic impact of the residual <scp>SYNTAX</scp> score on in‐hospital outcomes in patients undergoing primary percutaneous coronary intervention
Bibliographic record
Abstract
OBJECTIVES: This study sought to assess the impact of residual coronary artery disease (CAD), using the residual SYNTAX score (rSS), on in-hospital outcomes after primary percutaneous intervention (PPCI). The study also aimed to determine independent predictors for high rSS. Residual CAD has been associated with worsened prognosis in patients undergoing PCI for non-ST acute coronary syndromes. The rSS is a systematic angiographic score that measures the extent and complexity of residual CAD after PCI. MATERIALS AND METHODS: Data from 243 consecutive patients undergoing PPCI for ST-elevation myocardial infarction (STEMI) were analyzed. The rSS was derived from post-PPCI angiography. Patients were dichotomized into low (<8) and high rSS (≥8) groups and outcomes were compared between groups. The primary outcome of net adverse cardiovascular events (NACE) consisted of a composite of in-hospital death, congestive heart failure (CHF), recurrent MI and bleeding. RESULTS: The mean rSS was 4.7 (±7.2). A high rSS was associated with the primary outcome (P < 0.0001), in-hospital death (P = 0.0026), periprocedural death (P < 0.0001), CHF (P < 0.0004) and acute kidney injury (P < 0.0019). A high rSS was also an independent predictor of the primary outcome with an OR of 3.82. Independent predictors of a high rSS included a history of diabetes (OR 2.8), previous MI (OR 5.75), 2-vessel disease (VD) (OR 15.48, vs. 1-VD) and 3-VD (OR 57.06, vs. 1-VD). CONCLUSIONS: Residual CAD, as assessed by the rSS, confers a worsened prognosis in patients undergoing PPCI. Diabetes, previous MI and multi-vessel disease were independent predictors of a high rSS. © 2016 Wiley Periodicals, Inc.
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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 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".