Using the Zwolle Risk Score at Time of Coronary Angiography to Triage Patients With ST‐Elevation Myocardial Infarction Following Primary Percutaneous Coronary Intervention or Thrombolysis
Bibliographic record
Abstract
Background The Zwolle Risk Score was designed to identify the risk of complications in patients with ST‐segment‒elevation myocardial infarction (STEMI) following percutaneous coronary intervention (PCI). Its utility following PCI in STEMI treated with thrombolysis is unknown. The objective was to evaluate the safety of using the Zwolle Risk Score to triage patients with STEMI following PCI, including patients receiving thrombolysis. Methods and Results Patients aged ≥18 years with STEMI and primary PCI or PCI after thrombolysis were included. A triage protocol was developed, with high‐risk patients those with Zwolle Risk Score ≥4 triaged to the cardiac intensive care unit. A prospective evaluation of the triaging protocol was performed on 452 patients, mean age 65±12 years, 73% men. Median Zwolle Risk Score was 3 (interquartile range, 2‒5), with 257 low‐risk (57%), and 195 high‐risk (43%) patients. Adherence to the protocol was 91%. In‐hospital mortality was 0.4% in low‐risk and 13% in high‐risk patients ( P <0.001). Seventy‐two patients (16%) received thrombolysis. Median time post‐thrombolysis to PCI was 281 minutes (interquartile range, 219‒376). In‐hospital mortality was 0% versus 9% ( P =0.083) for low‐ and high‐risk patients, respectively. High‐risk patients had higher rates of cardiogenic shock (34% versus 1%, P <0.001), pulmonary edema (60% versus 9%, P <0.001), arrhythmia (25% versus 2%, P <0.001), blood transfusion (10% versus 2%, P <0.001), and stroke (4% versus 0.4%, P =0.011). Median hospital costs decreased by $1419 per low‐risk patient after protocol implementation. Conclusions For patients with STEMI following primary PCI or PCI following thrombolysis, a Zwolle‐based triaging system is safe and may decrease cardiac intensive care unit usage costs.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".