Risk stratification, management and outcomes of patients with non-ST elevation acute coronary syndrome: a Canadian teaching hospital perspective.
Bibliographic record
Abstract
BACKGROUND: Current guidelines for non-ST elevation acute coronary syndromes (NSTACS) recommend tailoring the intensity of therapeutic management according to the baseline risk of the patient. Although the clinical characteristics, risk stratification and therapeutic management of contemporary patients with NSTACS have been reported for other geographical regions, this information has not been documented from a Canadian perspective. OBJECTIVES: To describe the baseline clinical characteristics, therapeutic management and clinical outcomes of contemporary patients with NSTACS at a Canadian, tertiary care, teaching hospital, and to retrospectively risk stratify the patients with NSTACS according to the American College of Cardiology (ACC)/American Heart Association (AHA) and Thrombolysis in Myocardial Infarction (TIMI) risk guidelines to characterize management and outcomes according to the various risk classifications. METHODS: Baseline demographics, procedural variables and clinical outcome data were retrospectively collected in 380 patients with a diagnosis of NSTACS from July 1999 to July 2000. Patients were retrospectively categorized into high, intermediate and low risk categories using two classification schemes. RESULTS: According to the ACC/AHA guidelines, 10.3% and 89.7% of patients were intermediate and high risk, respectively. Applying the TIMI risk score, 20.0%, 52.4% and 27.6% of patients were low, intermediate and high risk, respectively. The use of antithrombotic, acetylsalicylic acid and beta-blocker therapy was very high both in hospital and at discharge. Glycoprotein IIb/IIIa inhibitors, angiotensin-converting enzyme inhibitors and lipid lowering agents were all underutilized. The use of pharmacological therapies and cardiovascular interventions did not appear to correlate with the level of risk of the patient, at least within these classification schemes. Adverse clinical events in hospital and length of hospital stay increased as the risk level of the patients increased. CONCLUSIONS: According to the ACC/AHA guidelines, patients with a discharge diagnosis of NSTACS in a nontrial setting are a high risk population, requiring prompt recognition and aggressive management. This study serves as an integral part of clinical practice to continually evaluate the quality of medical care.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".