[The clinical characteristics of acute coronary syndrome in China].
Bibliographic record
Abstract
OBJECTIVE: To analyse the characteristics of and the therapeutic measures for patients with acute ischemic syndromes in China. METHOD: This study is a part of an international multicentre registry-the Organization to Assess Strategies for Ischemic Syndromes (OASIS). Since April 1999, the data of patients admitted to hospital with acute ischemic cardiac chest pain have been collected by filling Case Report Forms offered by the Canadian Cardiovascular Collaboration. The main clinical characteristics of the patients and in hospital events were recorded. RESULTS: Two thousand two hundred and ninety cases of acute ischemic syndromes from 38 hospitals throughout the nation were enrolled in the registry (include unstable angina and non Q-wave myocardial infarction). The mean age of the patients was 62.8. The percentage of patients with chest pain at presentation and abnormal ECG was 48.9% and 89.7%, respectively. The clinical diagnosis at admission was unstable angina (UA) in 90.9% of the patients and non Q-wave myocardial infarction (non Q-wave MI) in the remaining 9.0%. During hospitalization the intervention procedures performed were as follows: thrombolytic therapy (TT) in 75 cases (3.3%), coronary angiography (CA) in 798 cases (34.9%), percutaneous transluminal coronary angioplasty (PTCA) in 403 cases (17.6%) and coronary artery bypass graft surgery (CABG) in 97 cases (4.2%). Nitrates (oral or patch) and anti platelet therapy were used in 2 212 cases (96.6%) and 2 163 cases (94.5%), respectively. The incidence of major in hospital events was 15.2%, including 31 deaths (1.4%). CONCLUSION: The patients with acute ischemic syndromes were diagnosed as unstable angina mostly in China. A relatively high PTCA rate but low CABG rate were noted in China. The most common cause of in hospital death is severe arrhythmias or sudden death.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".