Prospective observational study of acute coronary syndromes in China: practice patterns and outcomes
Bibliographic record
Abstract
OBJECTIVE: To describe the investigation and management of patients admitted to hospitals in China with suspected acute coronary syndromes (ACS) and to identify potential areas for improvement in practice. DESIGN: A multicentre prospective survey of sociodemographic characteristics, medical history, clinical features, in-hospital investigations, treatment practices and major events among patients with suspected ACS. SETTING: Large urban public hospitals. PATIENTS: Consecutive patients admitted to in-patient facilities with a diagnosis of suspected acute myocardial infarction (MI) or unstable angina pectoris. MAIN OUTCOME MEASURES: Myocardial infarction/re-infarction, heart failure, death. RESULTS: Between September 2004 and May 2005, data were collected prospectively from 2973 patients admitted to 51 hospitals in 18 provinces of China. An initial diagnosis of ST elevation MI, non-ST elevation MI and unstable angina was made in 43%, 11% and 46% of patients, respectively. Diagnosis was inconsistent with objective measures in up to 20% of cases. At both tertiary and non-tertiary centres, there was little evidence that clinical risk stratification was used to determine the intensity of investigation and management. The mortality rate during hospitalisation was 5% overall and similar in tertiary and non-tertiary centres, but reported in-hospital re-infarction rates (8%) and heart failure rates (16%) were substantially higher at non-tertiary centres. CONCLUSION: This study has identified a number of areas in the management of ACS patients, including diagnosis and risk stratification, which deviate from current guidelines. These findings will help inform the introduction of widely used quality improvement initiatives such as clinical pathways.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".