Risk factors of sudden death and death from arrhythmia in patients with non-ST elevation acute coronary syndromes in China
Bibliographic record
Abstract
Objective To analyze the relationship between sudden death and death from arrhythmia and multiple risk factors in patients with nonST elevation acute coronary syndromes in two years of followup in China. Methods This study was a part of an international multicentre registry Organization to Assess Strategies for Ischemic Syndromes(OASIS) . The patients admitted to the hospital with nonST elevation acute coronary syndrome were enrolled. No particular intervention was given for the treatment. All patients had been followedup for two years. The patients' clinical characteristics, therapeutic regimes and major events during hospitalization and two years' followup period were recorded by filling in Case Report Forms according to the protocol offered by Canadian Cardiovascular Collaboration. Cox regression model was used to analyze the association with the most common causes of death and multiple factors recorded. Results From April 1999 to December 2001, 2 294 cases were enrolled in 38 hospitals in China nationwide. Among them 2 188 patients two years followup was accomplished. The mean age of the patients was (62 8± 8 1)years . Male gender was dominant (62 3%). The clinical diagnosis at admission was unstable angina in 88 5% of the patients and non Qwave myocardial infarction(MI) in the remaining 11 5%. The mortality was 7 6% with total deaths of 174 by the end of 24month follow up. The most common cause of death was severe arrhythmias or sudden death (92 cases, 52 9%). More than 70 factors were analyzed by Cox regression model in order to determine which were the predominant factors of death. Major risk factors that predisposed to death were: number of episodes of MI during followup period, reMI within 24 hours during hospitalization, heart failure during hospitalization, previous history of MI, recurrent angina pectoris during hospitalization, the duration of hospitalization, and patient age. Protective factors that reduced the chance of death were: the frequency of using nitrate, frequency of taking antiplatelet medicine or βblocker during followup period. Conclusion In China, the most common cause of death in patients with nonST elevation acute coronary syndromes is severe arrhythmias or sudden death, and it is related with the severity of coronary artery disease and the age of patients in majority of cases. Some factors that influence survival are similar to those established by previous evidence based medicine.
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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 | 0.001 |
| 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) | 0.001 | 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".