Impact of treatment management on the hospital stay in patients with acute coronary syndrome
Bibliographic record
Abstract
BACKGROUND: The length of hospital stay in patients with acute coronary syndrome (ACS) is crucial for determining clinical outcomes, managing healthcare resources, controlling costs, and ensuring patient well-being. This study aimed to explore the impact of treatment approaches on the length of stay (LOS) for ACS patients. METHODS: A total of 7109 ACS cases were retrospectively recruited from a hospital between 2018 and 2023. Demographical baseline data, laboratory examinations, and diagnostic and treatment information of the included subjects were extracted from electronic medical records to investigate the factors contributing to extended hospitalization and further explore the impact of treatment management on the LOS. RESULTS: Advanced age, female sex, and elevated levels of B-type natriuretic peptide, C-reactive protein and higher low-density lipoprotein cholesterol were identified as risk factors for extended hospitalization. At the 0.2-0.9 quantile of LOS, compared with the non-invasive group, the percutaneous transluminal coronary angioplasty group and the stent implantation group exhibited decreases in LOS of 0.37-2.37 days and 0.12-2.28 days, respectively. Stratified analysis based on diagnosis showed that percutaneous coronary intervention decreased hospitalization time in the high quantile of LOS but conversely increased it in the low quantile. CONCLUSION: Percutaneous coronary intervention is important for reducing hospitalization duration, particularly for patients susceptible to prolonged stays. Early and assertive management intervention, incorporating elements such as lipid-lowering therapy, and anti-inflammatory agents, is essential for improving outcomes within high-risk groups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".