The Average Effect of Emergency Department Admission on Readmission and Mortality for Older Adults With Chest Pain
Bibliographic record
Abstract
BACKGROUND: Many older adults (65+) present to the Emergency Department (ED) with chest pain, but do not have otherwise clear clinical indication of whether they should be admitted or discharged. This uncertainty leads to decisions that are highly variable-in addition to already being costly-which could have adverse consequences, since older adults are particularly vulnerable from hospitalization. OBJECTIVE: The objective of this study was to determine whether admitting versus discharging an older adult presenting to the ED with chest pain reduces risk of mortality and readmission. STUDY DESIGN: Electronic health records were curated from an academic hospital system between January 1, 2014, and September 27, 2018. Average effects of admission on 30-day readmission and mortality were estimated using a new causal inference approach based on a latent-variable model of the admission process. Additional analyses assessed moderators and robustness of estimates. SUBJECTS: Older patients (n=3090) presenting to University of Wisconsin Hospital ED. MEASURES: Readmission and mortality within 25, 30, and 35 days of discharge from the ED for discharged patients or the hospital for admitted patients RESULTS:: For older chest pain patients, admission is estimated to lower the 30-day risk of readmission by 42.8% (95% confidence interval: 41.0%-44.6%) but increase the 30-day risk of mortality by 0.8% (95% confidence interval: 0.4%-1.2%). Individuals with higher hierarchical conditional category scores or diabetes with complications have both lower 30-day risk of readmission and higher 30-day risk of mortality compared with their counterparts (P≤0.02). CONCLUSIONS: Our findings suggest ED admission may prevent readmission at the cost of increasing mortality risk for older chest pain patients, especially those with comorbidity. Additional studies are needed to validate these findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".