Factors associated with physician follow-up among patients with chest pain discharged from the emergency department
Bibliographic record
Abstract
BACKGROUND: Many patients with chest pain do not receive follow-up from a physician after discharge from the emergency department despite significant survival benefit associated with follow-up care. Our objective was to evaluate factors associated with physician follow-up to understand this gap in practice. METHODS: We conducted an observational study involving patients at high risk who were assessed for chest pain and discharged from an emergency department in Ontario between April 2004 and March 2010. We used multivariable logistic regression to determine the association of clinical and nonclinical characteristics with physician follow-up. RESULTS: We identified 56 767 patients, of whom 25.1% did not receive any follow-up by a physician, 69.0% were seen by their primary care physician, and 17.3% were seen by a cardiologist within 30 days. Patients who had medical comorbidities and cardiac conditions such as myocardial infarction or heart failure were less likely to have follow-up. In contrast, a previous visit to a primary care physician was associated with the highest odds of having physician follow-up (odds ratio [OR] 6.44, 95% confidence interval [CI] 5.91-7.01). Similarly, a previous visit to a cardiologist was strongly associated with follow-up by a cardiologist (OR 3.01, 95% CI 2.85-3.17). Patients evaluated in emergency departments with the highest tertile of chest pain volume were more likely to receive follow-up from any physician (OR 1.52, 95% CI 1.31-1.77) and from a cardiologist (OR 2.04, 95% CI 1.61-2.57). INTERPRETATION: Nonclinical factors are strongly associated with physician follow-up for patients with chest pain after discharge from the emergency department. However, patients with comorbidities and at higher risk for future adverse events are less likely to receive follow-up care.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 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".