Clinical Effectiveness of Cardiac Noninvasive Diagnostic Testing in Patients Discharged From the Emergency Department for Chest Pain
Bibliographic record
Abstract
Background More than 4 million cardiac noninvasive diagnostic tests are performed annually in the United States. However, questions remain regarding their effectiveness in improving clinical outcomes. We sought to evaluate whether noninvasive diagnostic tests were associated with lower rates of myocardial infarction or cardiovascular death when compared with no testing. Methods and Results We performed a retrospective, population‐based cohort study of adults evaluated for chest pain and discharged home from an emergency department in Ontario, Canada. Propensity score matching was employed to reduce confounding between the testing and nontesting groups. There were 370 863 patients evaluated in our cohort. Rates of the composite outcome were low for both groups after propensity‐score matching (0.29% and 0.78% for the nontesting group at 90 days and 1 year, respectively, and 0.34% and 0.68% for the noninvasive diagnostic test group at 90 days and 1 year respectively). Over 1 year, patients undergoing noninvasive diagnostic testing had a small but statistically significant lower hazard of developing the composite outcome of myocardial infarction or cardiovascular mortality (hazard ratio, 0.87; 95% CI , 0.78–0.96 [ P <0.01]), which appears to be driven by the high‐risk subgroup (hazard ratio, 0.75; 95% CI , 0.61–0.92 [ P <0.01]). Conclusions We report a lower observed rate of the composite outcome of cardiovascular death or myocardial infarction associated with noninvasive diagnostic testing following evaluation for chest pain in the emergency department. This lower rate was driven by the high‐risk subgroup. These results suggest that risk‐based testing should be considered for patients discharged from the emergency department for chest pain.
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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 | 0.005 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".