Effect of a High-Sensitivity Troponin I and Associated Diagnostic Protocol on Emergency Department Length of Stay: A Retrospective Cohort Study
Bibliographic record
Abstract
Background The objective of this study was to assess the introduction of a high-sensitivity troponin I (hs-TnI) assay and its associated accelerated protocol on ED length of stay (LOS) for patients presenting with chest pain, compared to an accelerated diagnostic protocol (ADP) using conventional troponin (TnI) testing. Methods We conducted a retrospective cohort study of all adults with a primary presenting complaint of chest pain of cardiac origin and a Canadian Triage and Acuity Scale (CTAS) score of 2 or 3 between November 8, 2019, and November 9, 2021, to a tertiary care urban Canadian ED. The primary outcome was ED LOS. Secondary outcomes included consultation proportions and Major Adverse Cardiac Events (MACE) within 30 days of the index ED visit. Results 2640 patients presenting with chest pain were included, with 1333 in the TnI group and 1307 in the hs-TnI group. Median ED LOS decreased significantly from 392 minutes for the TnI group and 371 minutes for the hs-TnI group (Median difference=21 minutes; 95% CI: 5.3, 36.7). Consultations and admissions were not statistically different between study periods. The MACE outcomes did not change following the implementation of the hs-TnI test (13.6% vs 13.1%; p=0.71). Conclusions The implementation of an accelerated CP protocol using a hs-TnI assay in a tertiary care Canadian ED was associated with a modest reduction of LOS for all patients and a substantial reduction of LOS for patients undergoing serial troponin testing. Moreover, this strategy was safe with no increase in adverse outcomes.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".