ArticleAmerican journal of clinical pathology2022
Emergency Department Management of Chest Pain With a High-Sensitivity Troponin-Enabled 0/1-Hour Rule-Out Algorithm.
Article in American journal of clinical pathology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Pooled it
- Clinical performance of the next generation Elecsys Troponin T high-sensitivity Gen 6 assay in acute coronary syndrome (PERFORM-TSIX): study design.Clinical research in cardiology : official journal of the German Cardiac Society · 2026Observational
- Historical Review of Acute Myocardial Ischemia Risk Assessment.Hawai'i journal of health & social welfare · 2026Review
- Performance Evaluation of the 2020 European Society of Cardiology 0-hour/1-hour Algorithm Using High-sensitivity Cardiac Troponin I for Non-ST-segment Elevation Acute Coronary Syndrome and Mortality Assessment Based on 1-year Real-world Data.Annals of laboratory medicine · 2026Article
- Article
- Improved Utilization of Serial Testing Without Increased Admissions after Implementation of High-Sensitivity Troponin I: a Controlled Retrospective Cohort Study.Journal of general internal medicine · 2024Article
- Implementation of High-Sensitivity Cardiac Troponin Assays in the United States.Journal of the American College of Cardiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
objectivesThe analytical sensitivity of high-sensitivity cardiac troponin T (hsTnT) assays has enabled rapid myocardial infarction rule-out algorithms for emergency department (ED) presentations. Few studies have analyzed the real-world impact of hsTnT algorithms on outcomes and operations.
methodsComparison of ED length of stay (LOS) and 30-day outcomes (return to ED, inpatient admission, and mortality) for patients presenting with chest pain during 2 separate 208-day periods using a 0/1-hour hsTnT-enabled algorithm or fourth-generation TnT.
resultsDischarge, 30-day readmission, and 30-day mortality rates were not significantly different with fourth-generation TnT vs hsTnT. Thirty-day return rates were significantly decreased with hsTnT (17.4% vs 14.9%; P < .01). For encounters with TnT measured at least twice and resulting in discharge, median ED LOS decreased by 61 minutes with the use of hsTnT (488 vs 427 minutes; P < .0001). Median time between first and second TnT results decreased by 82 minutes with hsTnT (202 vs 120 minutes; P < .0001), suggesting that the 0/1-hour algorithm was incompletely adopted.
conclusionsImplementation of the hsTnT algorithm was associated with decreased 30-day return rates and decreased ED LOS for a subset of patients, despite incomplete adoption of the 0/1-hour algorithm.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.