Outcomes and Management When Using High-sensitivity Versus Conventional Cardiac Troponin in Patients With Chest Pain: A Meta-analysis
Bibliographic record
Abstract
ABSTRACT Background Cardiac troponin (cTn) measurement is pivotal in diagnosing and managing chest pain. High-sensitivity cTn (hs-cTn) assays are slowly supplanting conventional cardiac troponin (c-cTn) use, allowing earlier identification of high-risk patients and diagnosis of myocardial infarction (MI). This improved sensitivity is said to come at the cost of reduced specificity for MI. However, there is a paucity of data regarding the exact impact of this change in patient management and outcomes. Objectives To compare outcomes and management of patients with chest pain when using hs-cTn versus c-cTn. Methods We conducted a systematic search of studies in all languages across various databases. Inclusion criteria for studies were (1) observational or randomized trials, (2) included adult patients presenting with chest pain, (3) use of hs-cTn or c-cTn in diagnosis, (3) reported data on any of the pre-defined outcomes. The primary outcome was all-cause mortality and secondary outcomes were major adverse cardiovascular events (MACE), MI following index admission, coronary angiography, and revascularization. Study quality was appraised using the Cochrane Tool for Assessing Risk of Bias for randomized trials and the Newcastle-Ottawa Quality Assessment scale for observational studies. Outcomes were analyzed using Review Manager (RevMan) 5.3, employing Mantel-Haenszel analysis of random effects to compute for relative risk and odds ratio. Results Pooled analysis from 5 studies showed that among patients with chest pain, those for whom hs-cTn over c-cTn was used had no difference in all-cause mortality (RR 1.01, 95% CI 0.92-1.12, p=0.82, I 2 =0%), a significant decrease in MI (RR 0.74, 95% CI 0.63-0.87, p=0.0003) and a trend towards increase in MACE (RR 1.08, 95% CI 1.00-1.16, p=0.04, I 2 =0%). They were more likely to undergo coronary angiogram (OR 1.52, 95% CI 1.02-2.28, p=0.04) and revascularization (OR 1.34, 95% CI 1.03-1.75, p=0.03). Conclusion Use of hs-cTn over conventional cTn led to higher rates of coronary angiography and revascularization. While there was significant reduction in myocardial infarction, there was no reduction in all-cause mortality and even a trends towards increased MACE.
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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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.073 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".