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Record W4413282907 · doi:10.31762/ahj2534.0203

Outcomes and Management When Using High-sensitivity Versus Conventional Cardiac Troponin in Patients with Acute Chest Pain: A Meta-analysis

2025· article· en· W4413282907 on OpenAlexaboutno aff
John Christopher A. Pilapil, Paula Victoria Catherine Cheng-Bromeo, Paul Anthony O Alad, Jaime Alfonso M. Aherrera

Bibliographic record

VenueASEAN heart journal · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicineChest painInternal medicineTroponinCardiologyTroponin IIntensive care medicineMyocardial infarction

Abstract

fetched live from OpenAlex

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 assays as part of the diagnostic and therapeutic strategy. 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, I2=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, I2=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, with no reduction in all-cause mortality and no significant MACE reduction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.036
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0260.073
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.036
GPT teacher head0.312
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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