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Record W3173577073 · doi:10.1093/ehjacc/zuab039

Direct comparison of high-sensitivity cardiac troponin T and I in the early differentiation of type 1 vs. type 2 myocardial infarction

2021· article· en· W3173577073 on OpenAlexaff
Thomas Nestelberger, Jasper Boeddinghaus, María Rubini Giménez, Pedro López‐Ayala, Paul David Ratmann, Patrick Badertscher, Karin Wildi, Desirée Wussler, Luca Koechlin, Ketina Arslani, Tobias Zimmermann, Michael Freese, Therese Rinderknecht, Òscar Miró, Francisco Javier Martín‐Sánchez, Damian Kawecki, Nicolas Geigy, Dagmar I. Keller, Raphael Twerenbold, Christian Müller

Bibliographic record

VenueEuropean Heart Journal Acute Cardiovascular Care · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsVancouver General HospitalUniversity of British Columbia
FundersSchweizerische HerzstiftungSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungStiftung für Kardiovaskuläre Forschung BaselAbbott FundRocheKnowles Teacher InitiativeSiemens USASingulex
KeywordsMedicineMyocardial infarctionInternal medicineCardiologyReceiver operating characteristicTroponin IArea under the curveConfidence intervalTroponin complexChest painTroponin T

Abstract

fetched live from OpenAlex

AIMS: To directly compare the diagnostic accuracy of high-sensitivity cardiac troponin (hs-cTn) T vs. hs-cTnI in the early non-invasive differentiation of Type 1 myocardial infarction (T1MI) due to plaque rupture and atherothrombosis from Type 2 myocardial infarction (T2MI) due to supply-demand mismatch. METHODS AND RESULTS: In a prospective multicentre diagnostic study, two independent cardiologists centrally adjudicated the final diagnosis of T1MI vs. T2MI according to the fourth universal definition of myocardial infarction (MI), using all available clinical information including cardiac imaging in patients presenting with acute chest pain. Diagnostic accuracy was quantified by the area under the receiver operating characteristics curve (AUC). The most extensively validated hs-cTnT-Elecsys and hs-cTnI-Architect assays were measured at presentation, 1 h, and 2 h. Among 5887 patients, 1106 (19%) had a final diagnosis of MI, including 860 (78%) T1MI and 246 (22%) T2MI. The AUC of hs-cTnT-Elecsys to differentiate T1MI from T2MI was moderate and comparable to that provided by hs-cTnI-Architect: hs-cTnT-Elecsys AUC-presentation 0.67 [95% confidence interval (CI) 0.64-0.71], AUC-1 h 0.70 (95% CI 0.66-0.74), and AUC-2 h 0.71 (95% CI 0.66-0.75) vs. hs-cTnI-Architect AUC-presentation 0.71 (95% CI 0.67-0.74), AUC-1 h 0.72 (95% CI 0.68-0.76), and AUC-2 h 0.74 (95% CI 0.69-0.78), all P = not significant (NS). Similarly, the AUC of absolute changes was moderate and comparable for hs-cTnT-Elecsys and hs-cTnI-Architect (all P = NS). Cut-off concentrations achieving at least 90% specificity for the differentiation of T1MI vs. T2MI were >114 ng/L for hs-cTnT-Elecsys [odds ratio (OR) 4.2, 95% CI 2.7-6.6] and >371 ng/L for hs-cTnI-Architect (OR 4.0, 95% CI 2.6-6.2). CONCLUSION: hs-cTnT-Elecsys and hs-cTnI-Architect provided comparable, albeit only moderate, diagnostic accuracy for the early differentiation of T1MI vs. T2MI. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov number, NCT00470587, https://clinicaltrials.gov/ct2/show/NCT00470587.

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)0.009
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.300
Teacher spread0.270 · 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 designObservational
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

Citations19
Published2021
Admission routes1
Has abstractyes

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