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Record W2002122302 · doi:10.1001/archinte.162.1.79

Elevated Cardiac Troponin Levels in Patients With Submassive Pulmonary Embolism

2002· article· en· W2002122302 on OpenAlexaff
James D. Douketis, Mark Crowther, Eric Stanton, Jeffrey S. Ginsberg

Bibliographic record

VenueArchives of Internal Medicine · 2002
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicinePulmonary embolismCardiologyInternal medicineMyocardial infarctionChest painTroponin ITroponinCreatine kinase

Abstract

fetched live from OpenAlex

BACKGROUND: Cardiac troponins are reliable markers of myocardial injury that are being used increasingly in patients presenting with undifferentiated chest pain or dyspnea to diagnose an acute coronary syndrome. If elevated cardiac troponin levels also occur in patients with pulmonary embolism because of right ventricular dilation and myocardial injury, such patients could be misdiagnosed. We performed a prospective cohort study to determine the prevalence of elevated cardiac troponin I (cTnI) levels in patients with submassive pulmonary embolism. METHODS: Consecutive patients with objectively confirmed submassive pulmonary embolism and no previous history of ischemic heart disease, other cardiac disease, or renal insufficiency were included. Creatine kinase and cTnI levels were measured within 24 hours of clinical presentation on 2 occasions 8 to 12 hours apart. RESULTS: Of 24 patients with submassive pulmonary embolism, 5 (20.8%) had elevated cTnI levels of 0.4 microg/L or higher (95% confidence interval, 7.1-42.2%). One of these patients had a cTnI level higher than 2.3 microg/L that was suggestive of myocardial infarction. CONCLUSION: Pulmonary embolism should be considered in the differential diagnosis of patients presenting with undifferentiated chest pain or dyspnea and an elevated cardiac troponin level.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.269
Teacher spread0.252 · 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

Citations126
Published2002
Admission routes1
Has abstractyes

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