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Record W1747109111 · doi:10.25011/cim.v32i5.6929

Cardiac troponin in the intensive care unit

2009· review· en· W1747109111 on OpenAlexaffvenue
Wendy Lim

Bibliographic record

VenueClinical and investigative medicine · 2009
Typereview
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineMyocardial infarctionTroponinCoronary care unitIntensive care unitCritically illCardiologyInternal medicineIntensive care medicineAcute coronary syndromeTroponin IIntensive careClinical significanceBiomarkerTroponin T

Abstract

fetched live from OpenAlex

PURPOSE: Cardiac troponin is specific to the myocardium and is a useful biomarker for the diagnosis of myocardial infarction. Detection of elevated blood levels of troponin indicates damage to myocardial cells, but does not indicate the mechanism. Causes other than acute coronary syndromes and myocardial infarction can result in troponin elevation and these conditions frequently occur in critically ill patients in the intensive care unit. The interpretation, clinical significance and appropriate management of an elevated troponin measurement in critically ill patients are uncertain. SOURCE: Studies evaluating the prevalence of troponin elevation among medical-surgical intensive care unit patients, and its prognostic significance with regards to adverse outcomes will be reviewed. CONCLUSIONS: Cardiac troponin elevation is common and observed in 40 to 50% of critically ill medical and surgical patients. Elevated levels appear to identify patients at increased risk for death in the intensive care unit or hospital setting. This finding, and its relation to myocardial infarction and acute coronary syndromes, requires prospective study to better understand the implications for diagnosis and management.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.414
GPT teacher head0.495
Teacher spread0.081 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2009
Admission routes2
Has abstractyes

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