Elevated Cardiac Troponin Levels in Critically Ill Patients: Prevalence, Incidence, and Outcomes
Bibliographic record
Abstract
BACKGROUND: Levels of cardiac troponin, a sensitive and specific marker of myocardial injury, are often elevated in critically ill patients. OBJECTIVES: To document elevated levels of cardiac troponin I in patients in a medical-surgical intensive care unit and the relationship between elevated levels and electrocardiographic findings and mortality. METHODS: A total of 198 patients expected to remain in the intensive care unit for at least 72 hours were classified as having myocardial infarction (cardiac troponin I level >or=1.2 microg/L and ischemic electrocardiographic changes), elevated troponin level only (>or=1.2 microg/L and no ischemic electrocardiographic changes), or normal troponin levels. Events were classified as prevalent if they occurred within 48 hours after admission and as incident if they occurred 48 hours or later after admission. Factors associated with mortality were examined by using regression analysis. RESULTS: A total of 171 patients had at least one troponin level measured in the first 48 hours. The prevalence of elevated troponin level was 42.1% (72 patients); 38 patients (22.2%) had myocardial infarction, and 34 (19.9%) had elevated troponin level only. After the first 48 hours, 136 patients had at least 1 troponin measurement. The incidence of elevated troponin level was 11.8% (16 patients); 7 patients (5.1%) met criteria for myocardial infarction, and 2 (1.5%) had elevated troponin level only. Elevated levels of troponin I at any time during admission were associated with mortality in the univariate but not the multivariate analysis. CONCLUSIONS: Elevated levels of cardiac troponin I in critically ill patients do not always indicate myocardial infarction or an adverse prognosis.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".