Bibliographic record
Abstract
BACKGROUND: The clinical significance of elevated cardiac troponin (cTn) level in patients in the intensive care unit (ICU) is uncertain. We reviewed the frequency of cTn elevation and its association with mortality and length of ICU stay in these patients. METHODS: Studies were identified using MEDLINE, EMBASE, and reference list review. We included observational studies of critically ill patients that measured cTn at least once and reported the frequency of elevated cTn or outcome (mortality and length of ICU or hospital stay). We pooled the odds ratios (ORs) using the inverse variance method in studies that conducted multivariable analysis to examine the relationship between elevated cTn and mortality (adjusted analysis). We calculated the weighted mean difference in length of stay between patients with and without elevated cTn and pooled the results using the inverse variance method (unadjusted analysis). RESULTS: A total of 23 studies involving 4492 critically ill patients were included. In 20 studies, elevated cTn was found in a median of 43% (interquartile range, 21% to 59%) of 3278 patients. In adjusted analysis (6 studies comprising 1706 patients), elevated cTn was associated with an increased risk of death (OR, 2.5; 95% confidence interval [CI], 1.9 to 3.4; P < .001). In the unadjusted analysis (8 studies comprising 1019 patients), elevated cTn was associated with an increased length of ICU stay of 3.0 days (95% CI, 1.0 to 5.1 days; P = .004) and an increased length of hospital stay of 2.2 days (95% CI, -0.6 to 4.9; P = .12). CONCLUSIONS: Elevated cTn measurements among critically ill patients are associated with increased mortality and ICU length of stay. Research is needed to clarify the underlying causes of elevated cTn in this population and to examine their clinical significance.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".