Prognostic Value of Troponin and Creatine Kinase Muscle and Brain Isoenzyme Measurement after Noncardiac Surgery
Bibliographic record
Abstract
BACKGROUND: There is uncertainty regarding the prognostic value of troponin and creatine kinase muscle and brain isoenzyme measurements after noncardiac surgery. METHODS: The current study undertook a systematic review and meta-analysis. The study used six search strategies and included noncardiac surgery studies that provided data from a multivariable analysis assessing whether a postoperative troponin or creatine kinase muscle and brain isoenzyme measurement was an independent predictor of mortality or a major cardiovascular event. Independent investigators determined study eligibility and abstracted data in duplicate. RESULTS: Fourteen studies, enrolling 3,318 patients and 459 deaths, demonstrated that an increased troponin measurement after surgery was an independent predictor of mortality (odds ratio [OR] 3.4, 95% confidence interval [CI] 2.2-5.2), but there was substantial heterogeneity (I(2) = 56%). The independent prognostic capabilities of an increased troponin value after surgery in the 10 studies that assessed intermediate-term (≤ 12 months) mortality was an OR = 6.7 (95% CI 4.1-10.9, I(2) = 0%) and in the 4 studies that assessed long-term (more than 12 months) mortality was an OR = 1.8 (95% CI 1.4-2.3, I(2) = 0%; P < 0.001 for test of interaction). Four studies, including 1,165 patients and 202 deaths, demonstrated an independent association between an increased creatine kinase muscle and brain isoenzyme measurement after surgery and mortality (OR 2.5, 95% CI 1.5-4.0, I(2) = 4%). CONCLUSIONS: An increased troponin measurement after surgery is an independent predictor of mortality, particularly within the first year; limited data suggest an increased creatine kinase muscle and brain isoenzyme measurement also predicts subsequent mortality. Monitoring troponin measurements after noncardiac surgery may allow physicians to better risk stratify and manage their patients.
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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 | 0.028 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.017 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".