High-Sensitivity Cardiac Troponin I vs a Clinical Chemistry Score for Predicting All-Cause Mortality in an Emergency Department Population
Bibliographic record
Abstract
BackgroundFor patients investigated for suspected acute coronary syndrome, there is uncertainty if a single measurement of high-sensitivity cardiac troponin I (hs-cTnI) at emergency department (ED) presentation can identify patients at both low and high risk for mortality.MethodsWe included consecutive adult patients in the ED who had a Clinical Chemistry Score (CCS) taken at presentation (ie, combination of glucose, creatinine for estimated glomerular filtration rate determination, and hs-cTnI assay) in a Canadian city between 2012 and 2013. Outcomes were 3-month, 1-year, and 5-year all-cause mortality using the provincial death registry. Mortality rates and test performance (eg, sensitivity and specificity) with 95% confidence intervals (CIs) were obtained for the CCS or hs-cTnI assay alone using established cutoffs for these tests.ResultsOur cohort included 5974 patients with a 1-year mortality rate of 17.2% (95% CI, 16.2-18.3). A CCS ≥ 1 yielded a sensitivity of 99.2% (95% CI, 98.4-99.6) compared with the hs-cTnI ≥ 5 ng/L cutoff sensitivity of 88.4% (95% CI, 86.3-90.3), with the mortality rate being significantly lower for patients with CCS < 1 (2.0%; 95% CI, 0.9-4.0) vs patients with hs-cTnI < 5 ng/L (5.0%; 95% CI, 4.2-6.0) at 1 year (P = 0.01). A CCS of 5 also yielded a higher specificity (88.5%; 95% CI, 87.5-89.3) compared with hs-cTnI > 26 ng/L (83.9%; 95% CI, 82.9-84.9), with no difference in mortality rates (37.4% vs 36.3%; P = 0.66). This trend was consistent at 3-month and 5-year mortality.ConclusionFor patients in the ED with a potential cardiac issue, using the CCS cutoffs can better identify patients at low and high risk for mortality than using published cutoffs for hs-cTnI alone.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".