Prognostic use of cardiac troponin T and troponin I in patients with heart failure.
Bibliographic record
Abstract
BACKGROUND: Troponin T (cTnT) and troponin I (cTnI) are present in the sera of some heart failure (HF) patients and have potential importance as prognostic markers. OBJECTIVE: To prospectively evaluate the prognostic value of cTnT and cTnI in well-characterized HF patients and clarify their relationship to other clinical markers of HF severity. METHODS: cTnT and cTnI were measured in 78 HF patients (45 inpatients, 33 outpatients) who were followed up prospectively for 12 months. RESULTS: Plasma cTnT (> or =0.02 ng/mL) and cTnI (> or =0.3 ng/mL) were detected in 51% and 46% of patients, respectively. These patients were more likely to be inpatients (70% versus 45% for cTnT, 75% versus 43% for cTnI, P<0.05 for both), have a higher plasma creatinine (153 versus 119 micromol/L for cTnT; 157 versus 118 micromol/L for cTnI, P<0.05) and lower plasma sodium (134 versus 138 mmol/L for both, P<0.05). At 12 months, they were more likely to have died or undergone cardiac transplantation (41% versus 14%, P=0.01 for cTnT; 43% versus 15%, P=0.004 for cTnI). After adjustment for New York Heart Association class, plasma sodium and inpatient status, a significant association with events was still evident for both troponins. CONCLUSIONS: Both cTnT and cTnI are strongly associated with other clinical indicators of HF severity and remain independent predictors of prognosis after adjustment for these factors. These results indicate a potential role for cTnT and cTnI in the clinical management of HF 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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".