Elevated Cardiac Troponin Levels in Geriatric Patients Without ACS: Role of Comorbidities
Bibliographic record
Abstract
Background Elevated levels of cardiac troponin T as measured by a high-sensitivity test (hscTnT) are common in geriatric patients with a large spectrum of comorbidities but without acute coronary syndrome (ACS). However, the relative contribution of individual comorbidities has never been clearly addressed. This study aimed to determine the relationship between hscTnT elevation as a response variable and individual comorbidities, and to estimate the impact of individual comorbidities on hscTnT elevation in geriatric patients free of ACS. Methods A nonexperimental, retrospective, matched, longitudinal cohort study was designed to evaluate the files of 7062 geriatric patients (aged ≥ 65 years) without ACS. The hscTnT levels of the patients have already been measured in all evaluated medical records. The dataset was split into 2 groups (0 and 1) based on the individual comorbidity (0 and 1) and hscTnT levels (≤ 14 ng/L = 0 and > 14 ng/L = 1). Results Our results show that although age was positively and significantly correlated with hscTnT (r = 0.17, P < 0.0001), the likelihood of experiencing elevated hscTnT levels in older individuals after having excluded ACS was related to the presence of comorbidities independently of their number ( P < 0.0001). The regression coefficients (β) associated with renal insufficiency (0.71), cardiomyopathy (0.63), chronic obstructive pulmonary disease (0.30), diabetes (0.25), and anemia (0.22) indicated that there exists a significant association between these comorbidities and the elevated hscTnT levels ( P < 0.001). The receiver operating characteristic curve for predictive modeling was estimated at 71% ( P < 0.0001). Conclusions Elevated hscTnT levels were mostly associated with renal insufficiency, cardiac myopathies, chronic obstructive pulmonary disease, diabetes, and anemia in geriatric patients without ACS. Developing guidelines to accurately evaluate hscTnT elevation in geriatric patients with comorbidities, without ACS, is clinically essential.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".