Increased level of high-sensitivity cardiac Troponin T in a geriatric population is determined by comorbidities compared to age
Bibliographic record
Abstract
High level of cardiac Troponin T (hs-cTnT) in geriatric population has been considered as an age-related phenomenon, which may question the interpretation of the increase of hs-cTnT in this population. The challenge is what is the primary cause of the increased hs-cTnT levels in elderly patients without AMI. Objective The aim of the current study was to determine the impact of aging on hs-cTnT levels in elderly patients without acute cardiac events but in the presence of comorbidities. Methods Sociodemographic and clinical data were collected from 6977 medical records of patients aged ≥65 years without acute coronary events but for whom hs-cTnT measurements were available. The patients were stratified based on age, troponin levels and the number of comorbidities. Results The results suggested that the likelihood of increased hs-cTnT was related to the presence of comorbidities independently of their number (p < 0.05). The adjusted odds ratio (AOR) for both advanced age and having comorbidity was statistically significant, however for the old group (74 ≥ age ≥ 84 years) the chance of having elevated troponin regarding age compared to the presence of comorbidity was 1.070 vs. 1.216, whereas for the old-old group (≥85 years) it was found to be 1.071 vs. 1.311. Besides statistical significance for age, from a clinical standpoint, the AOR of 1.070 may not be considered clinically relevant. Conclusion Increased hs-cTnT levels were associated with the presence of pre-existing comorbidities independently of age. Increased hs-cTnT levels in the elderly should always be considered as pathological, and a specific etiology should be searched.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 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".