HIGH-SENSITIVITY TROPONIN FOR CARDIOVASCULAR RISK STRATIFICATION IN ASYMPTOMATIC INDIVIDUALS WITH SUBCLINICAL ATHEROSCLEROSIS: INSIGHTS INTO SEX-SPECIFIC DIFFERENCES AND EMERGING CLINICAL APPLICATIONS: A META-ANALYSIS WITH CRUCIAL IMPLICATIONS FOR CARDIOVASCULAR RISK ASSESSMENT
Bibliographic record
Abstract
Background: Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, placing a significant burden on healthcare systems. The emergence of high-sensitivity cardiac troponin (hs-Tn), a biomarker for myocardial injury, offers new potential in improving cardiovascular risk prediction, particularly in asymptomatic individuals with subclinical atherosclerosis. This advancement addresses critical gaps in traditional risk stratification models and promotes early detection and intervention. Objective: This meta-analysis aimed to evaluate the role of hs-Tn in cardiovascular risk stratification for asymptomatic individuals with subclinical atherosclerosis, with a focus on sex-specific differences and the integration of hs-Tn with traditional and imaging-based risk models. Methods: A meta-analysis of nine studies, including randomized controlled trials, cohort studies, and observational studies, was conducted following PRISMA guidelines. The search spanned multiple databases from January 2010 to November 2024. Extracted data included population characteristics, hs-Tn assay types, subclinical atherosclerosis measures, follow-up durations, and outcomes. Statistical metrics such as odds ratios (OR), confidence intervals (CI), and p-values were analyzed to assess the associations. Study quality was evaluated using the Newcastle-Ottawa Scale and ROB-2 tools. Results: Elevated hs-Tn levels were associated with increased cardiovascular risk, with odds ratios ranging from 1.25 to 2.10 (p < 0.01). Sex-specific analyses indicated that males exhibited higher hs-Tn thresholds than females for equivalent risk levels. Combining hs-Tn with traditional models enhanced predictive accuracy by 18% and further improved when paired with imaging techniques such as coronary artery calcium scoring. Most studies demonstrated a low risk of bias, ensuring reliability. Conclusion: High-sensitivity cardiac troponin significantly enhances cardiovascular risk stratification in asymptomatic individuals. Incorporating sex-specific thresholds and integrating hs-Tn with traditional and imaging-based models could revolutionize early detection and prevention strategies, offering a transformative approach to cardiovascular care.
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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 | 0.050 | 0.062 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.080 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".