Long-Term Impact of Subclinical Hypothyroidism on Cardiovascular Outcomes in Adults: A Meta-Analysis of Cohort and Observational Studies
Bibliographic record
Abstract
Background: Subclinical hypothyroidism (SCH), defined by elevated thyroid-stimulating hormone (TSH) levels with normal free thyroxine (FT4), has been increasingly linked to cardiovascular disease. However, evidence remains mixed regarding its long-term impact on coronary outcomes. Objective: To evaluate the association between subclinical hypothyroidism and the risk of coronary heart disease (CHD) events, cardiovascular mortality, and all-cause mortality in adults using data from cohort and observational studies. Methods: A systematic search was conducted across PubMed, Scopus, Embase, and Web of Science from 2015 to 2024. Eligible studies included prospective cohorts reporting cardiovascular outcomes in adults with SCH versus euthyroid controls. Pooled hazard ratios (HRs) and relative risks (RRs) were calculated using a random-effects model. Subgroup analysis was conducted based on TSH levels (<10 mIU/L vs. ≥10 mIU/L). Study quality was assessed using the Newcastle-Ottawa Scale (NOS). Results: Three high-quality cohort studies involving 60,047 participants were included. SCH was significantly associated with an increased risk of CHD events (HR/RR = 1.20; 95% CI: 1.02–1.41; p = 0.03). The association with CHD mortality (HR/RR = 1.18; 95% CI: 0.97–1.43) and total mortality (HR/RR = 1.12; 95% CI: 0.99–1.26) was not statistically significant. Subgroup analysis revealed that individuals with TSH ≥10 mIU/L had a markedly increased CHD risk (HR/RR = 1.89; 95% CI: 1.28–2.80; p = 0.002). Conclusion: Subclinical hypothyroidism, particularly at higher TSH levels (≥10 mIU/L), is associated with an increased risk of coronary heart disease events. While associations with mortality were non-significant, the observed trends highlight the need for closer monitoring and targeted intervention strategies in patients with elevated TSH. Further large-scale studies are warranted to establish causality and optimize clinical management.
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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 | 0.020 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.043 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".