Cardiovascular and bone health outcomes in older people with subclinical hypothyroidism treated with levothyroxine: a systematic review and meta-analysis
Bibliographic record
Abstract
Problem: Thyroid dysfunction is common in older people, with females at higher risk. Evidence suggests that thyroid stimulating hormone (TSH) naturally increases with age. Subclinical hypothyroidism (SCH) is diagnosed when serum thyroid-stimulating hormone levels are mildly elevated while free thyroxine levels are within normal range. With uniform TSH reference ranges across the adult lifespan, a diagnosis of SCH is more likely with increasing age. Patients with SCH are often prescribed levothyroxine. This review investigates the cardiovascular and bone health impacts of levothyroxine in patients over 50 years old with a baseline diagnosis of SCH. Approach: Systematic review and meta-analysis. An advanced search function was performed across the Cochrane, Embase, Medline, PubMed, and Web of Science databases to collate previous studies that evaluated cardiovascular and bone health outcomes in SCH patients with and without levothyroxine, from inception until the 3rd of August 2023. The remaining studies were assessed using the Cochrane Risk of Bias tool for randomised controlled trials and the Newcastle-Ottawa quality of assessment for observational studies. The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) tool was then used to assess the overall quality of each study. The results where then pooled by their odds ratios, using R-programming. Findings: Seven studies that recruited 5,887 participants, ranging from 45.4 to 80.1 years of age were selected. Six studies for cardiovascular outcomes were pooled for meta-analysis, there was no association between levothyroxine and cardiovascular outcomes in the SCH patients aged over 65 years [pooled OR 0.99; 95% confidence interval (0.74-1.11)]. The results also showed no association between levothyroxine use and bone health outcomes for SCH patients aged over 65 years [pooled OR 0.99; 95% confidence interval (0.52-1.88)]. No heterogeneity was found between the 6 cardiovascular and the 3 bone health outcome articles (I2 =0%). Consequences: We found no association between levothyroxine use and cardiovascular and bone health outcomes in SCH participants over 65 years, indicating that more studies are needed on levothyroxine and its implications on cardiovascular and bone health outcomes in the older population.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".