Levothyroxine Treatment of Subclinical Hypothyroidism and the Risk of Adverse Cardiovascular Events
Bibliographic record
Abstract
Importance: There is uncertainty as to whether treatment of subclinical hypothyroidism (SCH) is associated with cardiovascular outcomes. Objectives: To determine whether levothyroxine replacement therapy decreases the risk of major adverse cardiovascular events (MACE) among individuals with SCH defined as having a thyrotropin (TSH) level between 5 and 10 mU/L. Design: We conducted a population-based cohort study using a prevalent new-user design. Setting: The study utilized data from the United Kingdom Clinical Practice Research Datalink. Participants: We identified a base cohort of individuals aged ≥18 years with incident SCH defined as having at least two TSH levels between 5 and 10 mU/L within one year between 1998 and 2018. We matched 76,946 levothyroxine treated to 76,946 untreated individuals based on age, sex, calendar time, duration of SCH, and time-conditional propensity score. We compared individuals with SCH treated with levothyroxine with individuals with no treatment. Exposure: Levothyroxine treatment versus no treatment. Main Outcome Measures: The primary outcome, MACE, was defined as a composite of nonfatal myocardial infarction, nonfatal ischemic stroke, and cardiovascular-related mortality. Results: The mean age of the study cohort was 62.8 years, and 76.5% were women. During a median follow-up time of 1.6 years (interquartile range: 0.5–4.2), the incidence rate for MACE among individuals treated with levothyroxine was 12.8 per 1000 person-years; confidence interval (CI): 12.2–13.3 and 13.9 per 1000 person-years; CI: 13.4–14.3 among nontreated individuals. Levothyroxine treatment was associated with a small decreased risk of MACE (hazard ratio: 0.88; CI: 0.83–0.93). Conclusions: Levothyroxine treatment of SCH was associated with a small decreased risk of MACE. However, given the observational nature of the study, residual confounding should be considered in the interpretation of this finding.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".