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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".