6418 Treatment of Subclinical Hyperthyroidism and Incident Atrial Fibrillation
Bibliographic record
Abstract
Abstract Disclosure: M. Jay: None. P. Huan: None. N. Cliffe: None. J. Rakoff: None. E. Morris: None. P. Kavsak: Advisory Board Member; Self; Roche Diagnostics, QuidelOrtho, Siemens. Consulting Fee; Self; QuidelOrtho, Roche Diagnostics. Grant Recipient; Self; QuidelOrtho. Speaker; Self; Abbott Laboratories. Other; Self; Siemens(Other Research Support (includes receipt of drugs, supplies, equipment or other in-kind support), Speaker/Honoraria)). M. Luthra: Advisory Board Member; Self; Bayer, Inc., Novonordisk. Consulting Fee; Self; Bayer, Inc., Novonordisk. Speaker; Self; Lilly/BI alliance, Novonordisk, Sanofi. Z. Punthakee: None. Background: Treating overt hyperthyroidism prevents atrial fibrillation (AF). Though subclinical hyperthyroidism (SH) has been associated with AF risk, it is unknown whether treating SH prevents AF. Objective: We aimed to identify the association between treating SH and incident AF in outpatients. Methods: In a retrospective chart review, 2169 patients ≥ 18 years, diagnosed with SH between 2000-2021 were identified using the regional biochemistry database. After excluding those with prior AF, hypothyroidism, thyroid cancer, pituitary disease, and pregnancy, 360 patients categorized as treated (n=131) or untreated (n=229) were analyzed. The primary outcome was incident AF. Incidence rates were compared between the two groups over the time since SH treatment start for the treated group, and time since diagnosis of SH for the untreated group. Pharmacoepidemiologic Cox analysis adjusted for age and hypertension, with treatment as a time dependent covariate was used to account for untreated time in the treated group. Secondary outcomes were AF prevalence, P wave duration on ECG, as well as ventricular and ascending aorta diameters on echocardiogram. We included sensitivity and subgroup analyses. Results: Mean age of patients with SH was 55.19 years, 78% were female, 43% had toxic nodules and 14% had Grave’s disease. Amongst the 19 patients who developed AF, 58% had toxic nodules and no patient had Grave’s disease. In the treated and untreated groups, AF occurred in 3.1% and 6.6% (p=0.15) and AF incidence was 0.8 and 1.4 %/year (p=0.31), respectively. The hazard ratio (HR) was 0.60 (95% CI 0.19-1.92; p=0.39). In the subgroup of patients with free T4 (FT4) ≥ 15 pmol/L, AF incidence was 0.5 and 3.0 %/yr in the treated and untreated groups, respectively (p=0.01), while adjusted HR was 0.185 (95% CI 0.022-1.59, p=0.12). In those with TSH ≤ 0.1 mU/L, treatment was not associated with AF incidence. As some cases of AF were documented nearly simultaneously with treatment of SH, a sensitivity analysis was performed reassigning 2 patients diagnosed with AF <30 days after starting SH treatment to the untreated group. Here, in the treated and untreated groups, AF occurred in 1.6% and 7.4% (p=0.02), and AF incidence was 0.4 and 1.8 %/year (p=0.02), respectively. The HR was 0.25 (0.06-1.13; p=0.07). In the treated versus untreated groups, the mean p wave duration, ventricular diameter, and ascending aorta diameter were 73.47 vs 73.42 ms (p=0.99), 4.29 vs 4.34 cm (p=0.86), and 3.33 vs 3.23 cm (p=0.58), respectively. Conclusions: We report the first study assessing the effect of treating SH in preventing incident AF. There was an overall trend towards lower AF following treatment of SH. Lack of statistical significance may be related to small sample size, supporting the need for larger scale studies. These data suggest the etiology of SH (toxic nodules) and FT4 levels could be factored into treatment decisions. Presentation: 6/2/2024
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".