Dose–response association of acute‐phase quetiapine treatment with risk of new‐onset hypothyroidism in schizophrenia patients
Bibliographic record
Abstract
AIMS: To assess association between quetiapine treatment and risk of new-onset hypothyroidism in schizophrenia patients. METHODS: We conducted a retrospective cohort study in a tertiary hospital in China between January 2016 and December 2018. Schizophrenia patients with normal thyroid tests at admission were included. Hypothyroidism, which was defined as thyroid-stimulating hormone >4.20 mU/L and free thyroxine <12.00 pmol/L, or on L-thyroxine prescriptions, was the outcome measure, and quetiapine treatment between admission and subsequent thyroid test was the exposure measure of this study. Adjusted relative risks and 95% confidence intervals were used to assess the independent association of quetiapine treatment with risk of new-onset hypothyroidism. The dose-response association was further analysed by 3 quetiapine doses: low (≤<=0.2 g/d), medium (0.2-0.6 g/d), and high (>0.6 g/d). RESULTS: A total of 2022 eligible patients were included in the final analysis. Sixty patients (15.0%) in the quetiapine group developed hypothyroidism, while 56 patients (3.5%) in the nonquetiapine group developed hypothyroidism. Relative risk (95% confidence interval) of developing hypothyroidism for quetiapine use was 4.01 (2.86-5.64) after adjusting for several potential confounding factors. A strong dose-response association between quetiapine use and risk of developing hypothyroidism was observed: adjusted relative risks (95% confidence intervals) were 1.00 (0.25-2.59), 4.22 (2.80-6.25) and 5.62 (3.66-8.38), respectively, for low-, medium- and high-dose quetiapine, as compared with no quetiapine. CONCLUSION: Acute phase quetiapine treatment for schizophrenia patients was strongly associated with increased risk of developing new-onset hypothyroidism, with a clear dose-response association.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".