Oxcarbazepine was associated with risks of newly developed hypothyroxinaemia and impaired central set point of thyroid homeostasis in schizophrenia patients
Bibliographic record
Abstract
AIMS: Hypothyroxinaemia might be easily ignored, because attention is typically paid to individuals with elevated thyroid stimulating hormone (TSH). In this study, we aimed to evaluate the association of oxcarbazepine use as adjuvant for treatment of schizophrenia with hypothyroxinaemia and central set point of thyroid homeostasis. METHODS: This retrospective cohort study was conducted in the Second Affiliated Hospital of Xinxiang Medical University. Inpatients with a diagnosis of schizophrenia admitted between January 2016 and October 2019 with normal thyroid function at admission were included. Oxcarbazepine use was the exposure measure. Newly developed hypothyroxinaemia was the primary outcome measure and parameters of thyroid homeostasis central set point as measured by TSH index and thyroid feedback quantile-based index (TFQI) were the secondary outcome measures. RESULTS: In total, 1207 eligible patients were included. The occurrence of hypothyroxinaemia in patients who received oxcarbazepine was higher (35/107, 32.7%) than in those patients who did not (152/1099, 13.8%), with adjusted relative risk of 2.24 and 95% confidence interval of 1.57 and 3.17. Oxcarbazepine use was associated with greater reduction in TSH index (adjusted β -0.33 and 95% confidence interval -0.48, -0.19) and TFQI (adjusted β -0.24 and 95% confidence interval -0.31, -0.16). CONCLUSION: Oxcarbazepine use was independently associated with increased risk of developing hypothyroxinaemia, and greater reduction in TSH index and TFQI, suggesting that impaired central set point of thyroid homeostasis might be involved in the mechanism of oxcarbazepine-induced hypothyroxinaemia.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".