Increased Risk of Primary Sjögren's Syndrome in Female Patients with Thyroid Disorders: A Longitudinal Population-Based Study in Taiwan
Bibliographic record
Abstract
BACKGROUND: A number of reports have indicated an association between thyroid diseases and primary Sjögren's syndrome (pSS). However, fewer studies have investigated whether the presence of thyroid diseases is associated with increased risk of developing pSS. Thus, the aim of our study was to use a nationwide health claims database to explore the prevalence and risk of pSS in female patients with thyroid diseases. METHODS: From the Registry of Catastrophic Illness database in the National Health Insurance Research Database in Taiwan, we identified 389 female patients with a diagnosis of pSS from 2005 to 2010. We also obtained 1945 control subjects frequency-matched on sex, 10-year age interval, and year of index date from the Longitudinal Health Insurance Database (LHID2000). Both groups were retrospectively traced back to a period of eight years to obtain diagnosis of thyroid diseases prior to index date. RESULTS: A significantly higher risk of pSS was associated with the presence of thyroid diseases (adjusted odds ratio (AOR) = 2.1, 95% confidence interval (CI) = 1.6-2.9). Among the sub-categories of thyroid diseases, patients with thyroiditis (AOR = 3.6, 95% CI = 1.7-7.5), thyrotoxicosis (AOR = 2.5, 95% CI = 1.6-3.8), and unspecified hypothyroidism (AOR = 2.4, 95% CI = 1.2-4.6), and simple and unspecified goiter (AOR = 2.0, 95% CI = 1.3-3.3) were significantly associated with increased risk of pSS. The associations were generally stronger in the mid-forties to mid-sixties age group, except in patients with unspecified hypothyroidism. CONCLUSIONS: The risk of pSS was significantly increased in female patients with thyroid diseases, particularly those in their mid-forties to mid-sixties. An increased awareness of the possibility of pSS in perimenopausal females with thyroid diseases is important to preserve their quality of life and to avoid comorbidity.
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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) | 0.000 | 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 | 0.000 |
| 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".