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Published on: February 17, 2023
Analysis of independent risk factors and construction of a predictive model for thyroid dysfunction in early
Yiliminuer Keremu1, Xiaolu Yu1, Gang Zhao2
1Department of Medical Laboratory Center, Tumor Hospital Affiliated to Xinjiang Medical University, Xinjiang Key Laboratory of Molecular Biology for Endemic Diseases, Urumqi, Xinjiang, China.
Introduction:
Thyroid dysfunction during early pregnancy significantly impacts maternal and fetal health, with risks including preeclampsia, preterm birth, and developmental abnormalities. This study aims to identify independent risk factors and develop a predictive model to enable early diagnosis and intervention, improving pregnancy outcomes through tailored clinical management strategies.
Methods:
We retrospectively analyzed the general information and relevant laboratory indicators of 2151 women in early pregnancy admitted to three Xinjiang hospitals from April 2021 to November 2024. The patients were divided into a normal thyroid function group (n=1490) and a thyroid dysfunction group (n=661). The test results were analyzed to screen for independent risk factors and constructed a predictive model.
Results:
Key findings revealed a 30.73% thyroid dysfunction incidence, including subclinical hypothyroidism (76.40%), hypothyroidism (12.86%), hyperthyroidism (6.35%), and subclinical hyperthyroidism (4.39%). Regional reference ranges were established as TSH (0.22-2.40) mIU/L and FT4 (13.54-20.26) pmol/L. Univariate analysis identified significant differences in A-TPO, A-TG, TSH, and FT3 (P < 0.05). Multivariate analysis confirmed A-TPO, TSH and FT3 as independent risk factors. The prediction model demonstrated excellent performance with an AUC of 0.911 (95% CI: 0.891-0.932), 0.874 sensitivity, and 0.955 specificity.
Conclusion:
The study demonstrated that A-TPO, TSH and FT3 were independent risk factors for thyroid dysfunction in women during early pregnancy. A predictive model was constructed based on these three indicators. Validation of the model's performance indicates that it has good predictive capabilities.
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