[Analysis of influencing factors and construction of a predictive model for permanent congenital hypothyroidism in neonates with congenital hypothyroidism].

Objective: To analyze the influencing factors and establish a predictive model for permanent congenital hypothyroidism (PCH) in neonates with congenital hypothyroidism (CH). Methods: A total of 682 neonates diagnosed with CH between January and December 2021 at the Third Affiliated Hospital of Zhengzhou University were retrospectively enrolled, including 370 males and 312 females, with the diagnostic age of (17.6±4.3) d. According to the type of CH, the patients were divided into the PCH group (n=212) and the transient CH (TCH) group (n=470). Differences in various indicators between the two groups were analyzed. Multivariate logistic regression analysis was used to identify the influencing factors of PCH, and a nomogram of the predictive model was constructed. The predictive efficacy, accuracy, and clinical applicability of the model were evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis, respectively. Results: The proportion of maternal thyroid disease history, levels of thyroid-stimulating hormone (TSH) at initial diagnosis, the rate of thyroid ectopia or agenesis, the proportion of pathogenic/likely pathogenic (P/LP) genetic variants, the proportion of biallelic DUOX2/DUOXA2 variants, and the proportion of TPO/TG gene variants were all higher in the PCH group than in the TCH group. In contrast, free thyroxine (FT4) at initial diagnosis, levothyroxine (L-T4) dosage at 1 year of age, and the proportion of normal or enlarged thyroid size were lower in the PCH group than in the TCH group(all P<0.05). Multivariate logistic regression analysis showed that increased birth weight (OR=0.96, 95%CI: 0.92-0.99), greater gestational age (OR=0.90, 95%CI: 0.79-0.98), and higher FT4 at initial diagnosis (OR=0.79, 95%CI: 0.73-0.86) were protective factors for PCH. Conversely, maternal history of thyroid disease (OR=2.14, 95%CI: 1.52-3.81), elevated TSH at initial diagnosis (OR=1.12, 95%CI: 1.08-1.17), higher L-T4 dosage at 1 year of age (OR=1.94, 95%CI: 1.45-2.06), abnormal thyroid imaging (OR=6.83, 95%CI: 3.92-11.91), and P/LP genetic variants (OR=2.87, 95%CI: 1.63-5.06) were risk factors for PCH. Five variables (initial TSH, initial FT4, L-T4 dosage at 1 year of age, thyroid imaging characteristics, and P/LP gene variants) were selected to construct a nomogram prediction model for PCH risk. The AUC of the model for predicting PCH in CH neonates was 0.88(95%CI: 0.85-0.91), with a sensitivity of 84.0% and a specificity of 80.0%. The calibration curve indicated good calibration of the model, and decision curve analysis showed that the model achieved satisfactory net clinical benefit within the threshold probability range of 0.1-0.7. Conclusions: Higher TSH level at initial diagnosis, lower FT4 level at initial diagnosis, higher L-T4 dosage at 1 year of age, abnormal thyroid imaging, and pathogenic/likely pathogenic (P/LP) genetic variants are factors associated with the prediction of PCH. The nomogram established in this study shows favorable predictive performance and clinical applicability.