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This study is aimed at examining the impact of ChatGPT on pediatric endocrine and metabolic conditions, particularly in the areas of screening and diagnosis, in both Chinese and English modes. A 40-question questionnaire covering the four most common pediatric endocrine and metabolic conditions was posed to ChatGPT in both Chinese and English three times each. Six pediatric endocrinologists evaluated the responses. ChatGPT performed better when responding to questions in English, with an unreliable rate of 7.5% compared to 27.5% for Chinese questions, indicating a more consistent response pattern in English. Among the reliable questions, the answers were more comprehensive and satisfactory in the English mode. We also found disparities in ChatGPT's performance when interacting with different target groups and diseases, with improved performance for questions posed by clinicians in English and better performance for questions related to diabetes and overweight/obesity in Chinese for both clinicians and patients. Language comprehension, providing incomprehensive answers, and errors in key data were the main contributors to the low scores, according to reviewer feedback., Conclusion: Despite these limitations, as ChatGPT continues to evolve and expand its network, it has significant potential as a practical and effective tool for clinical diagnosis and treatment., What Is Known: • The deep learning-based large-language model ChatGPT holds great promise for improving clinical practice for both physicians and patients and has the potential to increase the speed and accuracy of disease screening and diagnosis, as well as enhance the overall efficiency of the medical process. However, the reliability and appropriateness of AI model responses in specific field remains unclear. • This study focused on the reliability and appropriateness of AI model responses to straightforward and fundamental questions related to the four most prevalent pediatric endocrine and metabolic disorders, for both healthcare providers and patients, in different language scenarios., What Is New: • The AI model performed better when responding to questions in English, with more consistent, as well as more comprehensive and satisfactory responses. In addition, we also found disparities in ChatGPT's performance when interacting with different target groups and different diseases. • Despite these limitations, as ChatGPT continues to evolve and expand its network, it has significant potential as a practical and effective tool for clinical diagnosis and treatment., (© 2024. The Author(s).)

Background: Kabuki syndrome (KS) is a monogenic disorder leading to special facial features, mental retardation, and multiple system malformations. Lysine demethylase 6A, (KDM6A, MIM*300128) is the pathogenic gene of Kabuki syndrome type 2 (KS2, MIM#300867), which accounts for only 5%-8% of KS. Previous studies suggested that female patients with KS2 may have a milder phenotype., Method: We summarized the phenotype and genotype of KS2 patients who were diagnosed in Shanghai Children's Medical Center since July 2017 and conducted a 1:3 matched case-control study according to age and sex to investigate sex-specific differences between patients with and without KS2., Results: There were 12 KS2 cases in this study, and 8 of them matched with 24 controls. The intelligence quotient (IQ) score of the case group was significantly lower than that of the control group (P < 0.001). In addition, both the incidence of intellectual disability (ID) (IQ < 70) and moderate-to-severe ID (IQ < 55) were significantly higher in the case group than those in the control group. No sex-specific difference was found in the incidence of ID or moderate-to-severe ID between the female cases and female controls, whereas there was a significant difference between male cases and male controls. Furthermore, the rate of moderate-to-severe ID and congenital heart disease (CHD) was significantly higher in the male group than that in the female group., Conclusions: Our results showed that a sex-specific difference was exhibited in the clinical phenotypes of KS2 patients. The incidence of CHD was higher in male patients, and mental retardation was significantly impaired. However, the female patients' phenotype was mild., (© 2024. The Author(s).)

Background: ABCC8 variants can cause hyperinsulinemia by activating or deactivating gene expression. This study used targeted exon sequencing to investigate genetic variants of ABCC8 and the associated phenotypic features in Chinese patients with hyperinsulinemic hypoglycemia (HH)., Methods: We enrolled eight Chinese children with HH and analyzed their clinical characteristics, laboratory results, and genetic variations., Results: The age at presentation among the patients ranged from neonates to 0.6 years old, and the age at diagnosis ranged from 1 month to 5 years, with an average of 1.3 ± 0.7 years. Among these patients, three presented with seizures, and five with hypoglycemia. One patient (Patient 7) also had microcephaly. All eight patients exhibited ABCC8 abnormalities, including six missense mutations (c. 2521 C > G, c. 3784G > A, c. 4478G > A, c. 4532T > C, c. 2669T > C, and c. 331G > A), two deletion-insertion mutations (c. 3126&#95;3129delinsTC and c. 3124&#95;3126delins13), and one splicing mutation (c. 1332 + 2T > C). Two of these mutations (c. 3126&#95;3129delinsTC and c. 4532T > C) are novel. Six variations were paternal, two were maternal, and one was de novo. Three patients responded to diazoxide and one patient responded to octreotide treatment. All there patients had diazoxide withdrawal with age. Two patients (patients 3 and 7) were unresponsive to both diazoxide and octreotide and had mental retardation., Conclusions: Gene analysis can aid in the classification, treatment, and prognosis of children with HH. In this study, the identification of seven known and two novel variants in the ABCC8 gene further enriched the variation spectrum of the gene., (© 2024. The Author(s).)