Background Type 1 diabetes mellitus is a heterogeneous autoimmune disease with diverse characteristics between ethnicities and ages.Understanding this heterogeneity is essential for optimizing management and developin...Background Type 1 diabetes mellitus is a heterogeneous autoimmune disease with diverse characteristics between ethnicities and ages.Understanding this heterogeneity is essential for optimizing management and developing precision treatments.This study investigates the clinical,metabolic and immunological heterogeneity of type 1 diabetes mellitus in children across different ages of onset.Methods A retrospective analysis of 401 children newly diagnosed with type 1 diabetes mellitus at a single center from January 2009 to August 2024 was conducted.We compared the clinical characteristics of our cohort with others from different countries.Patients were categorized into three age groups:6 months-5 years,5-10 years and≥10 years at diagnosis.Clinical,metabolic,and immunological features were compared among groups.Results The median cohort age was 8.58 years;48.9%were male.Diabetic ketoacidosis occurred in 56.1%of patients,higher than in the Finnish and American cohorts.Most clinical characteristics are not significantly different among age groups.The 6 months-5 years group had a lower area under the curve(AUC)for C-peptide compared to the other age groups.The≥10 years group was more likely to be thyroid antibody positive and have vitamin D deficiency.Immunologically,type 1 diabetes mellitus patients showed significantly increased counts of T lymphocytes,CD3+CD8+T cells and B lymphocytes,along with decreased interleukin-2 and increased interleukin-6 levels compared to healthy controls.Of note,the 6 months-5 years group had a higher CD4/CD8 ratio,which was negatively correlated with C-peptide AUC.Conclusions Significant heterogeneity in type 1 diabetes mellitus features exists across age groups.Early-onset patients showed poorer islet function and late-onset patients were more prone to metabolic complications.Collectively our study emphasizes the need for age-specific management strategies.展开更多
Background Accurate final height prediction for girls with menarche is important,yet traditional Greulich-Pyle(GP)and Bayley-Pinneau predictions based on left hand-wrist bone age(BA)and target height demonstrate limit...Background Accurate final height prediction for girls with menarche is important,yet traditional Greulich-Pyle(GP)and Bayley-Pinneau predictions based on left hand-wrist bone age(BA)and target height demonstrate limited accuracy.This study aims to develop a method to more accurately predict final height.Methods One hundred and seventy-three girls with menarche from August 2018 to June 2023 were analyzed retrospectively.BAs in Greulich and Pyle and Hoerr knee atlases were evaluated.Knee radiomic features were extracted using PyRadiomics;least absolute shrinkage and selection operator regression was utilized to develop radiomic scores of the distal femur and proximal tibia.Ordinary least squares regression with stepwise selection was used to build a multilinear equation.This was further compared with traditional methods in fivefold cross-validation(CV=5)using residual distribution and Bland-Altman agreement analysis.Results Height gain in our Chinese cohort after menarche was 8.94±2.99 cm.A stepwise multilinear equation was built with height at menarche,BA of GP and radiomic score of the distal femur(R^(2)=0.733,F statistic=115.1,P<0.05).Compared with traditional methods,a multilinear equation displayed the lowest residuals(residual range:-5.677 cm to+6.444 cm)and best Bland-Altman agreement(the mean difference:-0.01 cm,95%limits of agreement:-3.96 to+3.93 cm).Conclusions A robust linear regression model that incorporates knee radiomic scores,BA of GP,height at menarche,and father’s height demonstrated the best final height prediction in our cohort.This research is an innovative application of radiomic score of the distal femur to final height prediction.Further validation is warranted to test robustness across populations and scenarios.展开更多
基金supported by the National Nature Science Foundation of China(82170910)the 2024 National Clinical Key Specialty Construction Project(No.10000015Z155080000004)+1 种基金the Special Fund for People's Livelihood Scientific Research of Public Institutions under the Science and Technology Development Fund of Pudong New Area(PKJ2025-Y03)the Clinical Youth Cadre Hospital Fund of Shanghai Children's Medical Center(QN-SCMC2023-5)。
文摘Background Type 1 diabetes mellitus is a heterogeneous autoimmune disease with diverse characteristics between ethnicities and ages.Understanding this heterogeneity is essential for optimizing management and developing precision treatments.This study investigates the clinical,metabolic and immunological heterogeneity of type 1 diabetes mellitus in children across different ages of onset.Methods A retrospective analysis of 401 children newly diagnosed with type 1 diabetes mellitus at a single center from January 2009 to August 2024 was conducted.We compared the clinical characteristics of our cohort with others from different countries.Patients were categorized into three age groups:6 months-5 years,5-10 years and≥10 years at diagnosis.Clinical,metabolic,and immunological features were compared among groups.Results The median cohort age was 8.58 years;48.9%were male.Diabetic ketoacidosis occurred in 56.1%of patients,higher than in the Finnish and American cohorts.Most clinical characteristics are not significantly different among age groups.The 6 months-5 years group had a lower area under the curve(AUC)for C-peptide compared to the other age groups.The≥10 years group was more likely to be thyroid antibody positive and have vitamin D deficiency.Immunologically,type 1 diabetes mellitus patients showed significantly increased counts of T lymphocytes,CD3+CD8+T cells and B lymphocytes,along with decreased interleukin-2 and increased interleukin-6 levels compared to healthy controls.Of note,the 6 months-5 years group had a higher CD4/CD8 ratio,which was negatively correlated with C-peptide AUC.Conclusions Significant heterogeneity in type 1 diabetes mellitus features exists across age groups.Early-onset patients showed poorer islet function and late-onset patients were more prone to metabolic complications.Collectively our study emphasizes the need for age-specific management strategies.
基金supported by the Shanghai Oriental Talents Program-Youth Project(QNWS2024011)the Fundamental Research Funds for the Central Universities(YG2023QNA35).
文摘Background Accurate final height prediction for girls with menarche is important,yet traditional Greulich-Pyle(GP)and Bayley-Pinneau predictions based on left hand-wrist bone age(BA)and target height demonstrate limited accuracy.This study aims to develop a method to more accurately predict final height.Methods One hundred and seventy-three girls with menarche from August 2018 to June 2023 were analyzed retrospectively.BAs in Greulich and Pyle and Hoerr knee atlases were evaluated.Knee radiomic features were extracted using PyRadiomics;least absolute shrinkage and selection operator regression was utilized to develop radiomic scores of the distal femur and proximal tibia.Ordinary least squares regression with stepwise selection was used to build a multilinear equation.This was further compared with traditional methods in fivefold cross-validation(CV=5)using residual distribution and Bland-Altman agreement analysis.Results Height gain in our Chinese cohort after menarche was 8.94±2.99 cm.A stepwise multilinear equation was built with height at menarche,BA of GP and radiomic score of the distal femur(R^(2)=0.733,F statistic=115.1,P<0.05).Compared with traditional methods,a multilinear equation displayed the lowest residuals(residual range:-5.677 cm to+6.444 cm)and best Bland-Altman agreement(the mean difference:-0.01 cm,95%limits of agreement:-3.96 to+3.93 cm).Conclusions A robust linear regression model that incorporates knee radiomic scores,BA of GP,height at menarche,and father’s height demonstrated the best final height prediction in our cohort.This research is an innovative application of radiomic score of the distal femur to final height prediction.Further validation is warranted to test robustness across populations and scenarios.
