OBJECTIVE: To elucidate the epidemiological characteristics and genetic variant profile of Short-chain acyl-CoA dehydrogenase deficiency (SCADD) among newborns from Hainan Province and evaluate its significance within the local neonatal disease screening panel. METHODS: A total of 84 184 newborns born in Hainan Province from February to December 2024 were included. Tandem mass spectrometry (MS/MS) was employed to detect butyrylcarnitine (C4) and propionylcarnitine (C3) levels in dried blood spots. Screening thresholds were set at C4 > 0.43 μ mol/L and C4/C3 ratio > 0.28. Suspected cases underwent confirmatory testing via urinary ethylmalonic acid analysis by gas chromatography-mass spectrometry and whole-exome sequencing for ACADS gene variants. This study was approved by the Medial Ethics Committee of the hospital (Ethics No.: HNWCMC-2024-55). RESULTS: Six SCADD cases (male-to-female ratio = 1:1) were diagnosed, with all carrying compound heterozygous variants at two loci, yielding a prevalence of 7.13 per 100,000 live births. Four known ACADS gene variants were identified, with both c.322G>A and c.625G>A detected at a frequency of 41.7%. Regular follow-up (as of January 2026) revealed that all diagnosed cases have remained asymptomatic with normal growth and development. CONCLUSION The prevalence of SCADD among newborns in Hainan Province is relatively high, with c.322G>A and c.625G>A as the hotspot variants in the region. Given the absence of clinical phenotypes in all screen-detected cases during long-term follow-up, it is recommended to remove this condition from the routine neonatal screening program for this region to reduce unnecessary anxiety and medical cost.
Humans ; Infant, Newborn ; Neonatal Screening/methods* ; Female ; Male ; Lipid Metabolism, Inborn Errors/epidemiology* ; Acyl-CoA Dehydrogenase/genetics* ; China/epidemiology* ; Follow-Up Studies

OBJECTIVE

To describe in detail the research agenda-setting process of the Department of Health National Specialty Center for Eye Care with the guidance of the National Institute of Health (NIH) - Department of Clinical Epidemiology.

A research agenda technical working group (TWG) was organized to spearhead the research agenda setting, in collaboration and guidance of the NIH. After identifying relevant internal and external stakeholders, the TWG drafted a contextual map that served as an overarching framework. Research topics were obtained from the stakeholders and the TWG collated, reviewed and summarized prior to ranking them systematically. Each topic was prioritized through a weighted ranking system evaluating its feasibility, public health benefit, and resource/cost requirements. A final en banc session including the stakeholders was held to formalize the approval of the research agenda. An infographic was developed to serve as a visual guide for consultants and trainees in initiating research.

The TWG tallied 85 unique research topics from both the internal and external stakeholders. These topics encompassed a broad range of areas, including epidemiology, surgical, and medical management, health systems research, economic evaluations of interventions, and occupational/environmental factors.

The 2024-2027 research agenda of the Department of Health National Specialty Center for Eye Care was crafted, with the guidance of the NIH Department of Clinical Epidemiology. The goal was to improve the center's research output by aligning it with stakeholders thereby serving as a research benchmarking tool for the local ophthalmology community

OBJECTIVES: This study investigates independent risk factors for postoperative internal fixation device infection in patients with maxillofacial fractures and proposes an early warning model based on the synthetic minority over-sampling technique (SMOTE) algorithm. METHODS: A total of 1 104 patients who underwent surgical treatment for maxillofacial fractures at Oral and Maxillofacial Surgery Department, Affiliated Hospital of Nantong University from January 2021 to December 2024 were retrospectively analyzed. The patients were divided into two groups based on the presence of postoperative internal fixation device infection: the infection group (27 cases) and non-infection group (1 077 cases). Clinical data from both groups were collected and subjected to statistical analysis. Univariate and binary Logistic regression analysis were used to identify risk factors for postoperative internal fixation device infection in maxillofacial fractures. Subsequently, a Logistic regression model was established, and the dataset was improved based on the SMOTE algorithm to construct an early warning model with the improved dataset. The prediction performance of the models was compared and validated. RESULTS: Among the 1 104 patients who underwent surgical treatment for maxillofacial fractures, 27 cases of postoperative internal fixation device infections were identified, corresponding to an infection rate of 2.45% (27/1 104). Age, diabetes history, fracture severity, and oral hygiene status were all identified as risk factors for postoperative internal fixation device infections in maxillofacial fractures (all P<0.05). The prediction model based on the original data (P1). The prediction model based on the SMOTE algorithm (P2). Receiver operating characteristic (ROC) curve analysis shows that the area under curve (AUC) for the P2 model was 0.882, the P1 model was 0.861, indicating the superior predictive performance of the P2 model. The DeLong test results show that the difference in AUC between the two models was statistically significant (P<0.05). CONCLUSIONS Age, diabetes history, postoperative fracture severity, and oral hygiene status are all risk factors for infections associated with internal fixation devices after maxillofacial fracture surgery. The proposed early warning model demonstrated good predictive performance. Medical professionals can utilize this model to effectively intervene and anticipate infections related to internal fixation devices after maxillofacial fracture surgery.
Humans ; Algorithms ; Retrospective Studies ; Male ; Female ; Fracture Fixation, Internal/instrumentation* ; Risk Factors ; Middle Aged ; Adult ; Logistic Models ; Surgical Wound Infection/epidemiology* ; Aged ; Internal Fixators/adverse effects* ; Maxillofacial Injuries/surgery* ; Adolescent

OBJECTIVES: This study aimed to use machine learning algorithms to build a prediction model of the first permanent molar caries of 9-year-old children in Suzhou and screen out risk factors. METHODS: Random stratified whole group sampling was applied to randomly select 9-year-old students from 38 primary schools in 14 townships and streets in Wuzhong District for oral examination and questionnaire survey. Multifactor Logistics regression was used to analyze the risk factors of tooth decay. The data set was randomly divided into training sets and verification sets according to 8∶2, and R 4.3.1 was used to build five machine learning algorithms: random forest, decision tree, extreme gradient boosting (XGBoost), Logistics regression, and lightweight gradient enhancement (LightGBM). The predictive effect of these five models was evaluated using the area under the characteristic curve (AUC). The marginal contribution of quantitative characteristics to the caries prediction model was determined through Shapley additive explanations (SHAP). RESULTS: This study included 7 225 samples that met the standard. The caries rate of the first permanent molar was 54.96%. Multifactor Logistic regression analysis showed that sweet drinks, dessert and candy, snack frequency, and snacks before going to bed after brushing teeth were correlated with the occurrence of first permanent molar caries (P<0.05). The AUC values of decision tree, Logistic regression, LightGBM, random forest, and XGBoost were 75.5%, 83.9%, 88.6%, 88.9%, and 90.1%, respectively. Compared with the variables after single heat coding, the SHAP value of high-frequency sweets (such as dessert candy ≥2 times a day, mother's sugary diet ≥2 times a day) and bad oral hygiene habits (such as frequent snacks before going to bed after brushing teeth and irregular brushing teeth) exhibited the highest positive. CONCLUSIONS XGBoost algorithm has a good prediction effect for first permanent molar caries in 9-year-old children. High-frequency sweet factors and bad oral hygiene habits have a strong positive impact on the risk of first permanent molar caries and are key drivers that can be used in the formulation of targeted interventions.
Humans ; Dental Caries/epidemiology* ; Child ; Machine Learning ; China/epidemiology* ; Molar ; Risk Factors ; Female ; Logistic Models ; Male ; Decision Trees ; Algorithms

Objective To investigate the impact of the triglyceride-glucose(TyG)index on the risk of inflammatory bowel disease(IBD).Methods Based on the data from UK Biobank,participants were allocated into three groups,TyG1(≤4.564),TyG2(4.564-4.808),and TyG3(≥4.808),according to tertiles of the TyG index.Kaplan-Meier curves were established to analyze the cumulative incidence of IBD.Further,Cox proportional hazard regression was employed to analyze the hazard ratio(HR)and its 95% confidential interval(95%CI)of each group.The same analysis was conducted for different subtypes(ulcerative colitis and Crohn's disease)of IBD.Sensitive analysis based on the competing risk model was performed after excluding participants who were diagnosed within one year.Results A total of 116 423 participants were included in this study,with the median follow-up time of 12.56 years.The incidence densities of IBD in the TyG1,TyG2,and TyG3 groups were 4.47,5.94,and 6.50 per 10 000 person-year,respectively.The cumulative incidence of IBD increased with the rise in TyG,and Log-rank test results showed differences in cumulative incidence between groups(P<0.001).After adjusting the confounding factors,the HR(95%CI)of IBD in the TyG2 and TyG3 groups was 1.50(1.21-1.85)and 1.71(1.36-2.16),respectively.The results of the subgroup analysis after adjusting the confounding factors revealed that the HR(95%CI)of ulcerative colitis and Crohn's disease in the TyG3 group was 1.48(1.16-1.74)and 2.27(1.51-3.42),respectively.The sensitive analysis yielded similar results after excluding participants who were diagnosed within one year.Conclusion A high TyG index indicates an increased risk of IBD and its subtypes.
Humans ; Inflammatory Bowel Diseases/blood* ; Triglycerides/blood* ; Incidence ; Blood Glucose/analysis* ; Male ; Female ; Risk Factors ; Proportional Hazards Models ; Adult ; Middle Aged ; Crohn Disease/epidemiology*

Objective To analyze the changing trends of the burden of non-alcoholic fatty liver disease(NAFLD)in China from 1990 to 2021 and provide a basis for formulating prevention and treatment strategies.Methods The standardized incidence rate,prevalence,mortality,and disability-adjusted life year(DALY)rate of NAFLD in China from 1990 to 2021 were extracted from the Global Burden of Disease Study 2021.The average annual percentage change of rate data was calculated by Joinpoint 4.2 and the age,period,and birth cohort effects of the prevalence and DALY rate were analyzed by the age-period-cohort model.Results Compared to 1990,the incidence rate and prevalence of NAFLD have been on the rise,while the mortality and DALY rate have been declining.The age effect curves of prevalence and DALY rate showed an upward trend followed by a downward trend for both males and females.With the period from 1992 to 1996 as the reference group,the period effect curve of prevalence showed a downward trend followed by an upward trend,being the lowest in the period from 2002 to 2006(RR=0.93).The period effect curve of DALY rate showed a downward trend from 1992 to 2011 and then tended to flatten out.With the period from 1972 to 1981 as the reference group,the birth cohort effect curve of prevalence showed a steady upward trend in the general population and both male and female populations.The birth cohort effect curve of DALY rate showed an overall upward trend followed by a downward trend,with the peak occurring in the birth cohort group between 1922 and 1931.The DALY rate of NAFLD caused by smoking and high fasting blood glucose has shown a downward trend since 2014,and fasting blood glucose gradually became the dominant factor as age increased.Conclusions From 1990 to 2021,NAFLD in China has shown a rising prevalence but a significantly declining DALY rate.This suggests that current prevention and control strategies are effective,and further efforts should be made to raise residents' health awareness in controlling the occurrence and development of NAFLD.
Humans ; Non-alcoholic Fatty Liver Disease/epidemiology* ; China/epidemiology* ; Prevalence ; Female ; Male ; Incidence ; Disability-Adjusted Life Years ; Middle Aged ; Adult

Objective To analyze the influencing factors of death in the elderly with coronavirus disease 2019(COVID-19).Methods The case data of death caused by COVID-19 in West China Fourth Hospital from January 1 to July 8,2023 were collected,and surviving cases from the West China Elderly Health Cohort infected with COVID-19 during the same period were selected as the control.LASSO-Logistic regression was adopted to analyze the data after propensity score matching and the validity of the model was verified by drawing the receiver operating characteristic curve.Results A total of 3 239 COVID-19 survivors and 142 deaths with COVID-19 were included.The results of LASSO-Logistic regression showed that smoking(OR=3.33,95%CI=1.46-7.59,P=0.004),stroke(OR=3.55,95%CI=1.15-10.30,P=0.022),malignant tumors(OR=19.93, 95%CI=8.52-49.23, P<0.001),coronary heart disease(OR=7.68, 95%CI=3.52-17.07, P<0.001),fever(OR=0.51, 95%CI=0.26-0.96, P=0.042),difficulty breathing or asthma symptoms(OR=21.48, 95%CI=9.44-51.95, P<0.001),and vomiting(OR=8.19,95%CI=2.87-23.58, P<0.001)increased the risk of death with COVID-19.The prediction model constructed based on the influencing factors achieved an area under the curve of 0.889 in the test set.Conclusions Smoking,stroke,malignant tumors,coronary heart disease,fever,breathing difficulty or asthma symptoms,and vomiting were identified as key factors influencing the death risk in COVID-19.
Humans ; COVID-19/mortality* ; Aged ; Propensity Score ; China/epidemiology* ; Risk Factors ; Logistic Models ; Smoking ; SARS-CoV-2 ; Male ; Female ; Stroke ; Neoplasms

Objective To investigate the association between gastroesophageal reflux disease(GERD)and the risk of incident chronic obstructive pulmonary disease(COPD)and explore potential effect modifiers influencing this association.Methods Clinical data from 476 175 participants in the UK Biobank(2006-2010)were collected.A Cox proportional hazards model was used to assess the relationship between GERD and the risk of incident COPD.Subgroup analyses were conducted to examine potential modifiers of the primary findings.Results A total of 11 587(2.43%)new COPD cases were diagnosed.The Cox proportional hazards model revealed that GERD was associated with an increased risk of incident COPD(HR=1.59,95%CI=1.46-1.74,P<0.001).GERD was linked to a higher risk of incident COPD in individuals aged<60 years(P<0.001)and non-smokers(P=0.011).No association was observed between GERD and the risk of incident COPD in current smokers with a daily cigarette consumption<10 cigarettes(P=0.261).Conclusion GERD may increase the risk of incident COPD.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Gastroesophageal Reflux/epidemiology* ; Middle Aged ; Proportional Hazards Models ; Incidence ; Male ; Risk Factors ; Female ; Aged

BACKGROUND: Research has indicated that the disease burden of alopecia areata (AA) in China exceeds the global average. Therefore, accurate and updated epidemiological information is crucial for policymakers. In this study, we aimed to comprehensively assess the disease burden of AA in China. METHODS: The following four key indicators were utilized: the prevalence of cases; disability-adjusted life-years (DALYs); the age-standardized prevalence rate (ASPR); and the age-standardized DALY rate (ASDR) of AA according to the Global Burden of Disease (GBD) study 2021. We analyzed the epidemiological burden of AA in China during 2021, examined changes between 1990 and 2021, and performed a Bayesian age-period-cohort analysis to predict trends over the course of the next decade (2022-2030). Additionally, a Gaussian process regression model was applied to estimate the relationship between the gross domestic product (GDP) and the ASPR and ASDR of AA at the provincial level between 1992 and 2021. RESULTS: In 2021, the estimated number of patients with AA in China was approximately 3.49 million (95% uncertainty interval [UI], 3.37-3.62 million); of these patients, 1.20 million (95% UI, 1.16-1.25 million) were male and 2.29 million (95% UI, 2.20-2.37 million) were female. This large number of patients with AA resulted in a total of 114,431.25 DALYs (95% UI, 74,780.27-160,318.96 DALYs). Additionally, the ASPR and ASDR were 224.61 per 100,000 population (95% UI, 216.73-232.65 per 100,000 population) and 7.41 per 100,000 population (95% UI, 4.85-10.44 per 100,000 population), respectively; both of these rates were higher than the global averages. The most affected demographic groups were young and female individuals 25-39 years of age. Slight regional disparities were observed, with the northern and central regions of China bearing comparatively higher burdens. Between 1990 and 2021, the health loss and disease burden caused by AA in China remained relatively stable. The ASPR and ASDR of AA increased with the GDP when the annual GDP was less than 2 trillion Chinese yuan; however, a downward trend was observed as the GDP surpassed 2 trillion Chinese yuan. A slight upward trend in the disease burden of AA in China is predicted to occur over the next decade. CONCLUSIONS AA continues to be a public health concern in China that shows no signs of declining. Targeted efforts for young individuals and females are necessary because they experience a disproportionately high burden of AA.
Humans ; China/epidemiology* ; Alopecia Areata/epidemiology* ; Global Burden of Disease ; Female ; Male ; Adult ; Disability-Adjusted Life Years ; Middle Aged ; Prevalence ; Adolescent ; Young Adult ; Bayes Theorem ; Child ; Quality-Adjusted Life Years ; Child, Preschool

BACKGROUND: Approximately 40% of individuals with diabetes worldwide are at risk of developing diabetic kidney disease (DKD), which is not only the leading cause of kidney failure, but also significantly increases the risk of cardiovascular disease, causing significant societal health and financial burdens. This study aimed to describe the burden of DKD and explore its cross-country epidemiological status, predict development trends, and assess its risk factors and sociodemographic transitions. METHODS: Based on the Global Burden of Diseases (GBD) Study 2021, data on DKD due to type 1 diabetes (DKD-T1DM) and type 2 diabetes (DKD-T2DM) were analyzed by sex, age, year, and location. Numbers and age-standardized rates were used to compare the disease burden between DKD-T1DM and DKD-T2DM among locations. Decomposition analysis was used to assess the potential drivers. Locally weighted scatter plot smoothing and Frontier analysis were used to estimate sociodemographic transitions of DKD disability-adjusted life years (DALYs). RESULTS: The DALYs due to DKD increased markedly from 1990 to 2021, with a 74.0% (from 2,227,518 to 3,875,628) and 173.6% (from 4,122,919 to 11,278,935) increase for DKD-T1DM and DKD-T2DM, respectively. In 2030, the estimated DALYs for DKD-T1DM surpassed 4.4 million, with that of DKD-T2DM exceeding 14.6 million. Notably, middle-sociodemographic index (SDI) quintile was responsible for the most significant DALYs. Decomposition analysis revealed that population growth and aging were major drivers for the increased DKD DALYs in most regions. Interestingly, the most pronounced effect of positive DALYs change from 1990 to 2021 was presented in high-SDI quintile, while in low-SDI quintile, DALYs for DKD-T1DM and DKD-T2DM presented a decreasing trend over the past years. Frontiers analysis revealed that there was a negative association between SDI quintiles and age-standardized DALY rates (ASDRs) in DKD-T1DM and DKD-T2DM. Countries with middle-SDI shouldered disproportionately high DKD burden. Kidney dysfunction (nearly 100.0% for DKD-T1DM and DKD-T2DM), high fasting plasma glucose (70.8% for DKD-T1DM and 87.4% for DKD-T2DM), and non-optimal temperatures (low and high, 5.0% for DKD-T1DM and 5.1% for DKD-T2DM) were common risk factors for age-standardized DALYs in T1DM-DKD and T2DM-DKD. There were other specific risk factors for DKD-T2DM such as high body mass index (38.2%), high systolic blood pressure (10.2%), dietary risks (17.8%), low physical activity (6.2%), lead exposure (1.2%), and other environmental risks. CONCLUSIONS DKD markedly increased and varied significantly across regions, contributing to a substantial disease burden, especially in middle-SDI countries. The rise in DKD is primarily driven by population growth, aging, and key risk factors such as high fasting plasma glucose and kidney dysfunction, with projections suggesting continued escalation of the burden by 2030.
Humans ; Global Burden of Disease ; Risk Factors ; Male ; Female ; Disability-Adjusted Life Years ; Diabetic Nephropathies/epidemiology* ; Middle Aged ; Diabetes Mellitus, Type 2/epidemiology* ; Adult ; Diabetes Mellitus, Type 1/complications* ; Aged ; Adolescent ; Young Adult ; Quality-Adjusted Life Years