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 assess relationships between cold spells and genitourinary hospitalization risk. METHODS: Hospitalization records for genitourinary system diseases (GUDs) from 16 districts in Beijing (2013-2018) were analyzed. Cold spells were defined based on varying intensity thresholds. A two-stage analytical method was employed: first, generalized linear models assessed district-specific associations between cold spells and hospitalizations; second, random-effects meta-analysis aggregated the district-level results. Subgroup analyses were performed by admission type (emergency vs. outpatient), age, and sex. RESULTS: A total of 271,579 GUD-related hospitalizations were recorded. Cold spells (p1day2，daily mean temperature below the 1 ^st percentiles of the daily mean temperature distribution from January 1, 2013, to December 31, 2018, lasting for two or more consecutive days) were linked to a significant rise in hospitalization risks: 1.43 (95% CI: 1.32-1.56) for all GUDs, 1.35 (95% CI: 1.23-1.49) for urinary system diseases, and 1.46 (95% CI: 1.28-1.67) for renal failure, when compared to non-cold spell days. Emergency admissions showed higher risk increases than outpatient admissions. CONCLUSION Extreme cold spells significantly elevate hospitalization risks for GUDs. This highlights the urgent need for targeted public health interventions to mitigate cold-related health impacts, especially for vulnerable populations.
Humans ; Hospitalization/statistics & numerical data* ; Male ; Female ; Cold Temperature/adverse effects* ; Infant ; Child, Preschool ; Middle Aged ; Adult ; Child ; Aged ; Adolescent ; Young Adult ; Beijing/epidemiology* ; Female Urogenital Diseases/etiology* ; Male Urogenital Diseases/etiology* ; Infant, Newborn ; Risk Factors

OBJECTIVE: To assess the short-term lag effects of climate and air pollution on hospital admissions for cardiovascular and respiratory diseases, and to develop deep learning-based models for daily hospital admission prediction. METHODS: A multi-city study was conducted in Tokyo's 23 wards, Osaka City, and Nagoya City. Random forest models were employed to assess the synergistic short-term lag effects (lag0, lag3, and lag7) of climate and air pollutants on hospitalization for five cardiovascular diseases (CVDs) and two respiratory diseases (RDs). Furthermore, we developed hybrid deep learning models that integrated an autoencoder (AE) with a Long Short-Term Memory network (AE+LSTM) to predict daily hospital admissions. RESULTS: On the day of exposure (lag0), air pollutants, particularly nitrogen oxides (NO x), exhibited the strongest influence on hospital admissions for CVD and RD, with pronounced effects observed for hypertension (I10-I15), ischemic heart disease (I20), arterial and capillary diseases (I70-I79), and lower respiratory infections (J20-J22 and J40-J47). At longer lags (lag3 and lag7), temperature and precipitation were more influential predictors. The AE+LSTM model outperformed the standard LSTM, improving the prediction accuracy by 32.4% for RD in Osaka and 20.94% for CVD in Nagoya. CONCLUSION Our findings reveal the dynamic, time-varying health risks associated with environmental exposure and demonstrate the utility of deep learnings in predicting short-term hospital admissions. This framework can inform early warning systems, enhance healthcare resource allocation, and support climate-adaptive public health strategies.
Humans ; Hospitalization/statistics & numerical data* ; Cardiovascular Diseases/epidemiology* ; Japan/epidemiology* ; Air Pollutants/analysis* ; Air Pollution/adverse effects* ; Cities/epidemiology* ; Climate ; Respiratory Tract Diseases/epidemiology* ; Deep Learning ; Male

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major health concern in northwest China; however, the impact of particulate matter (PM) exposure during sand-dust storms (SDS) remains poorly understood. Therefore, this study aimed to investigate the association between PM exposure on SDS days and COPD hospitalization risk in arid regions. METHODS: Data on daily COPD hospitalizations were collected from 323 hospitals from 2018 to 2022, along with the corresponding air pollutant and meteorological data for each city in Gansu Province. Employing a space-time-stratified case-crossover design and conditional Poisson regression, we analyzed 265,379 COPD hospitalizations. RESULTS: PM exposure during SDS days significantly increased COPD hospitalization risk [relative risk ( RR) for PM _2.5, lag 3:1.028, 95% confidence interval ( CI): 1.021-1.034], particularly among men and the elderly, and during the cold season. The burden of PM exposure on COPD hospitalization was substantially high in Northwest China, especially in the arid and semi-arid regions. CONCLUSION Our findings revealed a positive correlation between PM exposure during SDS episodes and elevated hospitalization rates for COPD in arid and semi-arid zones in China. This highlights the urgency of developing region-specific public health strategies to address adverse respiratory outcomes associated with SDS-related air quality deterioration.
Humans ; China/epidemiology* ; Pulmonary Disease, Chronic Obstructive/chemically induced* ; Particulate Matter/analysis* ; Hospitalization/statistics & numerical data* ; Male ; Female ; Middle Aged ; Aged ; Air Pollutants/analysis* ; Environmental Exposure/adverse effects* ; Spatio-Temporal Analysis ; Adult ; Sand ; Air Pollution

OBJECTIVE: To investigate hypertension (HTN) trends, key risk factors, and gender disparities in rural China, and to propose targeted strategies for improving HTN control in resource-limited settings. METHODS: This longitudinal study used data from the Henan Rural Cohort Study, including baseline (2015-2017; n = 39,224) and follow-up (2018-2022; n = 28,621) participants. HTN was defined as systolic/diastolic blood pressure ≥ 140/90 mmHg, self-reported diagnosis, or use of antihypertensive medication. Severity was classified using a 7-tier blood pressure (BP) staging system (optimal, normal, high normal, and HTN stages 1-4). A generalized linear mixed-effects model (GLMM) identified associated risk factors. RESULTS: HTN prevalence increased modestly from 32.7% (95% CI: 32.2-33.2) to 33.9% (95% CI: 33.3%-34.4%). Awareness and treatment improved from 20.1% to 25.3%, and from 18.8% to 24.4%, respectively, but control rates remained low (6.2% to 12.3%). After adjustment, women had a 1.53-fold higher HTN risk than men ( OR = 1.53, 95% CI: 1.43-1.63), revealing gender-specific trends. Key risk factors included alcohol use ( OR = 1.37, 95% CI: 1.27-1.47) and overweight status ( OR = 1.76, 95% CI: 1.66-1.86). BP staging showed an increase in optimal BP (42.3% to 45.8%), but stagnant management of advanced HTN stages. CONCLUSION Hypertension in rural China is shaped by behavioral risk factors and healthcare access gaps. Gender-sensitive, community-based interventions, including task-shifting models, are necessary to mitigate the growing burden of hypertension.
Humans ; Hypertension/etiology* ; China/epidemiology* ; Female ; Male ; Rural Population/statistics & numerical data* ; Prevalence ; Risk Factors ; Middle Aged ; Adult ; Aged ; Longitudinal Studies ; Sex Factors ; Cohort Studies ; East Asian People

Ambient air pollution is increasingly being recognized as a risk factor for heart failure; however, its effects on cardiac biomarkers remain unclear. This scoping review assessed the existing evidence on the association between air pollution and cardiac biomarkers in heart failure, described the key concepts, synthesized data, and identified research gaps. Following the PRISMA-ScR guidelines, PubMed, Embase, Web of Science, and CNKI databases were searched for studies on air pollution, heart failure, and biomarkers. A total of 765 records were screened, and 81 full texts were assessed for eligibility, resulting in 15 studies. The results showed that the exposure to particulate matter was associated with elevated N-terminal pro-B-type natriuretic peptide and troponin levels. Several studies have linked particulate matter exposure to a higher cardiovascular risk and heart failure biomarkers. Inflammatory and oxidative stress markers were consistently elevated across studies, supporting the biological relevance of these associations. However, few studies have focused specifically on populations with heart failure or clinically relevant biomarkers, and the evidence for gaseous pollutants remains inconclusive. These findings highlight the need to integrate environmental risk assessment into heart failure care and inform policy efforts to reduce the pollution-related cardiovascular burden. Further research should address these gaps through improved exposure assessments and the integration of mechanistic evidence.
Heart Failure/epidemiology* ; Biomarkers/metabolism* ; Humans ; Air Pollution/adverse effects* ; Air Pollutants/adverse effects* ; Particulate Matter/adverse effects* ; Environmental Exposure ; Natriuretic Peptide, Brain/blood* ; Oxidative Stress ; Troponin/blood*

OBJECTIVES: This cross-sectional study aims to explore the association between oral health status and cognitive function in Chinese elderly individuals. METHODS: The survey participants were composed of elderly people aged≥60 who were admitted to West China Hospital of Stomatology, Sichuan University from August 2022 to March 2024. They were divided into a cognitive impairment (CI) group and a healthy control (HC) group according to the Montreal Cognitive Assessment (MoCA) score. General information and oral health indicators of all elderly people were collected. Independent sample t-test and chi-square test were used for inter-group comparison, and multiple linear regression model was applied for multivariate analysis of MoCA scores. RESULTS: A total of 402 elderly people were included in the study, and the number of remaining teeth in the CI group was significantly lower than that in the HC group. The decayed, missing, filled teeth index, debris index-simplified, gingival index, probing depth (PD), and clinical attachment loss in the CI group were all significantly higher than those in the HC group. There was no difference in denture wearing between the two groups. The results of multiple linear regression showed that there was a correlation between the number of remaining teeth and PD and MoCA scores after correcting for confounding factors. CONCLUSIONS Elderly individuals with CI have more prominent oral health issues compared to those with normal cognitive function. There may be a bidirectional relationship between the number of remaining teeth, PD, and cognitive function in elderly people.
Humans ; Oral Health ; Aged ; Cross-Sectional Studies ; Cognitive Dysfunction/epidemiology* ; Male ; Female ; China/epidemiology* ; Middle Aged ; Linear Models ; Aged, 80 and over ; Periodontal Index ; Cognition

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*