OBJECTIVES: To analyze the clinical characteristics of diffuse panbronchiolitis (DPB) in children and to enhance the clinical diagnosis and treatment of this disease. METHODS: A retrospective analysis was conducted on the clinical data of 6 children diagnosed with DPB who were hospitalized at The First Affiliated Hospital of Guangzhou Medical University from January 2011 to December 2019. RESULTS: Among the 6 patients, there were 2 males and 4 females; the age at diagnosis ranged from 7 to 12 years. All patients presented with cough, sputum production, and exertional dyspnea, and all had a history of sinusitis. Two cases showed positive serum cold agglutinin tests, and 5 cases exhibited pathological changes consistent with chronic bronchiolitis. High-resolution chest CT in all patients revealed centrilobular nodules diffusely distributed throughout both lungs with a tree-in-bud appearance. Five patients received low-dose azithromycin maintenance therapy, but 3 showed inadequate treatment response. After empirical anti-tuberculosis treatment, non-tuberculous Mycobacteria were found in the bronchoalveolar lavage fluid. Follow-up over 2 years showed 1 case cured, 3 cases significantly improved, and 2 cases partially improved. CONCLUSIONS The clinical presentation of DPB is non-specific and can easily lead to misdiagnosis. In cases where DPB is clinically diagnosed but does not show improvement with low-dose azithromycin treatment, special infections should be considered.
Humans ; Male ; Female ; Bronchiolitis/drug therapy* ; Retrospective Studies ; Child ; Haemophilus Infections/diagnosis*

OBJECTIVES: To investigate the clinical features of children with STAT gene mutations, and to explore corresponding immunotherapy strategies. METHODS: A retrospective analysis was performed for the clinical data of 10 children with STAT gene mutations who were admitted to the Department of Pediatrics of the First Affiliated Hospital of Guangzhou Medical University, from October 2015 to October 2024. Exploratory immunotherapy was implemented in some refractory cases, and the changes in symptoms, imaging manifestations, and cytokine levels were assessed after treatment. RESULTS: For the 10 children, the main clinical manifestations were recurrent rash since birth (7/10), cough (8/10), wheezing (5/10), expectoration (4/10), and purulent nasal discharge (4/10). Genotyping results showed that there was one child with heterozygous loss-of-function (LOF) mutation in the STAT1 gene, four children with heterozygous LOF mutation in the STAT3 gene, and five children with heterozygous gain-of-function (GOF) mutation in the STAT3 gene. Two children with LOF mutation in the STAT3 gene showed decreased interleukin-6 levels and improved clinical symptoms and imaging findings after omalizumab treatment. Three children with GOF mutation in the STAT3 gene achieved effective disease control after treatment with methylprednisolone (0.5 mg/kg per day). Two children with GOF mutation in the STAT3 gene received treatment with JAK inhibitor and then showed some improvement in symptoms. CONCLUSIONS STAT gene mutation screening should be considered for children with recurrent rash and purulent respiratory tract infections. Targeted immunotherapy may improve prognosis in patients with no response to conventional treatment.
Humans ; Male ; Immunotherapy ; Female ; Child, Preschool ; Child ; Gain of Function Mutation ; Retrospective Studies ; Infant ; Loss of Function Mutation ; STAT Transcription Factors/genetics*

OBJECTIVE: To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis (TB) in the Guangdong Province between 2010 and 2019. METHOD: Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering. Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive (ST-CAR) model. RESULTS: Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000 in 2019. Spatial hotspots were found in northeastern Guangdong, particularly in Heyuan, Shanwei, and Shantou, while Shenzhen, Dongguan, and Foshan had the lowest rates in the Pearl River Delta. The ST-CAR model showed that the TB risk was lower with higher per capita Gross Domestic Product (GDP) [Relative Risk ( RR), 0.91; 95% Confidence Interval ( CI): 0.86-0.98], more the ratio of licensed physicians and physician ( RR, 0.94; 95% CI: 0.90-0.98), and higher per capita public expenditure ( RR, 0.94; 95% CI: 0.90-0.97), with a marginal effect of population density ( RR, 0.86; 95% CI: 0.86-1.00). CONCLUSION The incidence of TB in Guangdong varies spatially and temporally. Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection. Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
Humans ; China/epidemiology* ; Incidence ; Bayes Theorem ; Spatio-Temporal Analysis ; Tuberculosis/epidemiology* ; Socioeconomic Factors

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*

Objective To compare the hemodynamic effects of anesthesia induction with remimazolam tosylate and etomidate in elderly frail patients.Methods This study was a single-center,prospective,randomized,single-blind trial.From January to April 2024,96 elderly frail patients undergoing elective surgery in Fuyang People's Hospital were recruited.After excluding 6 cases(3 refused to participate,1 had tracheal intubation time＞30 s,and 2 had missing data),90 patients were finally included.They were randomly divided into remimazolam tosylate group(intravenous injection of 0.2 mg/kg remimazolam tosylate for anesthesia induction,n=45)and etomidate group(intravenous injection of 0.3 mg/kg etomidate for anesthesia induction,n=45)by the random number table method.The area under the curve for mean arterial pressure(MAP)below or above baseline values(AUCMAP-and AUCMAP+),the heart rate(HR)below or above baseline values by 10％(AUCHR-and AUCHR+)within 10 minutes of anesthesia induction,the time to loss of consciousness,the time from the start of anesthesia induction to a bispectral index(BIS)＜60,the incidence of drug-related adverse reactions,the incidence of cardiovascular adverse events,and the usage of vasoactive drug administrations were compared between the two groups.Results Compared with the etomidate group,the AUCMAP-(145.10±35.75 vs.178.52±39.78)and AUCHR-[43.20(26.58,56.35)vs.54.99(43.01,65.85)]in remimazolam tosylate group were significantly reduced(P＜0.001,P=0.001).The time to loss of consciousness and the time from the start of anesthesia induction to BIS＜60 were prolonged(P＜0.001).The incidence of drug-related adverse reactions was significantly decreased(P＜0.05),and the number of norepinephrine administrations was significantly reduced(P＜0.05)in remimazolam tosylate group.However,there were no statistically significant differences in AUCMAP+,AUCHR+,the incidence of cardiovascular adverse events,and the usages of atropine,urapidil,and esmolol between the two groups(P＞0.05).Conclusion The use of remimazolam tosylate during anesthesia induction in elderly frail patients can provide more stable hemodynamic parameters and results in fewer adverse reactions than etomidate.

Objective:To explore the quantitative indexes of dual energy spectrum CT and related clinical data to establish a predictive model for predicting pneumoconiosis.Methods:In April 2024, the information of 203 pneumoconiosis patients diagnosed by the occupational disease appraisal expert group in the Third People's Hospital of Xinjiang Uygur Autonomous Region (Occupational Disease Hospital of Xinjiang Autonomous Region) from January 2022 to December 2023 was retrospectively analyzed. Another 207 non-pneumoconiosis patients with dust exposure history were selected as control group. The measurement data between the two groups were compared using T test or Wilcoxon in dependent quality test, count date asing chi-square or Fishers test, the energy spectrum related indicators and clinical indicators of the patients were compared between groups, and potential factors for diagnosis of pneumoconiosis were screened through univariate analysis, and independent risk factors were further determined by multivariate logistic regression. Based on the results of regression analysis, the machine learning model was constructed, and the reciver operating characteristic curve (ROC) was drawn to evaluate the efficiency of the model, and the Area under cruve (AUC) value, sensitivity and specificity were calculated.Results:Smoking, lung tissue mass, silicon dioxide (SiO 2) equivalent total mass and SiO 2 equivalent concentration were the risk factors for pneumoconiosis ( P<0.05) . Multivariate logistic regression analysis showed that smoking, lung tissue mass, total lung SiO 2 equivalent total volume and total lung SiO 2 equivalent total mass were independent predicators of the diagnosis of pneumoconiosis ( OR=0.53, 0.99, 1.13, 0.85, P<0.05) . Logistic regression machine learning was used to establish a predictive model, and the training set AUC was 0.74, and the verification set AUC was 0.72, indicating that the model had good accuracy and certain ability to diagnose pneumoconiosis. Conclusion:The machine learning prediction model established by the quantitative analysis index of dual energy spectrum CT and clinical related indexes has a good diagnostic performance for the diagnosis of pneumoconiosis.

Objective:To explore the risk factors of colostomy site incisional hernia associated with colorectal can-cer and to construct and validate a nomogram model.Methods:A retrospective case-control study was conducted to collect and analyze the clinical data of patients who underwent stoma reversal after colorectal cancer surgery in the Gen-eral Surgery Department of Linyi People's Hospital from January 2019 to January 2023.A total of 371 patients were en-rolled and divided into SSIH group and non-SSIH group according to whether SSIH occurred.SPSS 25.0 software was used to perform univariate analysis on 22 related factors of patients,and multivariate analysis was performed on statisti-cally significant risk factors to screen out the independent influencing factors of SSIH related to CRC surgery.According to the results of multivariate analysis,the R language version 4.3.1 was used to establish and verify the nomogram risk prediction model.Results:SSIH occurred in 52 of 371 patients(14.02％).The results of univariate analysis showed that BMI,coronary heart disease,incision infection,stoma location,parastomal hernia,and closure time were statistically sig-nificant(P＜0.05).Multivariate analysis showed that coronary heart disease,closure time and parastomal hernia were in-dependent risk factors for SSIH after CRC(P＜0.05).Based on the above results,the nomogram prediction model was successfully drawn and verified.Conclusions:Coronary heart disease,closure time and parastomal hernia are inde-pendent risk factors for SSIH after CRC surgery.The nomogram constructed based on these factors has a high predictive value for SSIH,which can provide a basis for clinicians to prevent and treat SSIH,and help reduce the incidence of SSIH.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective To analyze the association between lifestyle and the risk of type 2 diabetes(T2D)among adult residents.Methods The data was sourced from the Shanghai Suburban Adult Cohort and Biobank.A total of 42 096 adult residents who had not developed T2D were recruited from four districts of Shanghai(Songjiang,Jiading,Minhang,and Xuhui)between 2016 and 2019.The follow-up ended on Feb 28,2023.A structured questionnaire was used to collect information on six lifestyle-related items,including smoking,alcohol consumption,BMI,waist circumference(WC),physical activity,and diet.The unhealthy lifestyle scores(UHLS)were calculated by counting the number of all the unhealthy lifestyle items,with a range of 0-6.New-onset T2D events diagnosed by physicians were obtained through the medical information system.Cox proportional hazards regression model and restricted cubic spline model were utilized to evaluate the association between unhealthy lifestyles and the risk of T2D incidence.Results About 28.1%of the participants led 4-6 unhealthy lifestyles.A total of 1 752 new T2D cases were identified during 218 513.4 person-years of follow-up.Analysis of single unhealthy lifestyle showed that abnormal WC(HR=1.5,95%CI:1.4-1.7)and abnormal BMI(HR=1.3,95%CI:1.2-1.5)were associated with an increased risk of T2D.Compared with individuals with a UHLS of 0-1,those with a UHLS of 3 and 4-6 had 30%(95%CI:1.1-1.6)and 50%(95%CI:1.2-1.8)higher risks of T2D,respectively.Each additional unhealthy lifestyle was associated with a 10%increase in T2D incidence risk(HR=1.1,95%CI:1.1-1.2).Conclusion The risk of T2D in adult residents increases with the cumulative number of unhealthy lifestyles.Adult residents with abnormal WC or BMI,or have three or more unhealthy lifestyles accumulated,will increase the risk of new-onset T2D.

Objective:To explore the quantitative indexes of dual energy spectrum CT and related clinical data to establish a predictive model for predicting pneumoconiosis.Methods:In April 2024, the information of 203 pneumoconiosis patients diagnosed by the occupational disease appraisal expert group in the Third People's Hospital of Xinjiang Uygur Autonomous Region (Occupational Disease Hospital of Xinjiang Autonomous Region) from January 2022 to December 2023 was retrospectively analyzed. Another 207 non-pneumoconiosis patients with dust exposure history were selected as control group. The measurement data between the two groups were compared using T test or Wilcoxon in dependent quality test, count date asing chi-square or Fishers test, the energy spectrum related indicators and clinical indicators of the patients were compared between groups, and potential factors for diagnosis of pneumoconiosis were screened through univariate analysis, and independent risk factors were further determined by multivariate logistic regression. Based on the results of regression analysis, the machine learning model was constructed, and the reciver operating characteristic curve (ROC) was drawn to evaluate the efficiency of the model, and the Area under cruve (AUC) value, sensitivity and specificity were calculated.Results:Smoking, lung tissue mass, silicon dioxide (SiO 2) equivalent total mass and SiO 2 equivalent concentration were the risk factors for pneumoconiosis ( P<0.05) . Multivariate logistic regression analysis showed that smoking, lung tissue mass, total lung SiO 2 equivalent total volume and total lung SiO 2 equivalent total mass were independent predicators of the diagnosis of pneumoconiosis ( OR=0.53, 0.99, 1.13, 0.85, P<0.05) . Logistic regression machine learning was used to establish a predictive model, and the training set AUC was 0.74, and the verification set AUC was 0.72, indicating that the model had good accuracy and certain ability to diagnose pneumoconiosis. Conclusion:The machine learning prediction model established by the quantitative analysis index of dual energy spectrum CT and clinical related indexes has a good diagnostic performance for the diagnosis of pneumoconiosis.