OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

To evaluate the occurrence of rheumatological immune-related adverse events (irAEs) induced by immune checkpoint inhibitors (ICIs) using real-world database data.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.

Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)％.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0％vs 29.5％).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7％vs 7.8％,0.8％vs 0.1％,both P＜0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)％with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9％and 1.8％,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1％).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10％.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P＜0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To develop and validate a machine learning-based predictive model to assess the in-hospital mortality risk of patients with myocardial infarction(MI)complicated by heart failure(HF)undergoing percutaneous coronary intervention(PCI).Methods This retrospective study analyzed MI patients with HF who underwent PCI at The First Affiliated Hospital of Xinjiang Medical University from January 2019 to January 2023.Patient data,including demographic characteristics,vital signs,laboratory test results,imaging parameters and medication use,were collected and randomly divided into a training set(70％)and a validation set(30％).The extreme gradient boosting(XGBoost)model was used to identify variables significantly associated with in-hospital mortality,and the Shapley additive explanations(SHAP)model was applied to assess feature importance.A predictive model was then constructed using univariate and multivariate Logistic regression analyses.Model performance was evaluated using receiver operating characteristic(ROC)curves,area under the curve(AUC)values,calibration curves,and decision curve analysis.Finally,a nomogram was developed for intuitive risk assessment.Results A total of 1 214 MI patients with HF were included in the study,with a median age of 64 years.The in-hospital mortality rate was 7.41％(90 deaths).XGBoost feature selection identified ten key predictive variables:age,myoglobin,albumin,fasting blood glucose,N-terminal pro-B-type natriuretic peptide(NT-proBNP),diabetes mellitus,creatinine,cystatin C,procalcitonin,and left ventricular ejection fraction.Based on these variables,a Logistic regression model was developed,with seven final predictors:age,diabetes mellitus,creatinine,fasting blood glucose,cystatin C,NT-proBNP,and albumin.The model demonstrated high predictive accuracy,with AUC value of 0.869(95％CI:0.84-0.89)in the training set and 0.827(95％CI:0.79-0.85)in the validation set.The calibration curve indicated that the predicted probabilities were consistent with the actual observed outcomes,and decision curve analysis showed that the model had a high net benefit across various decision thresholds.Conclusion This study developed a machine learning-based predictive model incorporating Logistic regression to assess the in-hospital mortality risk of MI patients with HF undergoing PCI.The model demonstrated high predictive performance and clinical utility.The nomogram derived from this model provides an intuitive tool for individualized risk assessment,aiding clinicians in the early identification of high-risk patients,optimizing intervention strategies,and improving patient outcomes.

Objective To construct and validate machine learning-based models to predict the risk of acute kidney injury(AKI)following percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 2 315 STEMI patients who underwent PCI between January 2020 and June 2023 were included;306(13.2％)of them developed AKI.Baseline variables were screened using LASSO regression,with the optimal λ value selected via 10-fold cross-validation to identify AKI-associated features.Subsequently,eight distinct machine learning models were constructed and evaluated for their predictive performance.SHAP value analysis was employed to assess the impact of key variables on model predictions.Results LASSO regression identified seven variables significantly associated with AKI,including age,multivessel disease,preoperative creatinine,heart failure,white blood cell count,hemoglobin,and albumin levels.Among all the models,the light gradient boosting machine(LGBM)and extreme gradient boosting(XGB)demonstrated the best predictive performance,with training set AUCs being 0.899(95％CI:0.877-0.921)and 0.893(95％CI:0.868-0.918),and validation set AUCs being 0.809(95％CI:0.763-0.856)and 0.871(95％CI:0.833-0.909),respectively.SHAP analysis revealed that albumin,age,preoperative creatinine,and white blood cell count were the primary contributors to AKI risk.Conclusion This study successfully developed and validated machine learning-based predictive models capable of effectively identifying the risk of AKI following PCI in STEMI patients,thus providing valuable support for clinical decision-making.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective:To compare the efficacy of body posture combined with pharmacotherapy and pharmacotherapy alone in the treatment of chronic subdural hematoma(CSDH).Methods:Firstly, retrospective case series study was conducted. Thirty cases of CSDH that had received body posture combined with pharmacotherapy at Department of Neurosurgery, Huashan Hospital Affiliated to Fudan University from December 2016 to October 2020 were studied retrospectively. Twenty-seven patients were male, and 3 patients were female. The age of patients ( M(IQR)) was 66(16) years (range:28 to 84). Nineteen patients had unilateral hematoma, and 11 patients had bilateral hematoma. All patients received pharmacotherapy and body posture therapy that was to raise their lower limbs 20 to 30 cm with leg lift pad and get abdominal compressed with customized abdominal belt in supine position. Patients were required to maintain the body posture as much as possible, with the maximum to 16 to 18 hours per day. Patients with unilateral hematoma should tilt the head to the affected side and avoid tilting it to the opposite side. For patients with bilateral hematoma, there was no need for head lateralization. Patient were treated with oral dexamethasone and atorvastatin simultaneously. The preliminary efficacy of body posture combined with pharmacotherapy was determined by hematoma improvement rate which was analyzed by Clopper-Pearson method. Then, the multi-center, prospective, randomized controlled trial had carried out in 9 medical centers from August 2020 to November 2021. The stratified block randomization method was adopted. Patients were randomized in a ratio of 1∶1 to either receive pharmacotherapy alone(the control group) or body posture combined with pharmacotherapy(the experiment group) for 3 months and followed up for 6 months. Effective treatment was defined as complete absorption of hematoma, or the hematoma volume decreased by more than 10 ml and Markwalder grading scale score had improved by more than 1 point compared to the baseline. The efficacy rate and surgery conversion rate at 3 months and recurrence at 6 months were observed. Comparison between groups was performed with paired sample t test, Mann-Whitney U test, χ2 test, corrected χ2 test, or Fisher exact probability method. Logistic regression was used to compare the effective rate and operation rate between the two groups. Results:In the respective study, 30 patients completed follow-up 13 to 353 days after treatment. At the last follow-up, the incidence of almost complete absorption or significantly absorption of hematoma (hematoma volume was significantly reduced accompanied by symptom improvement) was 93.3%. The 95% CI for the incidence that analyzed by the Clopper-Pearson method was 77.9% to 99.2%. One hundred and six patients were enrolled in the multicenter study. Fifty-five patients underwent body posture combined with pharmacotherapy. The age was 74(17) years (range:26 to 92). Thirty-nine patients were males and 16 were females. Fifty-one patients underwent pharmacotherapy alone. The age was 69(12) years (range:48 to 84). Thirty-seven patients were males and 14 were females. The length of body posture recorded in diary card was (15.7±2.3) hours(range:7.6 to 19.3 hours). The efficacy rate in the body posture combined with pharmacotherapy group and pharmacotherapy alone group were 83.6% (46/55) and 56.9% (29/51), respectively at 3 months. The result of the logistic regression analysis showed that the efficacy of body posture combined with pharmacotherapy group was better than that of pharmacotherapy alone group ( OR=3.88,95% CI:1.57 to 9.58, P=0.003). Surgery rate in the body posture combined with pharmacotherapy group and pharmacotherapy alone group were 5.5% (3/55) and 21.6% (11/51) respectively. The result of Logistic regression showed that the pharmacotherapy alone group was more likely to be converted to surgery ( OR=0.21,95% CI:0.05 to 0.80, P=0.023). At the 6 months, no recurrence of cases was found in the body posture combined with pharmacotherapy group. However, the recurrence rate of pharmacotherapy alone group was 6.3% (3/48), there was no significant difference between the two groups ( P>0.05). Conclusion:The effect of body posture combined with pharmacotherapy for chronic subdural hematoma is better than that of pharmacotherapy alone.