BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

BACKGROUND: A growing body of research is exploring the role of antioxidant and anti-inflammatory dietary supplements in the treatment of osteoarthritis, highlighting an increasing emphasis on non-pharmacological interventions. Although more patients are turning to supplements to manage osteoarthritis, their actual effectiveness remains uncertain. OBJECTIVE: This study aims to provide a comprehensive evaluation of the available evidence concerning the efficacy of various dietary supplements in osteoarthritis treatment. SEARCH STRATEGY: We searched PubMed, Embase, Cochrane Library and Web of Science for studies on the use of various dietary supplements in the treatment of osteoarthritis from the creation of each database until Jan 20, 2025. INCLUSION CRITERIA: (1) Research object: osteoarthritis. (2) Intervention measures: patients in the treatment group received dietary supplements, while the control group received placebos. (3) Research type: randomized controlled trials (RCTs). DATA EXTRACTION AND ANALYSIS: Two researchers independently examined the literature and retrieved data based on predefined criteria. The information gathered included the first author, year of publication, sample size, participant demographics, length of the follow-up period, intervention and control measures, and inclusion indications. RCTs comparing dietary supplements to placebo with the pain and function subscales of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) among patients with osteoarthritis were included. The optimal dietary supplement was identified based on the total ranking by summing the surface under the cumulative ranking curve (SUCRA) of these two scores. Furthermore, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was used to confirm the quality of the evidence. RESULTS: Overall, 23 studies covering 21 dietary supplements and involving 2455 participants met the inclusion criteria. In the WOMAC pain score, the SUCRA of passion fruit peel extract was 91% (mean difference [MD]: -9.2; 95% confidence interval [CI]: [-16.0, -2.3]), followed by methylsulfonylmethane (89%), undenatured type II collagen (87%), collagen (84%), and Lanconone (82%). The SUCRA (99%) of passion fruit peel extract (MD: -41.0; 95% CI: [-66.0, -16.0]) ranked first in terms of the WOMAC function score, followed by Lanconone (95%), collagen (86%), ParActin (84%), and Lactobacillus casei strain Shirota (83%). The top three total rankings are passion fruit peel extract (95.0%), Lanconone (88.5%), and collagen (85.0%). However, the GRADE revealed low evidence quality. CONCLUSION Passion fruit peel extract was the best supplement for improving WOMAC pain and function scores in patients with osteoarthritis, followed by Lanconone and collagen. However, further large-scale, well designed RCTs are required to substantiate these promising findings. Please cite this article as: Chen CS, Wen L, Yang F, Deng YC, Ji JH, Chen RJ, Chen Z, Chen G, Gu JY. Effects of dietary supplements on patients with osteoarthritis: A systematic review and network meta-analysis. J Integr Med. 2025; 23(4): 357-369.
Humans ; Dietary Supplements ; Osteoarthritis/drug therapy* ; Randomized Controlled Trials as Topic

Objective:To investigate the biological behavior spectrum of platelet-derived growth factor alpha receptor (PDGFRA)-mutant gastrointestinal stromal tumor (GIST), and to compare the clinical values of the Zhongshan method of benign and malignant evaluation with the modified National Institutes of Health (NIH) risk stratification.Methods:A total of 119 cases of GIST with PDGFRA mutation who underwent surgical resection at Zhongshan Hospital, Fudan University from 2009 to 2020 were collected. The clinicopathological data, follow-up records, and subsequent treatment were reviewed and analyzed statistically.Results:There were 79 males and 40 females. The patients ranged in age from 25 to 80 years, with a median age of 60 years. Among them, 115 patients were followed up for 1-154 months, and 13 patients progressed to disease. The 5-year disease-free survival (DFS) and overall survival (OS) were 90.1% and 94.1%, respectively. According to the modified NIH risk stratification, 8 cases, 32 cases, 38 cases, and 35 cases were very-low risk, low risk, intermediate risk, and high risk, and 5-year DFS were 100.0%, 95.6%, 94.3%, and 80.5%, respectively. There was no significant difference in prognosis among the non-high risk groups, only the difference between high risk and non-high risk groups was significant ( P=0.029). However, the 5-year OS was 100.0%, 100.0%, 95.0% and 89.0%, and there was no difference ( P=0.221). According to the benign and malignant evaluation Zhongshan method, 43 cases were non-malignant (37.4%), 56 cases were low-grade malignant (48.7%), 9 cases were moderately malignant (7.8%), and 7 cases were highly malignant (6.1%). The 5-year DFS were 100.0%, 91.7%, 77.8%, 38.1%, and the difference was significant ( P<0.001). The 5-year OS were 100.0%, 97.5%, 77.8%, 66.7%, the difference was significant ( P<0.001). Conclusions:GIST with PDGFRA gene mutation shows a broad range of biological behavior, ranging from benign to highly malignant. According to the Zhongshan method, non-malignant and low-grade malignant tumors are common, the prognosis after surgery is good, while the fewer medium-high malignant tumors showed poor prognosis after surgical resection. The overall biological behavior of this type of GIST is relatively inert, which is due to the low proportion of medium-high malignant GIST. The modified NIH risk stratification may not be effective in risk stratification for PDGFRA mutant GIST.

Objective To investigate the prevalence of thyroid nodules and its influencing factors in adult women from 2017 to 2022 in Chengdu. Methods A total of 4 612 adult female patients with thyroid nodules in the 2nd Affiliated Hospital of Chengdu Medical College, Nuclear Industry 416 Hospital from January 2017 to December 2022 were selected and included in the study group. Among the 4 027 females without thyroid nodules diagnosed by physical examination in the hospital during the same period were matched for age and included in the control group. The differences in general data and thyroid-related serological parameters between the two groups were compared and the influencing factors of thyroid nodules and the epidemiological characteristics of thyroid nodules were analyzed. Results Increased Body mass index (BMI) (OR=1.104), serum anti-thyroglobulin antibodies (TGAb) (OR=1.150) and thyroid peroxidase antibody (TPOAb) (OR=1.143) levels, diabetes mellitus (OR=1.107) and family history of thyroid disease (OR=1.271) were risk factors for thyroid nodules; high quality of life and high education level were protective factors for thyroid nodules. Physical examination screening (59.67%) was the most common way to detect thyroid nodules. Influenced by the COVID-19 epidemi, physical examination screening in the past 3 years accounted for a lower proportion of thyroid nodules found (53.18%) than the pre-epidemic level (64.10%). Conclusion Strengthening thyroid screening and popular science popularization of thyroid nodules in key target populations is the focus of thyroid nodule prevention and treatment in Chengdu in the future.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

Near infrared spectroscopy(NIRS)technology combined with chemometrics algorithms has been widely used in quantitative and qualitative analysis of food and medicine.However,traditional chemometrics methods,especially linear classification methods,often yield unsatisfactory results when addressing multi-class classification problems.Convolutional neural network(CNN)is adept at extracting deep-level features from data and suitable for handling non-linear relationships.The modeling performance of CNN depends on the size and diversity of sample,while the collection and preprocessing of NIRS sample data is often time-consuming and labor-intensive.This study proposed a NIRS qualitative analysis method based on data augmentation strategies and CNN.The data augmentation strategy included two steps.Firstly,applying Bootstrap resampling and generative adversarial network(GAN)methods to augment three NIRS datasets(Medicine,coffee and grape).Secondly,combining the original samples(Y)with the Bootstrap augmented samples(B)and GAN augmented samples(G)to obtain three augmented datasets(Y-B,Y-G and Y-B-G).Based on this,a CNN model structure suitable for these datasets was designed,consisting of 2 one-dimensional convolutional layers,1 max-pooling layer,and 1 fully connected layer.The results showed that compared to the optimal models of partial least squares discriminant analysis(PLS-DA),support vector machine(SVM),and back propagation neural network(BP),the CNN model based on Y-B dataset achieved average accuracy improvements of 3.998%,9.364%,and 4.689%for medicine(Binary classification);the CNN model based on the Y-B-G dataset achieved average accuracy improvements of 6.001%,2.004%,and 7.523%for coffee(7-class classification);and the CNN model based on the Y-B dataset achieved average accuracy improvements of 33.408%,51.994%,and 34.378%for grapes(20-class classification).It was evident that the models established based on data augmentation strategies and CNN demonstrated better classification accuracy and generalization performance with different datasets and classification categories.

Objective To propose strategies for developing clinical predictive models,aiming to assist researchers in conducting standardized clinical prediction model studies.Methods Literature review was conducted to summarize the operational steps and content for developing clinical predictive models.Then,a methodological framework was summarized and refined through expert consultation.Results The 11-step methodological framework for developing clinical predictive models was obtained by synthesizing the experience of 456 clinical predictive modeling studies and expert consultation,and the details were analyzed and elaborated.Conclusions This study presents methodological strategies and recommendations for the development of clinical predictive models,intended to serve as a guide for researchers.

Objective To analyze the clinical and serological typing characteristics of invasive Haemophilus influ-enzae(Hin)infection in children.Methods Clinical data of 34 children with invasive Hin infection admitted to Children's Hospital of Shanxi from 2015 to 2021 were analyzed retrospectively.According to clinical diagnosis,they were divided into meningitis infection group and non-meningitis infection group.General data,symptoms,signs,laboratory serological indicators,and Hin serum typing characteristics of children,as well as differences in inflammatory factor level between the two groups were analyzed.Results Among the 34 patients,22 were males and 12 were females,with a male to female ratio of 1.83∶1.Children aged ≤36 months accounted for 82.35％.The levels of procalcitonin(PCT)(23.71[4.10,77.80])ng/mL and C-reactive protein(CRP)(200.00[164.55,200.00])mg/L in children in the meningitis infection group were higher than those in the non-meningitis group(1.08[0.49,6.00]ng/mL,69.46[48.09,125.63]mg/L,respectively),with statistically significant differences(both P＜0.05).The platelet(PLT)count in the non-meningitis group([312.56±186.81]× 109/L)was higher than that in the meningitis group([183.28±165.67]× 109/L),with statistically significant difference(P＜0.05).There was no statistically significant difference in white blood cell(WBC)count and neutrophil(NEUT)percentage between two groups(both P＞0.05).Among the isolated Hin strains,27,2,and 2 strains were type b(Hib),e and f,respectively;3 strains were not typed;serotype a,c and d strains were not found.There was no statistically significant difference in the distribution of typeable Hin strains between the two groups(x2=0.25,P＞0.05).There was no statistically significant difference in the constituent rate of typeable Hin strains between male and fe-male children(67.74％vs 32.26％,x2=1.42,P＞0.05).Conclusion The majority of invasive Hin infection cases are children under 3 years old,and the predominant strain is type b.CRP and PCT levels of infected children in-creased significantly,while PLT is significantly lower than that of non-infected children,which has certain clinical diagnostic value and can provide effective support for early classified diagnosis and anti-infection treatment of inva-sive infectious diseases combined with other clinical testing items.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.