Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Objective To compare the clinical characteristics of pneumococcal meningitis in different age groups, and to provide a basis for early diagnosis of pneumococcal meningitis. Methods Cerebrospinal fluid and/or serum samples were collected from 1742 suspected cases of meningitis in Baoji, Shaanxi Province from August 2013 to July 2019. Streptococcus pneumoniae was detected by isolation culture and real-time fluorescence quantitative polymerase chain reaction. Retrospective analysis of clinical manifestations, biochemical indicators and other information of laboratory confirmed cases was conducted by χ² test or Fisher's exact test. Results A total of 1742 samples of encephalitis or meningitis cases were detected, and 41 cases were confirmed as laboratory-confirmed Streptococcus pneumoniae infection. Among them, there were 12 cases (29.27%) in the infant group, 14 cases (34.15%) in the child group, and 15 cases (36.59%) in the adult group. The proportion of the adults with headache was significantly higher than that of the infants (χ²=11.408，P＜0.017). The proportion of the adults with consciousness disorder, elevated white blood cells and elevated neutrophils were significantly higher than those in the infant and the child groups（Fisher's exact test, P＜0.017；χ² =6.428，P＜0.017；χ² =10.898，P＜0.017；χ² =6.421，P＜0.017；χ² =9.758，P＜0.017；χ² =7.744，P＜0.017). The proportion of the infants with cerebrospinal fluid turbidity was significantly higher than that of the children (Fisher's exact test，P＜0.017). The proportion of the infants with decreased white blood cells and reduced glucose in cerebrospinal fluid was significantly higher than that of the children group and the adult group（Fisher's exact test, P＜0.001；Fisher's exact test, P＜0.001；Fisher's exact test, P＜0.017; Fisher's exact test, P＜0.017). Conclusion Most adult patients with pneumococcal meningitis have headache and consciousness disorders, with significantly increased proportion of white blood cells and neutrophils. Infant patients tend to have cloudy appearance of cerebrospinal fluid, leukopenia in blood, and decreased glucose in cerebrospinal fluid.

ObjectiveTo observe the effect of rehabilitation robot training on abdominal muscles thickness and balance ability in children with hemiplegia. MethodsFrom October, 2024 to December, 2025, 58 children with hemiplegia were admitted to Beijing Bo'ai Hospital and randomly divided into control group (n = 29) and experimental group (n = 29). Both groups received conventional rehabilitation treatment, and the experimental group received rehabilitation robot training in addition, for four weeks. The thickness of bilateral external oblique, internal oblique and transversus abdominis, Berg Balance Scale (BBS) score, the time of Timed Up and Go Test (TUGT), the center of pressure (COP) ellipse area, and self-selected walking speed (SWS) and maximum walking speed (MWS) of 10-meter walk test were compared before and after training. ResultsThree cases dropped out in each group. After training, the thickness of the external oblique, internal oblique and transverse abdominis on the hemiplegic side increased significantly in the experimental group (|t| > 7.280, P < 0.001, Cohen's d = 1.43~2.01), and was better in the experimental group than in the control group (|t| > 2.895, P < 0.01, Cohen's d = 0.80~1.60); the BBS score increased in both groups (|t| > 6.667, P < 0.001, Cohen's d = 1.30~4.06), and was better in the experimental group than in the control group (t = -2.721, P < 0.01, Cohen's d = 0.75). The time of TUGT decreased in both groups (t > 5.790, P < 0.001, Cohen's d = 1.14~2.68), and was better in the experimental group than in the control group (t = 2.290, P < 0.05, Cohen's d = 0.63). The SWS and MWS increased in both groups (|Z| > 2.910, P < 0.01, r = 0.40~0.68), and were better in the experimental group than in the control group (|Z| > 2.912, P < 0.05, r = 0.40~0.45), and the differences remained significant after correction. ConclusionRehabilitation robot training can improve the thickness of external oblique, the internal oblique and transversus abdominis muscles on the hemiplegic side in children with hemiplegia, and improve their balance and walking functions.

Objective To investigate the registration rate and trend of pulmonary tuberculosis complicated with diabetes mellitus (PTB-DM) in Wuhan from 2020 to 2024, and to provide scientific evidence for formulating PTB-DM prevention and control policies. Methods PTB-DM case data in Wuhan (2020-2024) were collected through the Infectious Disease Registration and Management Information System. Joinpoint regression model was employed to analyze the trend of registration rates of PTB-DM among the general population and across different regions, genders, and age groups. ARIMA model was used to predict the short-term prevalence of PTB-DM. Results Among 26275 pulmonary tuberculosis cases registered in Wuhan (2020-2024), 2669 cases (10.16%) were PTB-DM. The average annual registration rate of PTB-DM was 3.96/100,000, increasing from 2.74/100,000 in 2020 to 5.40/100,000 in 2024 (APC=19.07%, 95% CI:12.99%-26.92%, P<0.001). The PTB-DM registration rates showed an upward trend across different regions, genders, and age groups in Wuhan, with higher registration rates observed in near urban area, males, and individuals aged 60~64 and 65 years and above (χ²=99.566, P<0.001; χ²=781.891, P<0.001; χ²=2211.930, P<0.001). ARIMA model predicted that the prevalence of PTB-DM in Wuhan would remain stable and fluctuating in the short time. Conclusion PTB-DM registration rate in Wuhan increases from 2020 to 2024. Near urban area, males, and elderly populations are high risk groups. Future efforts should focus on strengthening the prevention and control of PTB-DM among these populations.

Objective To analyze the occurrence status of low blood pressure (BP) in patients with refractory heart failure (RHF) and its relationship with comorbidities. Methods A retrospective analysis was conducted on the clinical data of 360 patients with RHF who were hospitalized in department of cardiology of Affiliated Nantong Hospital of Shanghai University from May 2021 to May 2025. These patients were divided into the RHF with BP group and the RHF group based on their blood pressure at admission. The general data and comorbidities were compared between both groups. Multivariate logistic regression analysis was used to identify the risk factors for coexisting BP. Results The heart rate (HR), N-terminal pro-B-type natriuretic peptide (NT-proBNP), blood urea nitrogen, high-sensitivity cardiac troponin T, right atrial diameter, proportion of cardiac function grade IV, use rate of diuretics and prevalence rate of dilated cardiomyopathy (DCM) in the RHF with BP group were higher while the high-density lipoprotein cholesterol (HDL-C), albumin, left ventricular ejection fraction, use rate of lipid-lowering drugs and prevalence rate of coronary heart disease were lower compared to the RHF group, and the differences were statistically significant (P<0.05). Multivariate logistic regression analysis suggested that increased HR (OR=1.685, 95%CI: 1.106-2.569), increased NT-proBNP (OR=1.772, 95%CI: 1.138-2.759), decreased HDL-C (OR=0.605, 95%CI: 0.400-0.917) and DCM (OR=1.956, 95%CI: 1.176-3.255) were independent risk factors affecting BP in RHF patients (P<0.05). Conclusion The incidence rate of low blood pressure in elderly RHF patients is about 19.17%. Increased heart rate, increased NT-proBNP, decreased HDL-C and dilated cardiomyopathy are closely linked to the occurrence of low blood pressure, and they can be used as clinically related factors to identify patients at high risk of low blood pressure.

ObjectiveTo analyze the current status of traditional Chinese medicine （TCM） prediction model research for emerging acute infectious diseases， in order to provide reference for subsequent model construction and optimization. MethodsEight databases， including PubMed， Cochrane Library， and Embase， were systematically searched to comprehensively collect Chinese and English literature on TCM prediction models for emerging acute infectious diseases. The search period ranged from database inception to July 5， 2024. Reporting quality compliance was evaluated using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis—Traditional Chinese Medicine （TRIPOD-TCM） guideline. Risk of bias and applicability were assessed using the Prediction Model Risk of Bias Assessment Tool （PROBAST）. ResultsA total of 21 studies were included， comprising 11 early warning model studies， 5 diagnostic model studies， 3 prognostic model studies， and 2 prescription prediction model studies， involving 84 models in total. The diseases involved were mainly viral infectious diseases such as coronavirus disease 2019 （COVID-19） and hepatitis B. The most frequently applied TCM theory was the "five movements and six climates" theory. The most commonly used modeling method was neural network-based approaches. The most frequently reported predictive factors were meteorological variables， including daily mean temperature， wind speed， precipitation， relative humidity， and vapor pressure. In terms of reporting quality， the included studies showed poor item-level compliance， with only 13 sub-items achieving compliance rates above 50%. Overall compliance ranged from 27% to 59% across studies. Although the included studies showed relatively good applicability， all were assessed as having a high risk of bias. The main sources of bias included inappropriate handling of missing data， absence of calibration methods， and unreasonable validation strategies， indicating deficiencies across multiple stages of model development. ConclusionCurrent research on TCM prediction models for emerging acute infectious diseases exhibits distinctive modeling characteristics. These models are based on traditional TCM theories such as the "five movements and six climates"， incorporate TCM-specific features as predictive variables， and use TCM syndromes as outcomes. However， they generally suffer from low reporting compliance and a high risk of bias. Future studies should systematically design model development and validation processes， adhere to TRIPOD-TCM reporting standards， and apply PROBAST or develop dedicated bias risk assessment tools for TCM prediction models to improve methodological quality and promote their translation into clinical practice.

To promote the high-quality development of healthcare in the highland areas and to enable traditional Chinese medicine(TCM)to make a more prominent contribution to the healthcare of the people in these areas,it is imperative to clarify the roles of TCM in the formation of the healthcare system in the past and present,as well as the direction of innovative development of TCM in the plateau in the future.To this end,this paper first systematically reviews the literature to summarize the influence of TCM on the cultural background,theoretical framework,and practical system of Tibetan medicine during its origin,development,and maturation;then,through the example of typical cases,it elaborates on the direct practical applications of TCM in the prevention and treatment of a series of highland diseases from the perspectives of pathogenesis,therapeutic principles,unique drugs,and techniques;finally,it deeply reflects on a series of problems restricting the integration,inheritance,and innovative development of TCM in the highland areas and puts forward targeted suggestions to enable TCM to serve and safeguard the health of people living in the plateaus better together with the local ethnic medicine.

Objective To explore the value of analysis on the incidence of healthcare-associated infection(HAI)based on disease diagnosis-related grouping(DRG),case mix index(CMI),and relative weight(RW).Methods All discharged cases,DRG and HAI status in a tertiary first-class general hospital from January 1 to December 31,2023 were analyzed retrospectively.Incidences of HAI in different departments were adjusted and compared by CMI.Incidences of HAI in different DRG groups were adjusted by RW.Results Among the 47 695 cases included in the analysis,757 were HAI cases,including 225 DRG groups.The department of critical care medicine had the highest incidence of HAI(11.98％).After CMI adjustment,departments with higher incidence of HAI were main-ly the department of respiratory and critical care medicine(3.96％),department of critical care medicine(3.04％),and department of neurology(2.85％),et al.DRG groups with the top five high incidence of HAI were AH11(tracheotomy and with ventilator support ≥96 hours or extracorporeal membrane oxygenation[ECMO],accompa-nied by major complications and comorbidity[MCC],50.00％),BC29(ventricular shunt and revision surgery,31.43％),BB21(craniotomy other than trauma,accompanied by MCC,27.56％),BB11(craniotomy of brain trauma,accompanied by MCC,26.32％),and GB1A(major surgery of esophagus,stomach,and duodenum,accompanied by major or moderate complications and comorbidity,16.00％).After RW adjustment,the DRG groups with the top five high incidence of HAI were ES21(respiratory system infection/inflammation,accompanied by MCC,5.89％),BR21(cerebral ischemic disease,accompanied by MCC,5.17％),FR11(heart failure,shock,accompanied by MCC,4.80％),BC29(4.57％)and AH11(3.57％).Conclusion Analyzing the incidence of HAI based on CMI and RW can help to identify key departments and disease groups for infection prevention and control,and provide reference for precise prevention and control of HAI in the new era.

From 2019 to 2023, a total of 30.8602 million doses of non-National Immunization Program (non-NIP) vaccines were administered in Shaanxi Province, averaging 1 561 doses per 10 000 population. The annual administration of non-NIP vaccines increased from 4.359 1 million doses in 2019 to 7.858 2 million doses in 2023, with their proportional representation among all vaccines rising from 30.82% to 55.15%( χ2 trend=2 440 581.54, P<0.001). The administration rate per 10 000 population increased from 1 105 doses to 1 986 doses during this period( χ2 trend=373.10, P<0.001). Concurrently, the substitution rate of non-NIP vaccines for National Immunization Program vaccines rose from 4.94% in 2019 to 16.11% in 2023.

ObjectiveTo explore the current situation of forensic ethics practice and education by designing a questionnaire on forensic ethics， with a view to exploring the path of forensic ethics education construction. MethodsA total of 667 valid questionnaires were collected using the online survey method， basically covering various regions across the country and all sub-specialties of forensic medicine. Descriptive analysis was used to analyze the relevant data. ResultsMost practitioners had relevant ethical reflections in the process of forensic practice. 69.12% of the respondents indicated that they had studied the relevant rules， but approximately half stated that there were no corresponding ethical norms or standard operating manuals. The specific behaviors violating ethics in different units were diverse. 23.04% of the respondents reported that they had encountered unethical behaviors， but only 4.9% of them reported such violations. In terms of forensic ethics education， 87.75% of the respondents believed that there were issues with the current model of forensic ethics education. Meanwhile， the respondents showed a high degree of recognition for receiving forensic ethics education， with 84.15% of respondents expressing willingness to participate in relevant courses. More than half of respondents were willing to participate in forensic ethics education during undergraduate studies， new employee training， and regular post-employment training. ConclusionCurrently， there is a problem of ethical neglect in forensic work in China. Combining ethics courses with professional courses at the practitioner training stage and providing regular training at the practice stage are effective measures to popularize forensic ethics knowledge， enhance ethical awareness， and improve the quality of practice.