Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

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 systematically analyze the functional system and construction requirements for infection prevention and control('infection control system'in short)in medical institutions so as to facilitate the effective,standardized and practical construction of the infection control system.METHODS The questionnaires were de-signed based on the relevant criteria and literatures that were released in China with the combination of expect con-sultant and were distributed to experts or professionals involving multiple fields such as hospital infection manage-ment,clinical medical treatment and information technology.The questionnaires were recycled,summarized and analyzed.RESULTS The list of functions of the infection control system(consultative draft)was formulated after review of literatures and expert consultation,including fundamental functions such as data management,case sur-veillance and intervention feedback as well as the advanced functions like target surveillance,occupational protec-tion and interconnection.The surveyed subjects agreed unanimously after the questionnaire survey that all of the function modules and elements enlisted were important,the average score of importance was more than 4 points,the score of coefficient of variable(CV)for importance of the function modules was less than 0.25,indicating that there was high consistency in the opinions among the surveyed subjects.The element of tracing and epidemiologi-cal survey function was adopted and added according to the feedback suggestions from some of the subjects;two function elements including data query and clinical interaction were revised,and the list of function requirements for the infection control systems was finally defined.CONCLUSION The requirements for functions of the infection control system that are determined in the study can provide important bases and data support for the research and standardized development of future infection control system.

Objective:To investigate the clinical efficacy of moxibustion(Mox)combined with low-dose tadalafil(TAD)in the treatment of diabetes mellitus-induced erectile dysfunction(DMED)with the syndrome of Qi deficiency and blood stasis.Meth-ods:According to the inclusion and exclusion criteria,we selected 90 patients with DMED for this trial and equally randomized them into a Mox,a TAD,and a Mox combined with TAD(Mox+TAD)group to be treated by mild Mox applied to the acupoints Zusanli,Sanyinjiao and Yinlingquan qd alt,oral medication with low-dose TAD at 5 mg per dose qd,and combination of the above two thera-pies,respectively,all for 4 weeks.We obtained from the patients their IIEF-5 scores,traditional Chinese medicine(TCM)symptoms scores,Erectile Hardness Scale(EHS)scores,corpus cavernosal hemodynamic indexes,and the peak systolic velocity(PSV),end diastolic velocity(EDV)and resistance index(RI)of the corpus cavernosal arteries before and after treatment,and compared them among the three groups.Results:The total effectiveness rate was significantly higher in the Mox+TAD(90.0％)than in the Mox(46.7％)and TAD groups(60.0％)(P＜0.05).Compared with the baseline,the IIEF-5 and EHS scores were increased,while the TCM symptoms scores decreased in all the three groups after treatment,more significantly in the Mox+TAD group than in the other two(P＜0.05).And the PSV and RI were remarkably increased,while the EDV decreased(P＜0.05)in all the three groups(P＜0.05)after treatment,with PSV even higher in the Mox+TAD than in the Mox and TAD groups(P＜0.05).Conclusion:Moxi-bustion combined with tadalafil has a definite efficacy and safety for the treatment of DMED,which can effectively improve the erectile function of the patients by increasing penile blood supply,benefiting qi and activating blood circulation.

Objective To optimize the design of the existing water conductivity control system for pharmaceutical water equipment of full membrane process so as to solve its problems in precision and long cycle time due to water source,ambient temperature and intermittent working mode.Methods The optimized water conductivity control system was composed of an alkali metering pump,a conductivity sensor and a programmable logic controller(PLC),which used a fuzzy proportional-integral-derivative(PID)controller to regulate the water conductivity of pharmaceutical water equipment of full membrane process,and the particle swarm optimization(PSO)algorithm to optimize the parameters of the fuzzy PID controller.A simulation model was established with MATLAB software to verify the performance of the optimized control system.Results Simulation results showed the optimized control system had reductions in overshoot(by 19％)and adjustment time(by 29％)when compared with the fuzzy PID control system,and enhanced control efficiency effectively.Conclusion The optimized control system optimized by the PSO algorithm improves the quality of produced water,and can meet the demands for rapid and safe production of pharmaceutical water by pharmaceutical water equipment of full membrane process in different conditions.[Chinese Medical Equipment Journal,2025,46(6):14-19]

Objective:To investigate the clinical efficacy of Zhuangdan Yanshi Decoction combined with dapoxetine hydrochlo-ride in the treatment of premature ejaculation with cholestasis and phlegm disturbance.Methods:A total of 120 patients diagnosed with premature ejaculation and treated in the Andrology Outpatient Department of Shaanxi Provincial Hospital of Traditional Chinese Medicine from March to December in 2022 were selected and randomly divided into treatment group and control group,with 60 cases in each group.The incubation period of intravaginal ejaculation(IELT),the Diagnostic Scale of Premature Ejaculation(PEDT),the Premature Ejaculation Assessment Scale(PEP),the 5-item Sexual Function Evaluation of Chinese Premature Ejaculation Patients(CIPE-5)and the improvement of traditional Chinese medicine symptom scores were compared before and after the treatment.And the adverse reactions were recorded as well.Results:A total of 105 cases were ultimately included,with 55 cases in the treatment group and 50 cases in the control group.Measurable improvements in IELT,PEDT scores,PEP scores,CIPE scores and TCM symptom scores had been found after treatment in both of two groups(P＜0.05).Moreover,the improvement in the treatment group was superi-or to that in the control group(P＜0.05).The total effective rate in the treatment group was 89.1％,which was higher than that(84％)in the control group,with no statistically significant difference between the two groups(P＞0.05).The incidence of adverse reactions in the treatment group was 9.1％,which was 24％in the control group.There was significantly difference between two groups(P＜0.05).Conclusion:The combination therapy with Zhuangdan Yanshi Decoction and dapoxetine hydrochloride for premature ejaculation associated with cholestasis and phlegm disturbance syndrome is definite,and it can reduce the side effects of drugs,which is better than oral dapoxetine hydrochloride alone.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Trauma is an important cause of death in young- and middle-aged people. Trauma is comprehensive and includes many surgical specialties, and the surgical techniques of these specialties have long been mature. To reduce the mortality and disability rate of trauma patients, it is necessary to improve trauma management. Trauma has attracted attention in China and trauma treatment and care developed rapidly in recent years. To decrease traumatic mortality and disability rates, our team is committed to building an efficient trauma system in Shaanxi province and has successfully developed a trauma limb salvage map to address the high rates of amputation and disability in patients with limb injuries. This article elaborates on the construction experience of a trauma limb salvage map and its application details in Shaanxi province of China.
Humans ; China ; Limb Salvage/methods* ; Wounds and Injuries/surgery* ; Male ; Extremities/injuries* ; Adult ; Amputation, Surgical ; Middle Aged ; Female

Objective:To explore the feasibility of applying deep learning image reconstruction (DLIR) in low-radiation dose liver dual-energy CT to further improve image quality, diagnostic confidence of lesion, and accuracy of iodine concentration (IC) measurement.Methods:This prospective cohort study enrolled 60 patients scheduled for enhanced liver CT at the First Affiliated Hospital of Anhui Medical University from June 2023 to January 2024. The participants were randomly assigned into the standard dose group and low radiation dose group with 30 cases in each using randomized block method. The standard radiation dose group underwent standard-radiation dose 120 kVp scans during the venous phase, while the low radiation dose group underwent low radiation dose scans with a rapid kVp-switching spectral scanning mode at 80 kVp and 140 kVp. The effective radiation dose (ED) was calculated for both groups. The standard radiation dose group was reconstructed using adaptive statistical iterative reconstruction-V (ASIR-V) algorithm 40% (AR40 120 kVp). The low radiation dose group using high-intensity DLIR (DLIR-H) to reconstructed 40 keV and 50 keV virtual monoenergetic images (VMI) (DH-VMI 40 keV, DH-VMI 50 keV). The image quality of the above three groups was objectively evaluated through the measurement of image noise and calculation of contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) for the liver and portal vein; and the image quality was subjectively scored for image noise, contrast, lesion conspicuity, and diagnostic confidence. In the low radiation dose group, DLIR-H and ASIR-V40% reconstructed iodine maps were used to measure the liver and portal vein of IC values, standard deviations (SD), and coefficients of variation (CV). One-way analysis of variance or Kruskal-Wallis H test was used to compare the differences of subjective and objective image quality among the three groups, and paired t-test was used to compare the differences in measurement indexes between DLIR-H and ASIR-V40% reconstructed iodine maps. Results:The ED in the low radiation dose group [(2.2±0.5) mSv] was reduced by 56.8% compared to the conventional radiation dose group [(5.4±1.4) mSv]. Objective evaluations demonstrated that DH-VMI 40 keV had higher image noise, CNR, and SNR for liver and portal veins compared to AR40 120 kVp ( P<0.001). DH-VMI 50 keV had lower image noise ( P=0.200), with higher CNR and SNR for the liver and portal vein compared to AR40 120 kVp( P<0.001). In subjective evaluation, there was no statistically significant difference in image noise scores between DH-VMI 40 keV and AR40 120 kVp ( P>0.05), while the image noise score for DH-VMI 50 keV was lower than that of AR40 120 kVp ( P<0.05). Both DH-VMI 40 keV and DH-VMI 50 keV had higher scores for contrast, lesion conspicuity, and diagnostic confidence compared to those of AR40 120 kVp ( P<0.05). In the low radiation dose group, there was no statistically significant difference in IC values for the liver and portal vein between the ASIR-V40% and DLIR-H algorithm reconstructed iodine maps ( P>0.05). The SD and CV of liver and portal vein in the DLIR-H reconstructed iodine maps were lower than those in the ASIR-V40% reconstructed iodine maps ( P<0.001). Conclusions:DLIR can effectively reduce the image noise of low-energy (40, 50 keV) VMI, enhance lesion conspicuity and diagnostic confidence, and improve measurement accuracy without affecting IC values.