OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE To study the pharmacokinetic characteristics of antidepressant active components from Jiaotai pills in healthy subjects. METHODS Eight healthy subjects （3 males and 5 females） were recruited and given a single oral dose of 8.55 g of Jiaotai pills. Venous blood samples were collected before administration （0 h） and at intervals from 0.25 to 36.0 hours post- administration. After treating the plasma samples with protein precipitation， the blood concentrations of the antidepressant active ingredients （coptisine， berberine， magnoflorine， and palmatine） in Jiaotai pills were determined using liquid chromatography- tandem mass spectrometry （LC-MS/MS） method. DAS 2.0 software was employed to calculate the pharmacokinetic parameters of healthy subjects [half-life （t1/2）， peak concentration （cmax）， time to peak concentration （tmax）， area under the concentration-time curve （AUC）， and mean residence time （MRT）] using a non-compartmental model. RESULTS After healthy subjects took Jiaotai pills， the drug-time curve of the four antidepressant active ingredients conforms to a two-compartment model and tmax values were similar， with all reaching peak blood concentrations within 2.00 to 4.00 hours post-administration. However， the t1/2 and MRT of coptisine and berberine were significantly longer than that of magnoflorine and palmatine. There were also significant differences in the AUC and cmax among the four antidepressant active ingredients， with magnoflorine exhibiting markedly higher AUC0-t and cmax compared to the other three components. CONCLUSIONS In this study，LC-MS/MS is used to analyze the pharmacokinetic characteristics of the antidepressant active ingredients from Jiaotai pills in healthy subjects， can provide valuable references for the clinical application of Jiaotai pills.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

With the rising prevalence of chronic diseases and an aging population,China's traditional segmented health-care delivery model is increasingly inadequate for meeting the growing demand for long-term,systematic health management.In response,the"Physician-Pharmacist Co-management"model has emerged,aiming to enhance the quality and continuity of care through close collaboration between physicians and pharmacists.This paper starts from the concept and origin of"Physician-Phar-macist Co-management"model,focusing on its China-specific advantages shaped by national healthcare policies and clinical real-ities.Unlike the internationally recognized Collaborative Drug Therapy Management(CDTM)model,the Chinese approach re-flects local healthcare structures and needs.Using obstructive pulmonary disease(COPD)as a case study,we examine the mod-el's application and value in managing chronic respiratory diseases.Data indicate that,after the implementation of"physician-pharmacist co-management"model in COPD patients,the CAT score decreased by approximately 24％,the annual rate of acute exacerbation-related hospitalizations declined by about 72％,and the proportion of patients with regular pulmonary rehabilitation exercise habits increased by roughly 3.3-fold.Additionally,the percentage of patients without adverse reactions rose from 47.37％to 64.41％,and the vaccination rate increased by about 2.7-fold.These findings demonstrate the model's significant advantages in improving clinical outcomes,enhancing patient adherence,and reducing healthcare costs.Despite benefits,howev-er,the"Physician-Pharmacist Co-management"model in China faces several challenges,including limited public awareness,gaps in pharmacist training,and insufficient policy support.To address these challenges,this study recommends strengthening public education,establishing comprehensive evaluation systems for pharmaceutical professionals,and improving incentive mech-anisms.Overall,the findings suggest that the"Physician-Pharmacist Co-management"model holds considerable promise for im-proving the quality of chronic disease management,enhancing patient adherence,and optimizing healthcare resource utilization in China.

Objective This study aimed to investigate the regulatory effect of electroacupuncture(EA)intervention on the protein kinase B(Akt)/mammalian target of rapamycin(mTOR)/hypoxia-inducible factor 1α(HIF-1α)signaling pathway in the hippocampal tissue of Alzheimer's disease(AD)model mice and its effect on astrocytic glycolytic function,further exploring how EA ameliorates AD-related cognitive impairment.Methods Eighteen APP/PS1 mice were randomly divided into model,EA,and sham EA groups(n=6)using the random number table method.Six wild-type C57BL/6J mice served as the control group.The EA group received EA stimulation at acupoints"Shenshu"(BL23),"Baihui"(GV20),and"Zusanli"(ST36)(administered every other day,20 min per session,for 4 weeks).The sham EA group received identical needle insertions at the same acupoints without electrical stimulation.The control and model groups were only restrained.Cognitive function was assessed using the Morris water maze and Y-maze spontaneous alternation tests.Hippocampal morphology was observed via hematoxylin and eosin staining.Hippocampal β-amyloid peptide 1-42(Aβ1-42)deposition was detected using immunohistochemistry.HIF-1α protein expression,the p-Akt/Akt,and p-mTOR/mTOR ratios were measured using Western blotting.Pyruvate kinase M2(PKM2)and lactate dehydrogenase A(LDHA)activities were quantified using enzyme-linked immunosorbent assay.Hexokinase(HK)activity and L-lactate content were determined using a colorimetric assay.Co-localization of LDHA with the astrocyte marker glial fibrillary acidic protein was quantitatively analyzed using immunofluorescence double-labeling combined with Pearson's correlation coefficient.Results Compared with the control group,the model group mice exhibited cognitive decline,as shown by prolonged escape latency(P<0.01),reduced number of platform crossings,lower time spent in the target quadrant,and decreased spontaneous alternation accuracy(P<0.01).The hippocampal neurons showed cell body swelling,deeper nuclear staining,enlarged intercellular spaces,and increased average optical density of Aβ1-42(P<0.01).The p-Akt/Akt and p-mTOR/mTOR ratios,as well as HIF-1α protein expression,were elevated(P<0.01).PKM2,LDHA,HK,and L-lactic acid levels were significantly increased(P<0.01),and the co-localization coefficient of LDHA with astrocytes was enhanced.Compared to the model group,the EA group of mice showed improved cognitive function.The hippocampal neurons had more intact structures,with a more uniform cell distribution.The average optical density of Aβ1-42 decreased(P<0.01),and the p-Akt/Akt and p-mTOR/mTOR ratios,as well as HIF-1α protein expression,decreased(P<0.01).PKM2,LDHA,HK,and L-lactic acid levels decreased(P<0.05),and the co-localization coefficient of LDHA with astrocytes significantly decreased(P<0.01).No significant improvement was observed in any of the indicators in the sham EA group compared with the EA group.Conclusion EA at"Shenshu"(BL23),"Baihui"(GV20),and"Zusanli"(ST36)ameliorates cognitive dysfunction in AD model mice.The underlying mechanism may involve suppressing the overactivation of the hippocampal Akt/mTOR/HIF-1α signaling pathway,thereby downregulating key glycolytic enzyme activities and reducing abnormal lactate accumulation.Furthermore,the astrocytic glycolytic metabolic pathway may constitute a key therapeutic target for this intervention.

Objective:To investigate the impact of postoperative complications on adverse outcomes following curative-intent resection for gallbladder cancer (GBC).Methods:The multi-center real-world study was conducted. The clinicopathological data of 629 patients with GBC, who were admitted to 14 medical centers including The First Affiliated Hospital of Army Medical University from the national multicenter database of Biliary Surgery Group of Elite Group of Chinese Journal of Digestive Surgery, from April 2020 to April 2024 were collected. There were 225 males and 404 females, aged (64±10)years. Patients underwent open curative-intent resection for GBC. Observation indicators: (1)surgery, postoperative complica-tions and adverse outcomes; (2) analysis of risk factors affecting postoperative adverse outcomes in patients and population attributable fraction (PAF). Missing data in predictor variables were addressed using multiple imputation with chained equations, while cases with missing outcome variables were addressed using the "multiple imputation then deletion (MID)" strategy. The severity of multicollinearity among independent variables was assessed using the variance inflation factor (VIF) test. Multivariable possion regression models with log link and robust error variance were construc-ted incorporating restricted cubic splines (3 knots) to address nonlinear relationships in continuous variables, calculating adjusted relative risk ( RR) with corresponding 95% confidence interval ( CI). Adjusted PAF was calculated for each imputed dataset using the AF package of R software, with subsequent pooling performed according to Rubin's rules. Results:(1) Surgery, postoperative complications and adverse outcomes. All 629 patients underwent curative-intent resection for GBC, of which 143 cases had postoperative complications, including 68 cases of intra-abdominal ascites, 39 cases of pulmonary infection, 21 cases of bile leakage, 12 cases of intra-abdominal hemorrhage, 11 cases of liver failure, 10 cases of pan-creatic fistula, 10 cases of wound infection, 10 cases of gastroparesis, 7 cases of cholangitis, 7 cases of sepsis. The same patient could have more than one kind of complication. Of 629 patients, there were 19 cases of postoperative 90-day death and 11 cases of missing data, 42 cases with post-operative 90-day reoperation and 7 cases with missing data, 44 cases with postoperative 90-day readmission and 3 cases with missing data, 155 cases with prolonged postoperative hospital stay and 3 cases with missing data. (2) Analysis of risk factors affecting the postoperative adverse outcomes in patients and PAF. Results of multivariate analysis showed that pulmonary infection and liver failure were independent risk factors for postoperative 90-day mortality ( RR=3.74, 12.15, 95% CI as 1.18-11.83, 1.98-74.48, P<0.05). Pulmonary infection demons-trated the highest PAF as 4.61% (95% CI as 3.94%-5.28%, P<0.05). Intra-abdominal ascites, pulmonary infection, bile leakage, and intra-abdominal hemorrhage were independent risk factors for post-operative 90-day reoperation ( RR=4.80, 3.62, 3.46, 4.99, 95% CI as 2.49-9.26, 1.42-9.21, 1.34-8.92, 1.55-16.06, P<0.05). Intra-abdominal ascites demonstrated the highest PAF as 8.65% (95% CI as 8.22%-9.08%, P<0.05). Intra-abdominal ascites, bile leakage, and liver failure were independent risk factors for postoperative 90-day readmission ( RR=6.20, 3.33, 14.33, 95% CI as 3.21-11.95, 1.33-8.35, 3.72-55.28, P<0.05). Intra-abdominal ascites demonstrated the highest PAF as 9.11% (95% CI as 8.85%-9.37%, P<0.05). Intra-abdominal ascites, pulmonary infection, bile leakage, liver failure, and wound infection were independent risk factors for prolonged postoperative hospital stay ( RR=2.29, 2.21, 2.26, 2.14, 3.35, 95% CI as 1.63-3.23, 1.41-3.46, 1.32-3.86, 1.11-4.13, 1.70-6.60, P<0.05). Intra-abdominal ascites demonstrated the highest PAF as 6.03% (95% CI as 5.71%-6.35%, P<0.05). Conclusion:Pulmonary infection is the most significant risk factor for postoperative 90-day mortality after curative-intent resection for GBC, while intra-abdominal ascites is the most significant risk factor for postoperative 90-day reoperation, postoperative 90-day readmission, and prolonged postoperative hospital stay.

Objective:To explore the risk factors of adverse events during the perioperative period of transurethral resection of bladder tumor(TURBT)in bladder cancer patients with coronary atherosclerotic heart disease(CAD).Methods:We retrospectively analyzed the clinical data of bladder cancer patients who underwent TURBT in Beijing Anzhen Hospital from June 2022 to September 2024.All patients with bladder cancer and CAD underwent coronary computed tomography angiography(CCTA)for diagnosis and assessment of CAD before surgery.Based on the CCTA results,the patients with bladder cancer and CAD were divided into two groups:those with mild to moderate coronary stenosis and those with severe coronary stenosis.The severe coronary stenosis group was further divided into two subgroups based on whether they received low-molecular-weight heparin(LMWH)bridging therapy or continued their anti-platelet treatment before surgery.Perioperative anticoagulation and antiplatelet strategies were adjusted according to the opinions of the specialists.The incidence of adverse events within 30 days postoperative-ly was followed up and analyzed.Results:A total of 80 bladder cancer patients with CAD who underwent TURBT were included in the study.Among the 80 patients with CAD,55(68.8％)had mild to moder-ate coronary stenosis,and 25(31.2％)had severe coronary stenosis.Compared with those had mild to moderate coronary stenosis,the patients who had severe coronary stenosis had a higher incidence of post-operative bleeding and pulmonary embolism,although the differences were not statistically significant(P＞0.05).However,the incidence of postoperative myocardial infarction was significantly higher in the patients who had severe coronary stenosis(P=0.034).Among the patients with severe coronary stenosis,8(32.0％)received LMWH bridging therapy before TURBT,and 17(68.0％)continued their previous antiplatelet treatment.Compared with those who continued antiplatelet treatment,the patients who re-ceived LMWH bridging therapy had a higher incidence of postoperative bleeding and pulmonary embo-lism,although the differences were not statistically significant(P＞0.05).However,the incidence of postoperative myocardial infarction was significantly higher in the LMWH bridging group(P=0.032).Conclusion:Patients with mild-to-moderate coronary stenosis demonstrate relatively low perioperative risk during TURBT procedures and may safely undergo TURBT following antiplatelet therapy discontinuation.Conversely,those with severe coronary stenosis exhibit significantly higher perioperative risk and require intensive monitoring.In bladder cancer patients with concomitant severe coronary stenosis,perioperative LMWH bridging therapy is associated with increased myocardial infarction risk,whereas continued anti-platelet therapy does not elevate postoperative bleeding risk.Current evidence therefore supports maintai-ning antiplatelet therapy in these patients,with appropriate bleeding risk assessment.

Perception of recurrence risk in cardiovascular disease (CVD) patients plays a significant role in aspects such as their quality of life and treatment adherence. This paper reviews the theoretical foundations of recurrence risk perception, the conceptual origins and developmental process, measurement tools, influencing factors of recurrence risk perception in CVD patients, and research progress of recurrence risk perception in CVD management. The aim is to provide a basis for developing scientifically effective intervention measures for CVD patients in the future.

Objective To evaluate the clinical efficacy of hip-knee-ankle active and passive exercise therapy in patients with early-to mid-stage knee osteoarthritis(KOA).Methods A total of 180 patients with early to mid-stage knee osteoarthritis(KOA)were recruited from the First Affiliated Hospital of Hebei University of Tradi-tional Chinese Medicine between March 2023 and March 2024.Patients were randomly assigned to one of four groups:active movement group,passive movement group,combined movement group,and control group,with 45 patients in each group.The active movement group received hip-knee-ankle active movement therapy daily until the end of follow-up.The passive movement group underwent hip-knee-ankle passive movement therapy three times per week for two weeks.The combined movement group received both active and passive therapies.The control group was administered oral celecoxib capsules(200 mg once daily for two weeks).Joint function was assessed in all four groups before treatment,at two weeks post-treatment,and at 14 weeks post-treatment.The primary outcome measure was the WOMAC joint function score,while secondary outcomes included the WOMAC pain score,stiffness score,and quality of life score(SF-12).Results A total of 160 patients completed the trial,with 39 in the active group,42 in the passive group,40 in the combined group,and 39 in the control group.There were no significant differences in baseline characteristics among the groups(P>0.05).Compared to baseline,the WOMAC scores for function,pain,and stiffness in the passive,combined,and control groups decreased significantly at both 2 and 14 weeks post-treatment(P<0.05),while the SF-12 scores increased significantly(P<0.05).Between 2 and 14 weeks post-treat-ment,the active and combined groups showed further significant decreases in WOMAC function,pain,and stiffness scores(P<0.05)and increases in SF-12 scores(P<0.05).At 2 weeks post-treatment,compared to the control group,the passive and combined groups exhibited significantly lower WOMAC function scores(P<0.05),with no significant difference between the passive and combined groups(P>0.05).By 14 weeks post-treatment,the active and combined groups demonstrated significantly lower WOMAC function scores(P<0.05),with the combined group showing a significantly lower score than the active group(P<0.05).Conclusion The four therapeutic approaches demonstrate a certain degree of efficacy in improving joint function for patients with early and mid-stage KOA.The passive therapy group exhibits superior short-term outcomes,while the active therapy group shows better long-term benefits.The combined therapy group presents notable advantages in both short-term and long-term effi-cacy,although its short-term effectiveness does not surpass that of the passive therapy group.It is recommended for patients with early and mid-stage KOA who have underlying gastrointestinal and cardiovascular conditions.

Objective:To explore the position and length of anchor placement during the repair of anterior talofibular ligament (ATFL) in adolescents with unclosed epiphyseal plates by measuring the relevant data in three-dimensional CT.Methods:A total of 100 three-dimensional CT images of adolescent patients with unclosed epiphyseal plates were collected from the database of the Radiology Center of Renhe Hospital Affiliated to China Three Gorges University from January 1, 2017 to January 1, 2024. There were 69 males and 31 females, aged 12.38±0.90 years (range, 11-14 years), 47 on the left side and 53 on the right side, with a height of 155.72±5.84 cm (range, 145-175 cm), a weight of 48.02±5.93 kg (range, 40-72 kg), and a body mass index (BMI) of 19.77±1.61 kg/m 2 (range, 17.69-24.91 kg/m 2). The built-in measurement tool of the picture archiving and communication system (PACS) was used to measure the angle (α) between the direction of the nail placement and the longitudinal axis of the fibula, the distance between the nail placement point and the posterior edge of the fibula ( d), and the height from the nail placement point to the level of the fibula tip ( h) to evaluate the position and length of the anchor placement. Results:In adolescent patients, α was 47.50°±3.28° (range, 40.00°-56.00°), d was 17.12±1.80 mm (range, 11.70-21.90 mm), and h was 5.21±1.17 mm (range, 3.40-7.90 mm). The α, d and h of male patients were 47.48°±3.13° (range, 42.00°-56.00°), 17.49±1.54 mm (range, 14.45-21.90 mm) and 5.25±1.07 mm (range, 3.70-7.90 mm), respectively. Those of female patients were 47.55°±3.66° (range, 40.00°-53.00°), 16.30±2.07 mm (range, 11.65-20.30 mm) and 5.07±1.56 mm (range, 3.40-7.00 mm), respectively. There was a significant difference in d between male and female patients ( t=3.193, P=0.002), but there was no significant difference in α and h ( t=0.098, P=0.922; t=0.296, P=0.770). Conclusions:The safe range of anchor placement during ATFL anatomical repair in adolescents with unclosed epiphyseal plates is about 3.40-7.90 mm above the tip of fibula and 56°-90° with the longitudinal axis of fibula. Male patients with unclosed epiphyseal plates should choose anchors with a length of 14 mm and shorter, while females should choose anchors with a length of 10.8 mm.