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: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 analyze the reverse mechano-electric effect of the layered structure of articular cartilage and its influencing factors.Methods The cartilage samples were classified according to their physiological thickness(approximately 0.4 mm for the upper layer,1 mm for the middle layer,and 0.6 mm for the lower layer).Through a non-contact external electric field testing method,how different influencing factors affected the reverse mechano-electric effect of articular cartilage was analyzed.Results When the electric field spacing decreased,water content increased,and in vitro time decreased,the displacement of normal layered cartilage in a non-contact electric field increased by 18,10,15 μm,respectively.In the case of simulated arthritis defects,as the defect depth and radius increased,the overall deviation deflection of articular cartilage gradually decreased by about 7 μm.Conclusions The three-layer cartilage differed in their reverse mechano-electricity effects,showing the greatest deflection in the middle layer at 90％water content,under 7 mm electric field spacing,and after 12 hours ex vivo.

BACKGROUND:The pelvis has abundant trabecular bone content,but the ability of conventional sacroiliac percutaneous fixation to control trabecular bone is limited,leading to fixation failure.Therefore,the development of devices that can more effectively control trabecular bone tension is of significant importance.OBJECTIVE:The mechanical properties of a novel sacroiliac tension screw were investigated using biomechanical testing and numerical modeling analysis,along with an assessment of the reliability of the pull-out force numerical model.METHODS:A mechanical model was established based on the working principle of the novel sacroiliac tension screw.Numerical methods were employed to analyze its pull-out performance,validated through mechanical testing with polyurethane material to assess the reliability of the pull-out force numerical model.Using pelvic specimens,the mechanical effectiveness of the novel sacroiliac tension screw in repairing sacroiliac joint injuries was analyzed under normal standing posture,along with an evaluation of the load stiffness of different pelvic models in the standing position.RESULTS AND CONCLUSION:(1)The average error between the computed values of the numerical model and the measured values was 13.19％,indicating a certain level of validity for the numerical model.(2)The damage to the polyurethane material after the extraction of the screw was less pronounced in the novel screw group.(3)The average effective holding displacement for the novel screw was approximately(9.24±0.27)mm,significantly greater than the average displacement of(1.71±0.57)mm observed with the lag screws.However,the maximum resistance to pullout for the lag screws was significantly higher than that for the novel screws.(4)The novel screw effectively repaired sacroiliac joint injuries.(5)The stiffness after repair of sacroiliac joint injuries was equivalent when using a single novel screw compared to using two lag screws.(6)These results prove that the theoretical model for the maximum resistance to pullout of the screws established in this study has a certain level of validity and can guide the design of them with improved mechanical performance.The novel sacroiliac spiral blade screw can effectively hold trabecular bone and has practical clinical utility.

Objective To analyze the reverse mechano-electric effect of the layered structure of articular cartilage and its influencing factors.Methods The cartilage samples were classified according to their physiological thickness(approximately 0.4 mm for the upper layer,1 mm for the middle layer,and 0.6 mm for the lower layer).Through a non-contact external electric field testing method,how different influencing factors affected the reverse mechano-electric effect of articular cartilage was analyzed.Results When the electric field spacing decreased,water content increased,and in vitro time decreased,the displacement of normal layered cartilage in a non-contact electric field increased by 18,10,15 μm,respectively.In the case of simulated arthritis defects,as the defect depth and radius increased,the overall deviation deflection of articular cartilage gradually decreased by about 7 μm.Conclusions The three-layer cartilage differed in their reverse mechano-electricity effects,showing the greatest deflection in the middle layer at 90％water content,under 7 mm electric field spacing,and after 12 hours ex vivo.

Objective To investigate the clinical prognosis value of the positivity rate of oligoclonal bands(OCB)and immunoglobulin G(IgG)level of cerebrospinal fluid(CSF)in severe encephalitis.Methods A total of 699 cases of encephalitis patients admitted to the Department of Neurology of the First Affiliated Hospital of Air Force Military Medical University,and Xijing 986 Hospital from January 2016 to October 2020 were enrolled.According to the severity of their diseases,these patients were divided into a mild(n=360)group and a severe(n=339)group.CSF and serum samples were collected from the patient at the time of admission,and the differences in cerebrocyte count,glucose contem,glucose content,chlorine content,IgG of CSF and OCB of CSF and serum were compared.According to the GOS score of patients with severe encephalitis at discharge,the patients were divided into good prognosis group(n=259)and poor prognosis group(n=80),and multivariate Logistic regression analysis was used to analyze factors that affected the prognosis of severe encephalitis patients,and the correlation between the OCB and IgG of CSF and prognosis of patients with severe encephalitis.The predictive value of CSF IgG for the prognosis of patients with severe encephalitis was tested,and receiver operating characteristic(ROC)curve was plotted.Results Compared to patients with mild encephalitis,patients with severe encephalitis had a higher proportion of fever,pulmonary infection,status epilepticus,and mechanical ventilation,and were more likely to be complicated by stroke and hydrocephalus,and the differences were statistically significant(χ2=5.319～245.179,all P<0.05).There were significant differences in the positive rate of cerebrocyte count,chlorine content,IgG content and OCB in cerebrospinal fluid between the two groups(Z=-3.623,-4.875,-3.518,χ2=6.581,all P<0.05).CSF OCB and CSF IgG were independent risk factors for poor prognosis in patients with severe encephalitis(Wald χ2=7.295,0.001,all P<0.05).A restrictive cubic spline plot showed a linear relationship between CSF IgG and poor prognosis.The AUC(95%CI)of CSF IgG was 0.754(0.632～0.876).Conclusion The CSF IgG content and positive rate of CSF OCB in patients with severe encephalitis with poor prognosis are higher than those in patients with good prognosis,and detecting these two indicators has certain reference value for the prognosis prediction of patients with severe encephalitis.

Objective To investigate the changes in the levels of D-dimer(D-D),fibrin degradation product(FDP),thrombomodulin(TM),thrombin-antithrombin complex(TAT),tissue plasminogen activator-plasminogen activator inhibitor-1 complex(t-PAIC),and plasmin-alpha 2 plasmin inhibitor complex(PIC)during the treatment of patients with acute myeloid leukemia(AML)and their predictive value for efficacy and prognosis.Methods Thirty-one AML patients initially diagnosed at Guidong People's Hospital of Guangxi Zhuang Autonomous Region from January 2022 to December 2024 were collected as observation group,and 34 healthy medical checkupers were selected as control group.The changes in the levels of the indicators between two groups as well as before,during and after the treatment of observation group were compared,and observation group was divided into remission group and non-remission group according to the efficacy criteria,and the levels of the indicators between two groups were further compared.Risk factors for the efficacy and prognosis of AML patients were analyzed by using Logistic regression analysis.Results Before treatment,the levels of prothrombin time(PT),activated partial thromboplastin time(APTT),D-D,FDP,t-PAIC,PIC,TM and TAT in observation group were significantly higher than those in control group(P＜0.05),whereas there was no significant difference in fibrinogen(Fib)compared with control group(P＞0.05).During the treatment,the levels of t-PAIC and TM in observation group were higher than those before treatment(P＜0.05);After treatment,the levels of PT,D-D,FDP,PIC and TAT in observation group were significantly lower than those before treatment(P＜0.05).After treatment,the levels of PT,D-D,FDP,t-PAIC,PIC,TM and TAT were all lower than those during treatment(P＜0.05).The D-D,FDP,t-PAIC,PIC,TAT and TM levels in non-remission group were all higher than those in remission group,with the t-PAIC and TM levels showing statistical significance(P＜0.05).Binary Logistic regression analysis showed that t-PAIC was an independent risk factor affecting the efficacy and prognosis of AML patients(P＜0.05,OR=1.205,95％CI:1.015-1.430).Conclusion Regular testing of D-D,FDP,TM,TAT,t-PAIC and PIC levels can help to assess the disease changes and efficacy prognosis of AML patients,and provide an important reference for clinical decision-making.

Objective Bibliometric analysis software VOSviewer and CiteSpace were applied to analyze literatures related to acupuncture for myocardial Ischemia/Reperfusion(I/R)injury published in Chinese and English,to explore the status quo,dynamic trend and hot spots in the field,in order to provide reference for future research.Methods Based on the literature on acupuncture and moxibustion for myocardial I/R injury published in CNKI and Web of Science Core Collection database,VOSviewer and CiteSpace software were used to analyze literature publication trends,authors,institutions,countries,journals,keywords and citations,and draw graphs and tables to show the development status of the field and analyze the future development direction.Results Both Chinese and English literatures on the treatment of myocardial I/R injury by acupuncture and moxibustion show an increasing trend,which is one of the academic hotspots with great potential at present.In terms of Chinese literature,Yan Jie is the scholar who has published the most papers,and Hunan University of Traditional Chinese Medicine is the representative of the high production institution.The journal of Acupuncture Research has published the most papers.In terms of English literature,lu sheng-feng is the representative scholar with a high number of publications,Nanjing University of Chinese Medicine is the institution with the largest number of publications,and Evidence-Based Complementary and Alternative Medicine is the journal with the largest number of publications.The authors in the field have weak interinstitutional cooperation and exchange,and their research is mainly from China,with little international collaboration and exchange.At present,acupuncture treatment of myocardial I/R injury covers three aspects:specific acupoints,molecular biological mechanisms and clinical studies,which mainly focus on seven hot spots.Conclusion The bibliometric visual analysis visually demonstrated the current status,hot spots and frontier trends of acupuncture in the treatment of myocardial I/R injury.In the future,it is necessary to strengthen international collaboration,promote exchanges and cooperation between scholars and institutions,and promote the publication of multi-center,large-sample and high-level clinical randomized controlled studies;At the same time,the effect mechanism was further discussed from the perspectives of new molecular biological mechanisms,new intervention measures and point selection,and clinical translational research was carried out.

Objective:To evaluate the efficacy and safety of fecal microbiota transplantation (FMT) for treating functional constipation, analyze the incidence of, and factors that influence, adverse events, and provide scientific evidence for optimizing FMT treatment.Methods:This retrospective, multicenter, single-arm, pre–post real-world study included 1529 patients with functional constipation from four clinical centers. Eligibility criteria comprised meeting the diagnostic criteria for functional constipation, having undergone at least one FMT treatment, complete pre- and post-treatment data available, and age ≥18 years. Patients who had received other interventions affecting gut function within 1 month before treatment and those with severe organic diseases or immune deficiencies were excluded. Applying the above criteria yielded 1529 eligible patients with functional constipation from four medical centers (1405 from the Shanghai Tenth People's Hospital Affiliated to Tongji University, 20 from the Central Hospital of Wuhan, 67 from the Shanxi Bethune Hospital and 37 from the Longgang District People's Hospital of Shenzhen). The study cohort comprised 746 male (48.8%) and 783 female patients (51.2%) of mean age (51.4 ± 17.4) years, mean body mass index (26.4 ± 4.9) kg/m2, and mean duration of disease (15.0 ± 8.3) years. The primary outcomes were the incidence, types, and severity of adverse reactions during treatment, and their impact on patients' quality of life. Secondary outcomes included: (1) the efficacy of FMT in treating constipation. This was assessed based on changes in Patient Assessment of Constipation Symptoms (PAC-SYM) scores, where higher score indicates worse symptom. (2) Subjective satisfaction, evaluated through questionnaires or rating scales, reflecting patients' acceptance of and satisfaction with the treatment, with scores ranging from 1 to 5, where higher scores indicated greater satisfaction. Paired t-tests and Wilcoxon signed-rank tests were used to evaluate changes in symptom scores and biochemical indicators before and after treatment. Logistic regression was performed to analyze factors influencing adverse events, and subgroup analyses to explored differences in efficacy between patient groups.Results:In this cohort of 1529 patients with functional constipation, adverse reactions were primarily mild to moderate (1048/1529,68.5%). They comprised fever in 54 patients (3.5%), dizziness or fatigue in 218 (14.3%), throat discomfort in 806 (52.7%), nausea and vomiting in 166 (10.9%), and abdominal distension or pain in 415 (27.1%). According to multivariate logistic regression analysis, PAC-SYM scores were associated with the rate of adverse reactions, higher scores indicating a lower risk (OR = 0.958, 95% CI: 0.923–0.993, P=0.021). Among the 1529 patients, 274 (17.9%) underwent two or more treatment courses. After one treatment course, the patients' PAC-SYM scores decreased from (37.7 ± 3.2) pre-treatment to (23.7 ± 8.6) (mean difference 14.0 ± 9.1). PAC-SYM scores decreased by (20.7 ± 7.7) after two courses of FMT, and by (19.4 ± 6.3) after three courses. After treatment, 50.7%(775/1529) of patients reported satisfaction scores of ≥4. Adverse reactions impacted satisfaction; specifically, dizziness/fatigue, throat discomfort, and abdominal distension/pain were significantly associated with satisfaction (all P < 0.05). Conclusions:FMT achieved good relief of symptoms of functional constipation and multiple treatment courses have a cumulative effect. Adverse reactions, mainly dizziness/fatigue, throat discomfort, and abdominal distension/pain, had significant negative impacts on patient satisfaction.

Objective To analyze clinical efficacy of pentoxifylline combined with edaravone-dextrocamphenol in the treatment of acute cerebral infarction.Methods From June 2021 to January 2023,120 patients with acute cerebral infarction admitted to our hospital were collected as the research subjects.Patients were grouped into the combination group(n=60)and the single-agent group(n=60)using a random number table method.The single-agent group received intravenous infusion of edaravone-dextrocamphenol(15 mL edaravone-dextrocamphenol was injected within 0.5 h,twice a day),while the combination group received intravenous infusion of pentoxifylline based on single-agent group(0.1 g pentoxifylline was injected within 2 to 3 hours,with a maximum rate of less than 100 mg/h,twice/day).Changes of nerve function,hemodynamics and inflammatory factors before and after treatment were compared between the two groups.Results The total effective rate was significantly higher in the combination group than that of the single-agent group(95.0%vs.81.7%,P＜0.05).Compared with before treatment,the National Institutes of Health Stroke Scale(NIHSS)score,modified Rankin Scale(MRS)score,resistance index(RI),tumor necrosis factor-alpha(TNF-a)and interleukin-6(IL-6)were significantly decreased after treatment in both groups(P＜0.05),and the combined group was more lower(P＜0.05).Basel index,peak systolic flow velocity(Vs),peak diastolic flow velocity(Vd)and average blood flow velocity(Vm)were significantly increased in both groups(P＜0.05),and more higher in the combined group(P＜0.05).No apparent toxic reaction happened during treatment in both groups.Conclusion The combination of pentoxifylline and edaravone-dextrocamphenol has better therapeutic effect on acute cerebral infarction,which can optimize the neurological function and hemodynamics.