ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

Obesity is a chronic low-grade inflammation and a risk factor for diseases such as diabetes， hypertension， dyslipidemia， and malignant tumors， demonstrating an increasingly grim development situation. The nuclear factor-kappa B （NF-κB） signaling pathway is a key signaling pathway involved in the immune response and inflammatory response. In obese individuals， the expression of NF-κB is overactivated， which leads to abnormal inflammatory responses in the body. Therefore， it is expected to alleviate inflammation and treat obesity by regulating the NF-κB signaling pathway， which has been proven effective by a large number of studies. The available studies on the NF-κB signaling pathway mostly focus on tumors， and there is no systematic review of the mechanism of this pathway in mediating obesity and the traditional Chinese medicine （TCM） treatment. We reviewed the research progress in the pathological and physiological processes of obesity mediated by NF-κB signaling pathway and TCM treatment， aiming to give insights into the clinical treatment of obesity with TCM and provide reference targets and research directions for exploring the biological foundations and the development of new TCM preparations.

Objective: To compare the value of a body shape index (ABSI) and body roundness index (BRI) in predicting non-alcoholic fatty liver disease (NAFLD) among non-obese population, so as to provide a reference for the early identification of populations at high risk of NAFLD. Methods: Adults with a body mass index (BMI) of less than 28 kg/m2 who underwent health check-ups in Xiyuan Hospital of China Academy of Chinese Medical Sciences from 2022 to 2024 were selected as the study subjects. Demographic information, disease history, height, weight, waist circumference, blood pressure, and blood lipid indicators were collected, and ABSI and BRI were calculated. NAFLD was diagnosed using abdominal ultrasound. A multivariable logistic regression model was employed to analyze the relationships between ABSI, BRI and NAFLD among non-obese population. A generalized additive model combined with the penalized spline method was used to fit smooth curves to identify nonlinear relationships, and threshold effects were utilized to determine inflection points. The values of ABSI and BRI in predicting NAFLD among non-obese population were used the receiver operating characteristic (ROC) curve. Results: A total of 1 195 individuals were surveyed, including 345 males (28.87%) and 850 females (71.13%). A total of 348 cases of NAFLD were detected among the non-obese population, with a detection rate of 29.12%. The adjusted ABSI (sABSI) in the NAFLD group and non-NAFLD group were 7.95±0.33 and 8.08±0.34, while the BRI were 3.35±0.79 and 4.15±0.64, respectively, with statistically significant differences between the two groups (both P<0.05). Multivariable logistic regression analysis showed that, after adjusting for demographic information, disease history, blood pressure, and blood lipid indicators, both sABSI (OR=1.932, 95%CI: 1.184-3.158) and BRI (OR=1.594, 95%CI: 1.071-2.360) were significantly associated with NAFLD among non-obese population. Nonlinear positive correlations were observed between sABSI, BRI, and NAFLD among non-obese population. When sABSI≤8.46 and BRI≥2.72, both indices were positively associated with NAFLD. The area under the ROC curve for ABSI and BRI in predicting NAFLD risk among non-obese population were 0.619 and 0.782, respectively, with optimal cut-off values of 0.082 and 3.656, respectively. Conclusions ABSI and BRI show a non-linear relationship with NAFLD among non-obese population. BRI demonstrates relatively better performance in predicting NAFLD risk among this population and can serve as an auxiliary indicator for the early identification of NAFLD among non-obese population.

The National Institute for Health and Care Excellence(NICE)first updated its 2013 Health Technology Evaluations Guidelines in 2022,followed by further minor adjustments in 2023.This round of updates primarily focuses on five key areas:mea-suring the value of health technologies,understanding and improving the evidence base,structured decision-making,addressing challenging diseases and technologies,and ensuring consistency in methods across evaluation and review projects.It outlines the up-date process and major changes,providing an analysis of these key points with the aim of offering valuable insights and methodologi-cal references for health technology assessment in China.

BackgroundModified electroconvulsive therapy （MECT） is a common front-line strategy widely used in psychiatric practice， and the optimal first stimulus dosage in MECT is usually estimated clinically based on the factors influencing the patient's initial seizure threshold （IST）. However， previous studies on the influencing factors of IST have mostly suffered from limitations such as small sample sizes and single-dimensional research perspectives. ObjectiveTo explore the factors influencing IST in MECT for patients with mental disorders， so as to provide references for stimulus dosing strategies in MECT for the patients. MethodsA retrospective study was used to include 1 446 inpatients fulfilling the diagnostic criteria for any specific mental disorder listed in the ICD-10 and receiving MECT at Shandong Daizhuang Hospital from January 1， 2021 to August 1， 2023. Their general and clinical data were collected， including IST， psychiatric diagnostic categories， gender， ethnicity， age， body weight， body mass index （BMI）， course of disease， family history of psychiatric disorders， first episode status， use of antiepileptic drugs the day before treatment， use of benzodiazepines the day before treatment， and previous MECT treatment history. Pearson correlation analysis was utilized to test the correlation of IST with age， height， body weight， BMI， and course of disease， and stepwise multivariate linear regression analysis was performed to identify the factors affecting IST. ResultsIST yielded statistical difference among patients in terms of gender， first episode status， use of antiepileptic drugs the day before treatment， and use of benzodiazepines the day before treatment （t=2.256， -3.059， -2.136， -3.006， P<0.05 or 0.01）. IST in patients of different ages and psychiatric diagnostic categories also demonstrated statistical difference （F=913.120， 6.212， P<0.01）. Within young population， IST varied significantly based on the psychiatric diagnostic categories （F=2.986， P<0.05）. Correlation analysis indicated that IST was positively correlated with age， body weight， BMI and course of disease （r=0.886， 0.055， 0.184， 0.456， P<0.05 or 0.01）， and negatively correlated with height （r=-0.183， P<0.01）. Stepwise multivariate linear regression analysis revealed that age， gender， and body weight were influencing factors of IST （β=0.888， -0.049， -0.035， P<0.01）. ConclusionsAge， gender and body weight may be factors influencing IST in MECT for patients with mental disorders. ［Funded by Key R&D Plan Projects of Jining City in 2024 (number, 2024YXNS202）］

Objective To study the current status of the randomized controlled trial(RCT)outcome indicators of acupuncture and moxibustion in the treatment of chronic fatigue syndrome(CFS);To provide guidance and references for clinical research and protocol design.Methods RCT of acupuncture and moxibustion for CFS were retrieved from CNKI,Wanfang Data,VIP,SinoMed,PubMed,Embase,Web of Science databases from January 1,2015 to December 9,2024.Through literature screening and data extraction,Excel 2019 was used to make a descriptive analysis of the basic characteristics,diagnostic criteria,intervention measures,classification of outcome indicators,use frequency and evaluation time points of the included studies.Origin2021 software was used to draw bubble charts for visual display.Results Totally 119 RCT were included,involving 8 445 subjects,5 diagnostic criteria of Western medicine,5 diagnostic criteria of TCM,and 6 outcome indicators,namely clinical symptoms/signs,symptoms/syndrome of TCM,physical and chemical examination,quality of life,safety evaluation,and patient satisfaction.A total of 58 outcome indicators were reported,with a cumulative frequency of 430 times.Conclusion The RCT of acupuncture and moxibustion treatment of CFS have some problems,such as incomplete baseline assessment,lack of sample size calculation basis,high risk of bias,ignorance of primary and secondary indicators in the selection of outcome indicators,numerous indicators selection and measurement points,lack of long-term follow-up,inconsistent evaluation criteria for TCM syndrome efficacy,and insufficient attention to health economics evaluation and safety outcome indicators.

Objective:To evaluate the efficacy and safety of eculizumab in treating acute attacks of aquaporin-4 antibody(AQP4-IgG)positive neuromyelitis optica spectrum disorder(NMOSD).Methods:Six patients with AQP4-IgG-positive NMOSD treated with eculizumab at the Affiliated Hospital of Qingdao University from August 2023 to April 2024 were included.The patients' clinical characteristics, changes in scores of neurological function, pain and spasm before and after eculizumab treatment, and adverse drug reactions during the treatment period were described, and the data were subjected to Friedman test using SPSS 25.0.Results:The median score of expanded disability status scale in the six patients decreased from 3.25 before treatment to 1.25 after treatment, and the difference was statistically significant ( F=44.77, P<0.01).The functional status score showed noticeable improvement as early as week 1, demonstrating greater sensitivity to treatment response.Three patients experienced moderate to severe pain before treatment, with a mean pain score of 6, which reduced to 4.67 and 1.33 at week 2 and 6, respectively( F=29.17, P<0.05).Two patients reported spasms before treatment, with a mean score of 3.00, which decreased to 2.00, 1.50, and 1.00 at week 2, 3, and 6 after treatment, respectively( F=18.00, P>0.05).No serious adverse reactions were reported during the treatment. Conclusion:Eculizumab can effectively improve the neurological function and alleviate pain in patients with AQP4-IgG-positive NMOSD during acute attacks, and demonstrate good safety.

Objective:To evaluate the efficacy and safety of eculizumab in treating acute attacks of aquaporin-4 antibody(AQP4-IgG)positive neuromyelitis optica spectrum disorder(NMOSD).Methods:Six patients with AQP4-IgG-positive NMOSD treated with eculizumab at the Affiliated Hospital of Qingdao University from August 2023 to April 2024 were included.The patients' clinical characteristics, changes in scores of neurological function, pain and spasm before and after eculizumab treatment, and adverse drug reactions during the treatment period were described, and the data were subjected to Friedman test using SPSS 25.0.Results:The median score of expanded disability status scale in the six patients decreased from 3.25 before treatment to 1.25 after treatment, and the difference was statistically significant ( F=44.77, P<0.01).The functional status score showed noticeable improvement as early as week 1, demonstrating greater sensitivity to treatment response.Three patients experienced moderate to severe pain before treatment, with a mean pain score of 6, which reduced to 4.67 and 1.33 at week 2 and 6, respectively( F=29.17, P<0.05).Two patients reported spasms before treatment, with a mean score of 3.00, which decreased to 2.00, 1.50, and 1.00 at week 2, 3, and 6 after treatment, respectively( F=18.00, P>0.05).No serious adverse reactions were reported during the treatment. Conclusion:Eculizumab can effectively improve the neurological function and alleviate pain in patients with AQP4-IgG-positive NMOSD during acute attacks, and demonstrate good safety.

The National Institute for Health and Care Excellence(NICE)first updated its 2013 Health Technology Evaluations Guidelines in 2022,followed by further minor adjustments in 2023.This round of updates primarily focuses on five key areas:mea-suring the value of health technologies,understanding and improving the evidence base,structured decision-making,addressing challenging diseases and technologies,and ensuring consistency in methods across evaluation and review projects.It outlines the up-date process and major changes,providing an analysis of these key points with the aim of offering valuable insights and methodologi-cal references for health technology assessment in China.

Objective To study the current status of the randomized controlled trial(RCT)outcome indicators of acupuncture and moxibustion in the treatment of chronic fatigue syndrome(CFS);To provide guidance and references for clinical research and protocol design.Methods RCT of acupuncture and moxibustion for CFS were retrieved from CNKI,Wanfang Data,VIP,SinoMed,PubMed,Embase,Web of Science databases from January 1,2015 to December 9,2024.Through literature screening and data extraction,Excel 2019 was used to make a descriptive analysis of the basic characteristics,diagnostic criteria,intervention measures,classification of outcome indicators,use frequency and evaluation time points of the included studies.Origin2021 software was used to draw bubble charts for visual display.Results Totally 119 RCT were included,involving 8 445 subjects,5 diagnostic criteria of Western medicine,5 diagnostic criteria of TCM,and 6 outcome indicators,namely clinical symptoms/signs,symptoms/syndrome of TCM,physical and chemical examination,quality of life,safety evaluation,and patient satisfaction.A total of 58 outcome indicators were reported,with a cumulative frequency of 430 times.Conclusion The RCT of acupuncture and moxibustion treatment of CFS have some problems,such as incomplete baseline assessment,lack of sample size calculation basis,high risk of bias,ignorance of primary and secondary indicators in the selection of outcome indicators,numerous indicators selection and measurement points,lack of long-term follow-up,inconsistent evaluation criteria for TCM syndrome efficacy,and insufficient attention to health economics evaluation and safety outcome indicators.