BACKGROUND:Research suggests that exercise interventions may be more advantageous than pharmacologic treatments or dietary restriction alone for fat loss,but fewer studies have simultaneously examined the effects of training modalities and training cycles on visceral and subcutaneous fat in obese populations. OBJECTIVE:To investigate the impact of training modalities and training cycles on visceral and subcutaneous fat in recessive obesity female college students. METHODS:Sixty-three female college students with hidden obesity(body mass index<24 kg/m2 and body fat content percentage≥30%)were recruited from Zhengzhou College of Commerce and Industry,and were randomly divided into a high-intensity intermittent training group(n=32)and a moderate-intensity continuous training group(n=31)using the lottery method.Subjects in both groups performed exercise training of corresponding intensity on a running platform and ensured that the exercise volume of both groups was equal,3 times per week,every 4 weeks as one training cycle for 16 weeks.Before training and at the end of each training cycle,subjects'visceral fat,subcutaneous fat,and overall fat were measured using the corresponding test devices. RESULTS AND CONCLUSION:The repeated measures F results indicated that the main effects of training cycles on visceral fat area,visceral fat index,abdominal subcutaneous fat thickness,percentage of body fat and body mass index were significant,while the main effects of training modalities were significant for subcutaneous fat thickness in the triceps brachii and scapula regions.All the interaction effects between training modalities and training cycles were significant(P<0.05).Results from the simple effect tests revealed that the significant simple effects of training modalities at the 4th and 12th weeks for visceral fat area and visceral fat index,at the 8th and 12th weeks for subcutaneous fat thickness in the triceps brachii,scapula region,and abdominal regions,and at the 8th week for the percentage of body fat and body mass index.Simple effects of training cycles were significant for all measures within each group.(3)The results of multiple comparison tests indicated that in the high-intensity intermittent training group,visceral fat area,visceral fat index,percentage of body fat,body mass index and abdominal subcutaneous fat thickness decreased sequentially at the 4th,8th,12th,and 16th weeks,and subcutaneous fat thickness of the triceps brachii and scapula decreased sequentially at the 8th,12th,and 16th weeks(P<0.05).In the moderate-intensity continuous training group,visceral fat area,visceral fat index,subcutaneous fat thickness of the triceps brachii and scapula,percentage of body fat and body mass index decreased successively at the 8th,12th,and 16th weeks,while abdominal subcutaneous fat thickness decreased successively at the 4th,8th,12th,and 16th weeks(P<0.05).To conclude,both training modalities and training cycles are factors influencing visceral and subcutaneous fat in recessive obesity female college students.Training modality primarily affects subcutaneous fat in the triceps brachii and scapular region,but the fat loss effects may converge over a longer training cycle;training cycle primarily affects visceral fat area,visceral fat index,abdominal subcutaneous fat,body fat content,and body mass index.

Objective To develop a core outcome set(COS)for treatment of progressive vitiligo in Uyghur medicine,and to standardize the selection and reporting of outcome measures in relevant studies.Methods Based on the existing core outcome domain set of randomized controlled trials for vitiligo,additional outcome indicators reflecting the advantages and characteristics of Uyghur medical treatment were developed.Specific indicators for Uyghur medical treatment of progressive vitiligo were collected through literature review and semi-structured questionnaire surveys,and then a list of indicators were formed.The Delphi survey and consensus meetings were used to select core indicators.Results A total of 54 studies were included,and 86 questionnaires were collected.Through literature review and questionnaire surveys,a list of 28 indicators were obtained.After two rounds of Delphi survey and one consensus meeting,12 outcome indicators in 7 domains were finally determined,including vitiligo lesion area,repigmentation,disease control time,maintenance of repigmentation,recurrence rate,immune indicators,psychological health,patients' quality of life,adverse events,adverse reaction incidence,liver and kidney function monitoring,and Uyghur medicine syndrome differentiation of mucus.Additionally,some measurement tools for certain indicators were recommended.Conclusion The development of the COS for vitiligo treatment in Uyghur medicine helps to comprehensively evaluate the efficacy of Uyghur medicine,and will provide a model for establishing efficacy evaluation methods that conform to the characteristics of ethnic minority medicine.

Background: and Purpose Limited evidence exists on the effectiveness of endovascular treatment (EVT) for acute posterior circulation tandem lesion (PCTL). This study aimed to explore the role of extracranial vertebral artery (VA) stenting in patients with PCTL stroke undergoing EVT. Methods: Individual patient data were pooled from the BASILAR (EVT for Acute Basilar Artery Occlusion Study) and PERSIST (Posterior Circulation Ischemic Stroke) registries. Patients with PCTLs who underwent EVT were included in the present cohort and divided into the stenting and nonstenting groups based on the placement of extracranial VA stents. The primary efficacy outcome was the modified Rankin Scale (mRS) scores at 90 days and 1 year. Safety outcomes included 24-hour symptomatic intracranial hemorrhage (sICH) and all-cause mortality at 90 days and 1 year post-surgery. Results: A combined dataset of 1,320 patients with posterior circulation artery occlusion, including 263 (19.9%) with tandem lesions, of whom 217 (median age, 65 years; 82.9% male) met the inclusion criteria for the analysis. The stenting group had 84 (38.7%) patients, while the non-stenting group had 133 (61.3%). After adjustment for the potential confounders, extracranial VA stenting was associated with favorable shifts in mRS scores at both 90 days (adjusted common odds ratio [OR], 2.30; 95% confidence interval [CI], 1.23–4.28; P<0.01) and 1 year (adjusted OR [aOR], 2.04; 95% CI [1.05–3.97]; P=0.04), along with lower rate of mortality at both 90 days (aOR, 0.45; 95% CI [0.21–0.93]; P=0.01) and 1 year (aOR, 0.36; 95% CI [0.16–0.79]; P=0.01), with no significant difference in sICH incidence (aOR, 0.35; 95% CI [0.06–1.98]; P=0.24). Conclusion Extracranial VA stenting during EVT may improve functional outcomes and reduce mortality in patients with PCTL strokes.

Background: and Purpose Limited evidence exists on the effectiveness of endovascular treatment (EVT) for acute posterior circulation tandem lesion (PCTL). This study aimed to explore the role of extracranial vertebral artery (VA) stenting in patients with PCTL stroke undergoing EVT. Methods: Individual patient data were pooled from the BASILAR (EVT for Acute Basilar Artery Occlusion Study) and PERSIST (Posterior Circulation Ischemic Stroke) registries. Patients with PCTLs who underwent EVT were included in the present cohort and divided into the stenting and nonstenting groups based on the placement of extracranial VA stents. The primary efficacy outcome was the modified Rankin Scale (mRS) scores at 90 days and 1 year. Safety outcomes included 24-hour symptomatic intracranial hemorrhage (sICH) and all-cause mortality at 90 days and 1 year post-surgery. Results: A combined dataset of 1,320 patients with posterior circulation artery occlusion, including 263 (19.9%) with tandem lesions, of whom 217 (median age, 65 years; 82.9% male) met the inclusion criteria for the analysis. The stenting group had 84 (38.7%) patients, while the non-stenting group had 133 (61.3%). After adjustment for the potential confounders, extracranial VA stenting was associated with favorable shifts in mRS scores at both 90 days (adjusted common odds ratio [OR], 2.30; 95% confidence interval [CI], 1.23–4.28; P<0.01) and 1 year (adjusted OR [aOR], 2.04; 95% CI [1.05–3.97]; P=0.04), along with lower rate of mortality at both 90 days (aOR, 0.45; 95% CI [0.21–0.93]; P=0.01) and 1 year (aOR, 0.36; 95% CI [0.16–0.79]; P=0.01), with no significant difference in sICH incidence (aOR, 0.35; 95% CI [0.06–1.98]; P=0.24). Conclusion Extracranial VA stenting during EVT may improve functional outcomes and reduce mortality in patients with PCTL strokes.

Background: and Purpose Limited evidence exists on the effectiveness of endovascular treatment (EVT) for acute posterior circulation tandem lesion (PCTL). This study aimed to explore the role of extracranial vertebral artery (VA) stenting in patients with PCTL stroke undergoing EVT. Methods: Individual patient data were pooled from the BASILAR (EVT for Acute Basilar Artery Occlusion Study) and PERSIST (Posterior Circulation Ischemic Stroke) registries. Patients with PCTLs who underwent EVT were included in the present cohort and divided into the stenting and nonstenting groups based on the placement of extracranial VA stents. The primary efficacy outcome was the modified Rankin Scale (mRS) scores at 90 days and 1 year. Safety outcomes included 24-hour symptomatic intracranial hemorrhage (sICH) and all-cause mortality at 90 days and 1 year post-surgery. Results: A combined dataset of 1,320 patients with posterior circulation artery occlusion, including 263 (19.9%) with tandem lesions, of whom 217 (median age, 65 years; 82.9% male) met the inclusion criteria for the analysis. The stenting group had 84 (38.7%) patients, while the non-stenting group had 133 (61.3%). After adjustment for the potential confounders, extracranial VA stenting was associated with favorable shifts in mRS scores at both 90 days (adjusted common odds ratio [OR], 2.30; 95% confidence interval [CI], 1.23–4.28; P<0.01) and 1 year (adjusted OR [aOR], 2.04; 95% CI [1.05–3.97]; P=0.04), along with lower rate of mortality at both 90 days (aOR, 0.45; 95% CI [0.21–0.93]; P=0.01) and 1 year (aOR, 0.36; 95% CI [0.16–0.79]; P=0.01), with no significant difference in sICH incidence (aOR, 0.35; 95% CI [0.06–1.98]; P=0.24). Conclusion Extracranial VA stenting during EVT may improve functional outcomes and reduce mortality in patients with PCTL strokes.

Objective Build a predictive model integrating radiomics features with clinical characteristics for the prognosis prediction of acute anterior circulation large vessel occlusion(LVO)stroke patients after mechanical thrombectomy(MT),and explore its predictive value.Methods Patients with acute ischemic stroke who underwent endovascular treatment for LVO of the anterior circulation were enrolled consecutively from the endovascular treatment registry database for acute anterior circulation ischemic stroke(ACTUAL)and the Nanjing stroke registry system from January 2014 to January 2025 retrospectively.Baseline,clinical and imaging data were collected from enrolled patients,including gender,age,medical history(atrial fibrillation,hypertension,diabetes),smoke history,admission blood pressure,blood glucose,National Institutes of Health stroke scale(NIHSS)score,Alberta stroke program early CT score(ASPECTS),occluded blood vessels(internal carotid artery,middle cerebral artery),trial of Org 10172 in acute stroke treatment(TOAST)classification(atherosclerotic,cardiogenic embolism,others),collateral status(American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology[ASITN/SIR]classification),the onset-to-door time,the time from onset to puncture,the operation time,the time from onset to recanalization,recanalization status(modified thrombolysis in cerebral infarction[mTICI]score),symptomatic intracerebral hemorrhage(sICH)within 72 hours after MT and functional outcome at 90 days post-MT(modified Rankin scale[mRS]score).Divide all patients into a training set and a validation set in a ratio of 7∶3.The training set is used to build the predictive model,and the validation set is used to verify the predictive model.In the training set,patients were divided into a good prognosis group(mRS score 0-2)and a poor prognosis group(mRS score 3-6),the variables with P＜0.05 from the univariate Logistic regression analysis were enrolled into the multivariate Logistic regression analysis to screen the clinical risk factors affecting prognosis.The preoperative head MR axial diffusion weighted imaging sequence images of patients in the training set were selected.The Pyradiomics toolkit of the Python 3.6 platform was used to implement radiomics feature extraction.After conducting consistency analysis on the extracted features,standardization processing was performed.In the training set,feature dimension reduction is carried out on the radiomics feature values obtained after extraction and processing.The least absolute shrinkage and selection operator(LASSO)model was used to screen the features.The support vector machine(SVM),k-nearest neighbor,lightweight gradient boosting algorithm,random forest method and extreme gradient boosting algorithm are used to respectively construct models based on the screened radiomics features,use grid search with cross validation(GridSearchCV)to gain specific parameters in each model.The receiver operating characteristic(ROC)curve was used to analyze and compare the area under the curve(AUC)of each radiomics model,screen the most suitable radiomics model,and verify it in the validation set.The predicted probability value of prognosis calculated by this model is taken as the radiomics score.In the training set,the radiomics scores and the screened clinical risk factors were taken as independent variables,and a multivariate Logistic regression analysis was conducted.A nomogram was used to construct a comprehensive prediction model of radiomics plus clinical factors for predicting the prognosis of MT in acute stroke patients of LVO.The AUC of the clinical factor prediction model,the radiomics prediction model,and the radiomics plus clinical factor comprehensive prediction model were compared in the training set and the validation set,respectively.Results A total of 107 acute anterior LVO patients who underwent MT were included,comprising 72 males and 35 females,aged 27 to 87 years,with a median age of 64(56,71)years.There were 74 cases in the training set,among which 48 cases had a good prognosis and 26 cases had a poor prognosis.There were 33 cases in the validation set,among which 24 cases had a good prognosis and 9 cases had a poor prognosis.The NIHSS score of patients in the training set was lower than that of patients in the validation set(12[8,19]points vs.15[11,21]points,P=0.03),while there were no statistically significant differences in the remaining baseline,clinical and imaging data compared with the validation set(all P＞0.05).(1)Included the variables with P＜0.05 from the univariate Logistic regression analysis into the multivariate Logistic regression analysis.The results showed that age(OR,1.066,95％CI 1.003-1.133,P=0.039)and admission NIHSS score(OR,1.126,95％CI 1.028-1.233,P=0.011)were independent risk factors for poor prognosis of MT in patients with acute anterior circulation LVO stroke.(2)A total of 725 radiomics features were extracted.The results of intra-observer consistency analysis showed that the median intraclass correlation coefficient(ICC)of radiomics features was 0.75(0.56,0.87),and there were 424 features with ICC＞0.7 and 127 features with ICC＞0.9.The results of the inter-observer consistency analysis showed that the median ICC of radiomics features was 0.73(0.53,0.86).After dimensionality reduction using the LASSO,12 most relevant features were selected and incorporated into the radiomics-based prognostic model.The AUCs of the radiomics prediction models constructed by applying SVM,k-nearest neighbor,lightweight gradient boosting algorithm,random forest method and extreme gradient boosting algorithm were 0.803,0.890,0.969,1.000 and 1.000,respectively.The AUCs in the validation set were 0.769,0.743,0.817,0.792 and 0.799,respectively.SVM was selected as the final algorithm for the construction of the radiomics model.The radiomics data were input into SVM to obtain the radiomics score of each patient.(3)A comprehensive predictive nomogram model combining radiomics and clinical factors was constructed based on radiomics score,age,and the NIHSS score at admission.In the validation group,the integrated model demonstrated a significantly higher AUC-ROC(0.918,95％CI 0.831-0.969)compared to the radiomics model(AUC 0.803,95％CI0.694-0.886,P=0.026)and the clinical-feature model(AUC 0.784,95％CI0.674-0.872,P=0.009).In the validation set,there were no statistically significant difference among the integrated model(AUC 0.935,95％CI 0.792-0.991),radiomics model(AUC 0.769,95％CI 0.589-0.897,P=0.111)and the clinical-feature model(AUC 0.894,95％CI 0.737-0.974,P=0.602).The integrated model exhibited good calibration in both the training set and the validation set(Hosmer-Lemeshow test,P values were respectively 0.350,0.580).Conclusion The integrated radiomics-clinical model can provide effective prediction of MT on outcomes in acute anterior circulation LVO stroke patients,and it may offer an objective basis for clinical decision-making.

Objective:To investigate the efficacy of anatomical resection (AR) in the early stages of treating solitary hepatocellular carcinoma (HCC) combined with liver cirrhosis with a diameter of ≤5 cm in comparison to different surgical methods of preferential hepatic parenchymal preservation (non-anatomical liver resection, NAR).Methods:The clinical data of 1 390 cases with solitary HCC combined with liver cirrhosis at an early stage who underwent liver resection at Mengchao Hepatobiliary Hospital of Fujian Medical University and six other medical centers from September 2013 to May 2019 were retrospectively analyzed. Patients were divided into the AR group (486 cases) and the NAR group (904 cases) and the wide surgical margin (WSM) group (745 cases) and the narrow surgical margin (NSM) group (645 cases) according to whether they received AR and the width of the surgical margin (1 cm). The basic information of the patients, preoperative evaluation index data, and postoperative follow-up (follow-up every 3 months) were collected. The Kaplan-Meier method was used to plot the survival curve.The log-rank test was used to compare the difference in survival between the two groups. The Cox proportional hazards regression model was used to analyze the factors affecting the prognosis. Propensity score matching (PSM) was applied to reduce intergroup bias.Results:The overall survival (OS) rates for all patients at 1, 3, and 5 years were 95.5%, 79.9%, and 63.5%, respectively. The recurrence-free survival (RFS) rates were 81.5%, 59.0%, and 43.7%, respectively. There was a statistically significant difference in RFS rate between the AR group and the NAR group prior to PSM, but no statistically significant difference in OS rate (RFS rate: 47.0% vs. 41.9%, P<0.05; OS rate: 64.4% vs. 62.9%, P>0.05). The postoperative RFS rate and OS rate were significantly superior in the WSM group than those of the NSM group (RFS rate: 47.8% vs. 37.2%, P<0.001; OS rate: 69.0% vs. 57.3%, P<0.001). There was no statistically significant difference in OS rate and RFS rate between the AR group and the NAR group following PSM (RFS: 46.3% vs. 45.1%, P>0.05; OS rate: 64.0% vs. 64.3%, P>0.05).The 5-year OS and RFS rates in the WSM group were 66.8% and 60.2%, respectively. The 5-year OS and RFS rates for the NSM group were 48.7% and 41.4%, respectively, with a statistically significant difference ( P<0.05). Cox multivariate analysis indicated that serum albumin, tumor diameter, microvascular invasion, and surgical margin were independent prognostic factors affecting OS and RFS. The Child-Pugh grade and satellite lesions were independent prognostic factors affecting OS. Conclusion:Anatomical liver resection is not an independent risk factor for prognosis, but the state of the resection margin determines the prognosis of patients with solitary HCC combined with cirrhosis. Therefore, hepatic resection margins should be prioritized in such patients.

Objective To investigate the expression levels of microRNA-152-3p(miR-152-3p)and sex determining region-box transcription factor 5(SOX5)in gastric cancer(GC)tissues and their clinical significance.Methods A total of 120 GC patients were selected as study subjects.Re-al-time quantitative polymerase chain reaction(qRT-PCR)was used to detect the expression levels of miR-152-3p and SOX5,and their relationships with the clinicopathological characteristics of GC pa-tients were analyzed.The Kaplan-Meier method was applied to draw survival curves,and the Cox re-gression model was used to screen the prognostic influencing factors of GC patients.Results The ex-pression level of miR-152-3p in GC tissues was lower than that in adjacent non-cancerous tissues,while the expression level of SOX5 was higher than that in adjacent non-cancerous tissues(P＜0.05).The expressions of miR-152-3p and SOX5 in GC tissues were all associated with lymph node metastasis,degree of differentiation,and TNM stage(P＜0.05).The expression level of miR-152-3p was negatively correlated with that of SOX5(r=-0.512,P＜0.05),and there were targeted binding sites between miR-152-3p and SOX5.The 5-year specific survival rate of the low miR-152-3p expression group was lower than that of the high miR-152-3p expression group(60.53％versus 84.09％,x2=7.256,P＜0.05).The 5-year specific survival rate of the high SOX5 expression group was 63.10％,which was lower than 83.33％of the low SOX5 expression group,with a statis-tically significant difference(x2=4.840,P＜0.05).Multivariate Cox regression analysis showed that the expression levels of miR-152-3p and SOX5,as well as the TNM stage,were all independent prog-nostic influencing factors for GC patients(P＜0.05).Conclusion Low expressions of miR-152-3p and high expression of SOX5 are observed in GC tissues,and their expression levels are closely re-lated to clinicopathological characteristics such as TNM stage and patients' prognosis.

Objective:To evaluate the effect of transient receptor potential vanilloid type 1 (TRPV1) gene polymorphism on the postoperative analgesic efficacy of alfentanil in patients undergoing radical mastectomy.Methods:In this prospective study, adult female patients diagnosed with breast cancer who underwent surgical treatment at the First Affiliated Hospital of Zhengzhou University were selected as case group ( n=162), while age-matched healthy adult females were selected as control group ( n=80). All subjects had a body mass index of 18-30 kg/m 2. The genotype and allele frequencies of TRPV1 rs8065080 and rs222747 were compared between the two groups, and the consumption of alfentanil and requirement for rescue analgesia within 48 h after surgery were recorded in breast cancer patients with different TRPV1 rs222747 genotypes. Results:Three genotypes of CC, GC, and GG were detected at rs222747 locus of TRPV1 gene, and there was no significant difference in the genotype distribution between the two groups ( P>0.05). Three genotypes of CC, TC and TT were detected at rs8065080 locus of TRPV1 gene, and there was significant difference in the genotype distribution between the two groups ( P<0.05). There was no significant difference in the basic data of patients with different genotypes of TRPV1 gene rs222747 locus ( P>0.05). There were significant differences in the consumption of alfentanil during 0-24 h after surgery and during 24-48 h after surgery and rate of rescue analgesia within 48 h after surgery among patients with different genotypes of TRPV1 gene rs222747 locus ( P<0.05). Conclusions:The polymorphism at the TRPV1 gene rs222747 locus can influence the postoperative analgesic efficacy of alfentanil in breast cancer patients undergoing radical mastectomy, suggesting that genetic factors may be one of the reasons for the inter-individual variability in alfentanil efficacy.

Objective Build a predictive model integrating radiomics features with clinical characteristics for the prognosis prediction of acute anterior circulation large vessel occlusion(LVO)stroke patients after mechanical thrombectomy(MT),and explore its predictive value.Methods Patients with acute ischemic stroke who underwent endovascular treatment for LVO of the anterior circulation were enrolled consecutively from the endovascular treatment registry database for acute anterior circulation ischemic stroke(ACTUAL)and the Nanjing stroke registry system from January 2014 to January 2025 retrospectively.Baseline,clinical and imaging data were collected from enrolled patients,including gender,age,medical history(atrial fibrillation,hypertension,diabetes),smoke history,admission blood pressure,blood glucose,National Institutes of Health stroke scale(NIHSS)score,Alberta stroke program early CT score(ASPECTS),occluded blood vessels(internal carotid artery,middle cerebral artery),trial of Org 10172 in acute stroke treatment(TOAST)classification(atherosclerotic,cardiogenic embolism,others),collateral status(American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology[ASITN/SIR]classification),the onset-to-door time,the time from onset to puncture,the operation time,the time from onset to recanalization,recanalization status(modified thrombolysis in cerebral infarction[mTICI]score),symptomatic intracerebral hemorrhage(sICH)within 72 hours after MT and functional outcome at 90 days post-MT(modified Rankin scale[mRS]score).Divide all patients into a training set and a validation set in a ratio of 7∶3.The training set is used to build the predictive model,and the validation set is used to verify the predictive model.In the training set,patients were divided into a good prognosis group(mRS score 0-2)and a poor prognosis group(mRS score 3-6),the variables with P＜0.05 from the univariate Logistic regression analysis were enrolled into the multivariate Logistic regression analysis to screen the clinical risk factors affecting prognosis.The preoperative head MR axial diffusion weighted imaging sequence images of patients in the training set were selected.The Pyradiomics toolkit of the Python 3.6 platform was used to implement radiomics feature extraction.After conducting consistency analysis on the extracted features,standardization processing was performed.In the training set,feature dimension reduction is carried out on the radiomics feature values obtained after extraction and processing.The least absolute shrinkage and selection operator(LASSO)model was used to screen the features.The support vector machine(SVM),k-nearest neighbor,lightweight gradient boosting algorithm,random forest method and extreme gradient boosting algorithm are used to respectively construct models based on the screened radiomics features,use grid search with cross validation(GridSearchCV)to gain specific parameters in each model.The receiver operating characteristic(ROC)curve was used to analyze and compare the area under the curve(AUC)of each radiomics model,screen the most suitable radiomics model,and verify it in the validation set.The predicted probability value of prognosis calculated by this model is taken as the radiomics score.In the training set,the radiomics scores and the screened clinical risk factors were taken as independent variables,and a multivariate Logistic regression analysis was conducted.A nomogram was used to construct a comprehensive prediction model of radiomics plus clinical factors for predicting the prognosis of MT in acute stroke patients of LVO.The AUC of the clinical factor prediction model,the radiomics prediction model,and the radiomics plus clinical factor comprehensive prediction model were compared in the training set and the validation set,respectively.Results A total of 107 acute anterior LVO patients who underwent MT were included,comprising 72 males and 35 females,aged 27 to 87 years,with a median age of 64(56,71)years.There were 74 cases in the training set,among which 48 cases had a good prognosis and 26 cases had a poor prognosis.There were 33 cases in the validation set,among which 24 cases had a good prognosis and 9 cases had a poor prognosis.The NIHSS score of patients in the training set was lower than that of patients in the validation set(12[8,19]points vs.15[11,21]points,P=0.03),while there were no statistically significant differences in the remaining baseline,clinical and imaging data compared with the validation set(all P＞0.05).(1)Included the variables with P＜0.05 from the univariate Logistic regression analysis into the multivariate Logistic regression analysis.The results showed that age(OR,1.066,95％CI 1.003-1.133,P=0.039)and admission NIHSS score(OR,1.126,95％CI 1.028-1.233,P=0.011)were independent risk factors for poor prognosis of MT in patients with acute anterior circulation LVO stroke.(2)A total of 725 radiomics features were extracted.The results of intra-observer consistency analysis showed that the median intraclass correlation coefficient(ICC)of radiomics features was 0.75(0.56,0.87),and there were 424 features with ICC＞0.7 and 127 features with ICC＞0.9.The results of the inter-observer consistency analysis showed that the median ICC of radiomics features was 0.73(0.53,0.86).After dimensionality reduction using the LASSO,12 most relevant features were selected and incorporated into the radiomics-based prognostic model.The AUCs of the radiomics prediction models constructed by applying SVM,k-nearest neighbor,lightweight gradient boosting algorithm,random forest method and extreme gradient boosting algorithm were 0.803,0.890,0.969,1.000 and 1.000,respectively.The AUCs in the validation set were 0.769,0.743,0.817,0.792 and 0.799,respectively.SVM was selected as the final algorithm for the construction of the radiomics model.The radiomics data were input into SVM to obtain the radiomics score of each patient.(3)A comprehensive predictive nomogram model combining radiomics and clinical factors was constructed based on radiomics score,age,and the NIHSS score at admission.In the validation group,the integrated model demonstrated a significantly higher AUC-ROC(0.918,95％CI 0.831-0.969)compared to the radiomics model(AUC 0.803,95％CI0.694-0.886,P=0.026)and the clinical-feature model(AUC 0.784,95％CI0.674-0.872,P=0.009).In the validation set,there were no statistically significant difference among the integrated model(AUC 0.935,95％CI 0.792-0.991),radiomics model(AUC 0.769,95％CI 0.589-0.897,P=0.111)and the clinical-feature model(AUC 0.894,95％CI 0.737-0.974,P=0.602).The integrated model exhibited good calibration in both the training set and the validation set(Hosmer-Lemeshow test,P values were respectively 0.350,0.580).Conclusion The integrated radiomics-clinical model can provide effective prediction of MT on outcomes in acute anterior circulation LVO stroke patients,and it may offer an objective basis for clinical decision-making.