Objective:To explore the clinical efficacy, safety and possible neuroimaging mechanism of deep transcranial magnetic stimulation (dTMS) and repetitive transcranial magnetic stimulation (rTMS) in the treatment of refractory migraine.Methods:Thirty patients with refractory migraine were selected from the Department of Neurology, Affiliated Hospital of North Sichuan Medical College from October 2022 to August 2023. The patients were randomly divided into dTMS group ( n=10), rTMS group ( n=10) and sham stimulation group ( n=10). The dTMS group was treated with H7 coil and the rTMS group with "8" coil, and the sham stimulation group was treated with sham stimulation rTMS with the frequency of 10 Hz. The stimulation site was the contralateral primary motor cortex (M1) of headache, which was treated for 2 weeks (3 600 pulses per time, 5 times per week, 10 times in total). Visual Analogue Scale (VAS) and Headache Impact Test-6 (HIT-6) evaluations were performed before treatment, on the first day after treatment, and 1, 3 and 6 months after treatment. The resting-state functional magnetic resonance images of the 3 groups of patients before and after treatment were collected and analyzed by MATLAB2018b, SPM12 and RESTPLUS softwares, and the brain regions with different regional homogeneity (ReHo) before and after treatment were obtained. The general clinical data and scale scoring data were analyzed and processed by SPSS 26.0 version software. Results:There were significant differences in VAS scores among the dTMS group (before treatment 6.70±0.68, the first day after treatment 5.60±0.70, 1 month after treatment 5.00±0.82, 3 months after treatment 3.50±0.85, 6 months after treatment 3.90±1.45), the rTMS group (before treatment 6.90±0.74, the first day after treatment 5.90±0.74, 1 month after treatment 5.30±0.82, 3 months after treatment 5.30±0.82, 6 months after treatment 6.80±0.63) and the sham stimulation group (before treatment 6.60±0.97, the first day after treatment 6.70±0.95, 1 month after treatment 6.90±1.10, 3 months after treatment 6.70±0.68, 6 months after treatment 7.10±0.88; F=16.054, P<0.001), VAS scores among different time points ( F=34.292, P<0.001), and the interaction between groups and time ( F=24.136, P<0.001). Compared with those before treatment, VAS scores in the dTMS group and the rTMS group decreased on the first day after treatment, 1 month and 3 months after treatment (all P<0.05); VAS scores decreased in the dTMS group 6 months after treatment ( P<0.05). Compared with the sham stimulation group, the VAS scores of the dTMS group were lower at the same time points after treatment (all P<0.05), and the VAS scores of the rTMS group were lower on the first day after treatment, 1 month and 3 months after treatment (all P<0.05). Compared with the rTMS group, VAS scores were lower at 3 and 6 months after dTMS treatment (both P<0.05). There were significant differences in HIT-6 scores among groups ( F=13.173, P<0.001), HIT-6 scores among different time points ( F=60.788, P<0.001), and interaction between groups and time ( F=35.576, P<0.001). Compared with those before treatment, the HIT-6 scores in the dTMS group decreased on the first day after treatment ( P<0.05); the HIT-6 scores in the dTMS group and the rTMS group decreased 1 month and 3 months after treatment (both P<0.05); the HIT-6 scores decreased in the dTMS group 6 months after treatment ( P<0.05). Compared with the sham stimulation group, the HIT-6 scores were lower in the dTMS group at the same time points after treatment (all P<0.05), and the HIT-6 scores were lower in the rTMS group at 1 and 3 months after treatment (both P<0.05). Compared with the rTMS group, HIT-6 scores were lower at 3 and 6 months after dTMS treatment (both P<0.05). Analysis of ReHo results: compared with those before treatment, the ReHo values of the right cerebellar angle area 1 increased in the dTMS group and the sham stimulation group, decreased in the rTMS group. The ReHo values of the right middle occipital gyrus, left dorsolateral superior frontal gyrus and right cerebellar area 8 increased in the dTMS group, but decreased in the rTMS group and the sham stimulation group. The ReHo values of the left precentral gyrus and left superior temporal gyrus decreased in the dTMS group, while those in the rTMS group and the sham stimulation group increased. There were no obvious adverse reactions in the 3 groups during the treatment and follow-up period. Conclusions:dTMS and rTMS may help to improve the headache degree and quality of life of patients with refractory migraine, and they are safe, which may be related to the changes of brain network in the right cerebellar angle area 1, right middle occipital gyrus, left dorsolateral superior frontal gyrus, left precentral gyrus, left superior temporal gyrus and right cerebellar area 8.

Objective:To explore the clinical efficacy, safety and possible neuroimaging mechanism of deep transcranial magnetic stimulation (dTMS) and repetitive transcranial magnetic stimulation (rTMS) in the treatment of refractory migraine.Methods:Thirty patients with refractory migraine were selected from the Department of Neurology, Affiliated Hospital of North Sichuan Medical College from October 2022 to August 2023. The patients were randomly divided into dTMS group ( n=10), rTMS group ( n=10) and sham stimulation group ( n=10). The dTMS group was treated with H7 coil and the rTMS group with "8" coil, and the sham stimulation group was treated with sham stimulation rTMS with the frequency of 10 Hz. The stimulation site was the contralateral primary motor cortex (M1) of headache, which was treated for 2 weeks (3 600 pulses per time, 5 times per week, 10 times in total). Visual Analogue Scale (VAS) and Headache Impact Test-6 (HIT-6) evaluations were performed before treatment, on the first day after treatment, and 1, 3 and 6 months after treatment. The resting-state functional magnetic resonance images of the 3 groups of patients before and after treatment were collected and analyzed by MATLAB2018b, SPM12 and RESTPLUS softwares, and the brain regions with different regional homogeneity (ReHo) before and after treatment were obtained. The general clinical data and scale scoring data were analyzed and processed by SPSS 26.0 version software. Results:There were significant differences in VAS scores among the dTMS group (before treatment 6.70±0.68, the first day after treatment 5.60±0.70, 1 month after treatment 5.00±0.82, 3 months after treatment 3.50±0.85, 6 months after treatment 3.90±1.45), the rTMS group (before treatment 6.90±0.74, the first day after treatment 5.90±0.74, 1 month after treatment 5.30±0.82, 3 months after treatment 5.30±0.82, 6 months after treatment 6.80±0.63) and the sham stimulation group (before treatment 6.60±0.97, the first day after treatment 6.70±0.95, 1 month after treatment 6.90±1.10, 3 months after treatment 6.70±0.68, 6 months after treatment 7.10±0.88; F=16.054, P<0.001), VAS scores among different time points ( F=34.292, P<0.001), and the interaction between groups and time ( F=24.136, P<0.001). Compared with those before treatment, VAS scores in the dTMS group and the rTMS group decreased on the first day after treatment, 1 month and 3 months after treatment (all P<0.05); VAS scores decreased in the dTMS group 6 months after treatment ( P<0.05). Compared with the sham stimulation group, the VAS scores of the dTMS group were lower at the same time points after treatment (all P<0.05), and the VAS scores of the rTMS group were lower on the first day after treatment, 1 month and 3 months after treatment (all P<0.05). Compared with the rTMS group, VAS scores were lower at 3 and 6 months after dTMS treatment (both P<0.05). There were significant differences in HIT-6 scores among groups ( F=13.173, P<0.001), HIT-6 scores among different time points ( F=60.788, P<0.001), and interaction between groups and time ( F=35.576, P<0.001). Compared with those before treatment, the HIT-6 scores in the dTMS group decreased on the first day after treatment ( P<0.05); the HIT-6 scores in the dTMS group and the rTMS group decreased 1 month and 3 months after treatment (both P<0.05); the HIT-6 scores decreased in the dTMS group 6 months after treatment ( P<0.05). Compared with the sham stimulation group, the HIT-6 scores were lower in the dTMS group at the same time points after treatment (all P<0.05), and the HIT-6 scores were lower in the rTMS group at 1 and 3 months after treatment (both P<0.05). Compared with the rTMS group, HIT-6 scores were lower at 3 and 6 months after dTMS treatment (both P<0.05). Analysis of ReHo results: compared with those before treatment, the ReHo values of the right cerebellar angle area 1 increased in the dTMS group and the sham stimulation group, decreased in the rTMS group. The ReHo values of the right middle occipital gyrus, left dorsolateral superior frontal gyrus and right cerebellar area 8 increased in the dTMS group, but decreased in the rTMS group and the sham stimulation group. The ReHo values of the left precentral gyrus and left superior temporal gyrus decreased in the dTMS group, while those in the rTMS group and the sham stimulation group increased. There were no obvious adverse reactions in the 3 groups during the treatment and follow-up period. Conclusions:dTMS and rTMS may help to improve the headache degree and quality of life of patients with refractory migraine, and they are safe, which may be related to the changes of brain network in the right cerebellar angle area 1, right middle occipital gyrus, left dorsolateral superior frontal gyrus, left precentral gyrus, left superior temporal gyrus and right cerebellar area 8.

Objective:To evaluate the diagnostic efficacy of FibroScan combined with various noninvasive diagnostic models for liver fibrosis in patients with chronic hepatitis B (CHB) complicated with nonalcoholic fatty liver disease (NAFLD), and to establish a new predictive model with common clinical indicators.Methods:From January 2016 to May 2024, the clinical data of 118 CHB patients complicated with NAFLD from the First Affiliated Hospital of Zhengzhou University, who underwent liver biopsy and FibroScan examination were respectively analyzed. According to the Scheuer scoring system, different diagnostic endpoints were set based on the degree of liver fibrosis (S0 to S1, ≥S2, ≥S3, and S4), fibrosis stage ≥S2 was designated as the criterion for significant liver fibrosis. Fibrosis-4 (FIB-4), γ-glutamyl transpeptidase (GGT) to platelet ratio (GPR), GGT-age-platelet-international normalized ratio (GAPI) model, S index, King index and Forns index were calculated according to the common clinical indicators. The independent t test or Mann-Whitney U test was used to compare the two groups. Spearman rank correlation was used to analyze the correlation between each noninvasive diagnostic method and the degree of liver fibrosis. Receiver operating characteristic curve (ROC) was plotted, and the DeLong test was performed to compare the area under the curve (AUC), and to evaluate the predictive value of FibroScan combined with various noninvasive diagnostic models for the diagnosis of liver fibrosis. The laboratory indicators were compared between patients with non-significant liver fibrosis and patients with significant liver fibrosis. And the indicators with statistically significant differences ( P<0.05) in the univariate analysis were further analyzed by multivariate logistic regression to establish a new predictive model for liver fibrosis. Hosmer-Lemeshow test was used to assess the model′s goodness of fit. Results:The results of Spearman rank correlation showed that FIB-4, GPR, FibroScan, GAPI model, S index, King index, and Forns index were positively correlated with the stage of liver fibrosis ( r=0.413, 0.458, 0.512, 0.473, 0.533, 0.380 and 0.478, all P<0.001). The results of ROC analysis indicated that among combination of FibroScan and other diagnostic models, the AUC values of FibroScan+ FIB-4, FibroScan+ Forns index were relatively high in ≥S2 and ≥S3, which were 0.804 and 0.907, respectively. The platelet count ((200.65±50.89)×10 9/L vs. (169.96±63.68)×10 9/L), total cholesterol ((4.69±0.77) mmol/L vs. (4.32±1.00) mmol/L), high-density lipoprotein (HDL) (1.28 (1.05, 1.46) mmol/L vs. 1.08 (0.92, 1.21) mmol/L), total protein (74.00 (70.63, 77.08) g/L vs. 68.80 (64.60, 73.55) g/L), albumin (47.06 (44.65, 48.81) g/L vs. 44.70 (41.55, 46.20) g/L), and globulin (26.80 (24.48, 29.70) g/L vs. 25.80 (23.05, 27.60) g/L) of the non-significant liver fibrosis group were higher than those of the significant liver fibrosis group, and the differences were statistically significant ( t=2.74, 2.09; Z=-3.30, -3.88, -3.95, -2.01; P=0.007, =0.040, =0.001, <0.001, <0.001, =0.044). GGT (27.50 (17.00, 41.75) U/L vs. 37.00 (22.50, 87.00) U/L), the liver stiffness measurement (LSM) in the non-significant hepatic fibrosis group was lower than the significant liver fibrosis group (6.85 (5.60, 9.26) kPa vs. 11.60 (7.08, 17.26) kPa), and the differences were statistically significant ( Z=-2.73, -4.39; P=0.006, <0.001). The result of multivariate logistic regression analysis revealed that globulin, albumin, HDL, and LSM were independent factors of liver fibrosis ( OR (95% confidence interval)=0.865 (0.759 to 0.985), 0.804 (0.691 to 0.935), 0.128 (0.023 to 0.711), and 1.251 (1.091 to 1.433), respectively; P=0.029, 0.025, 0.019, 0.001). A novel model, GLAH, was established with globulin, LSM, albumin, and HDL. The AUC for diagnosing liver fibrosis degree ≥S2, ≥S3, and S4 was 0.847, 0.938, and 0.909, respectively, which were higher than those of the above models. The positive predictive value for diagnosing liver fibrosis degree ≥S2 with GLAH>1.12 as the cutoff value was 95.8%. The negative predictive value for excluding fibrosis stage ≥S2 with GLAH<-1.41 was 92.3%. This approach could reduce the number of liver biopsies by 48.3% (57/118), with an accuracy of 94.7% (54/57). Conclusions:The clinical value of FibroScan combined with FIB-4 or Forns index is better in the diagnisis of fibrosis stage ≥S2 and ≥S3. The GLAH model has higher diagnostic value and can accurately predict the degree of liver fibrosis in CHB patients complicated with NAFLD, thus reducing the need for liver biopsy.

Objective:To evaluate the diagnostic efficacy of FibroScan combined with various noninvasive diagnostic models for liver fibrosis in patients with chronic hepatitis B (CHB) complicated with nonalcoholic fatty liver disease (NAFLD), and to establish a new predictive model with common clinical indicators.Methods:From January 2016 to May 2024, the clinical data of 118 CHB patients complicated with NAFLD from the First Affiliated Hospital of Zhengzhou University, who underwent liver biopsy and FibroScan examination were respectively analyzed. According to the Scheuer scoring system, different diagnostic endpoints were set based on the degree of liver fibrosis (S0 to S1, ≥S2, ≥S3, and S4), fibrosis stage ≥S2 was designated as the criterion for significant liver fibrosis. Fibrosis-4 (FIB-4), γ-glutamyl transpeptidase (GGT) to platelet ratio (GPR), GGT-age-platelet-international normalized ratio (GAPI) model, S index, King index and Forns index were calculated according to the common clinical indicators. The independent t test or Mann-Whitney U test was used to compare the two groups. Spearman rank correlation was used to analyze the correlation between each noninvasive diagnostic method and the degree of liver fibrosis. Receiver operating characteristic curve (ROC) was plotted, and the DeLong test was performed to compare the area under the curve (AUC), and to evaluate the predictive value of FibroScan combined with various noninvasive diagnostic models for the diagnosis of liver fibrosis. The laboratory indicators were compared between patients with non-significant liver fibrosis and patients with significant liver fibrosis. And the indicators with statistically significant differences ( P<0.05) in the univariate analysis were further analyzed by multivariate logistic regression to establish a new predictive model for liver fibrosis. Hosmer-Lemeshow test was used to assess the model′s goodness of fit. Results:The results of Spearman rank correlation showed that FIB-4, GPR, FibroScan, GAPI model, S index, King index, and Forns index were positively correlated with the stage of liver fibrosis ( r=0.413, 0.458, 0.512, 0.473, 0.533, 0.380 and 0.478, all P<0.001). The results of ROC analysis indicated that among combination of FibroScan and other diagnostic models, the AUC values of FibroScan+ FIB-4, FibroScan+ Forns index were relatively high in ≥S2 and ≥S3, which were 0.804 and 0.907, respectively. The platelet count ((200.65±50.89)×10 9/L vs. (169.96±63.68)×10 9/L), total cholesterol ((4.69±0.77) mmol/L vs. (4.32±1.00) mmol/L), high-density lipoprotein (HDL) (1.28 (1.05, 1.46) mmol/L vs. 1.08 (0.92, 1.21) mmol/L), total protein (74.00 (70.63, 77.08) g/L vs. 68.80 (64.60, 73.55) g/L), albumin (47.06 (44.65, 48.81) g/L vs. 44.70 (41.55, 46.20) g/L), and globulin (26.80 (24.48, 29.70) g/L vs. 25.80 (23.05, 27.60) g/L) of the non-significant liver fibrosis group were higher than those of the significant liver fibrosis group, and the differences were statistically significant ( t=2.74, 2.09; Z=-3.30, -3.88, -3.95, -2.01; P=0.007, =0.040, =0.001, <0.001, <0.001, =0.044). GGT (27.50 (17.00, 41.75) U/L vs. 37.00 (22.50, 87.00) U/L), the liver stiffness measurement (LSM) in the non-significant hepatic fibrosis group was lower than the significant liver fibrosis group (6.85 (5.60, 9.26) kPa vs. 11.60 (7.08, 17.26) kPa), and the differences were statistically significant ( Z=-2.73, -4.39; P=0.006, <0.001). The result of multivariate logistic regression analysis revealed that globulin, albumin, HDL, and LSM were independent factors of liver fibrosis ( OR (95% confidence interval)=0.865 (0.759 to 0.985), 0.804 (0.691 to 0.935), 0.128 (0.023 to 0.711), and 1.251 (1.091 to 1.433), respectively; P=0.029, 0.025, 0.019, 0.001). A novel model, GLAH, was established with globulin, LSM, albumin, and HDL. The AUC for diagnosing liver fibrosis degree ≥S2, ≥S3, and S4 was 0.847, 0.938, and 0.909, respectively, which were higher than those of the above models. The positive predictive value for diagnosing liver fibrosis degree ≥S2 with GLAH>1.12 as the cutoff value was 95.8%. The negative predictive value for excluding fibrosis stage ≥S2 with GLAH<-1.41 was 92.3%. This approach could reduce the number of liver biopsies by 48.3% (57/118), with an accuracy of 94.7% (54/57). Conclusions:The clinical value of FibroScan combined with FIB-4 or Forns index is better in the diagnisis of fibrosis stage ≥S2 and ≥S3. The GLAH model has higher diagnostic value and can accurately predict the degree of liver fibrosis in CHB patients complicated with NAFLD, thus reducing the need for liver biopsy.

Objective:To compare the differences of brain activation in patients with neuromyelitis optica spectrum disorders (NMOSD) and multiple sclerosis (MS) under contact heat stimulation (CHS), and to explore the characteristics of pain-related brain networks in NMOSD and MS patients.Methods:Fourteen NMOSD patients (NMOSD group) and 12 MS patients (MS group) admitted to Affiliated Hospital of North Sichuan Medical College from September 2022 to December 2022 who met the diagnostic criteria were collected. Twelve healthy individuals (HC group) matched with gender and age were recruited during the same period. Visual Analogue Scale (VAS) score was used to evaluate the pain of the subjects, CHS painful stimuli were given, and task-state functional magnetic resonance imaging (fMRI) scans were performed at the same time, and the differences in brain activation among the 3 groups were analyzed and compared.Results:(1) Compared with the HC group, the NMOSD group had a stronger activation degree than the HC group in the brain regions including the cortex around the left distance fissure, bilateral medial superior frontal gyrus; the activation degree of the NMOSD group was weaker than that of the HC group in the brain areas including the left medial and paracingulate gyrus, right superior parietal gyrus, left postcentral gyrus, and right supplementary motor area (all P<0.05). (2) Compared with the HC group, the brain regions whose activation degree was weaker in the MS group included the left caudate nucleus, left medial and paracingulate gyrus, left paracentral lobule, right superior parietal gyrus, left postcentral gyrus, left precuneus, right supplementary motor area, right superior temporal gyrus and right thalamus, and there was no brain area in the MS group whose activation degree was stronger than that of the HC group (all P<0.05). (3) Compared with the MS group, the brain regions with stronger activation degree in the NMOSD group included the left perifissure cortex and right thalamus, but no brain regions with weaker activation degree were found in the NMOSD group (all P<0.05). (4) There was a correlation between somatic pain VAS scores and activation of the medial superior frontal gyrus in the NMOSD group ( r=0.66, P<0.05). Conclusions:The results of CHS-fMRI in the NMOSD group, MS group and HC group showed that multiple brain regions were activated, indicating that multiple brain regions were involved in the generation and processing of pain, and there was a pain-related brain network. Pain-related brain networks were altered in NMOSD patients and MS patients, and there were differences in pain-related brain networks between the two diseases.

【Objective】 To investigate the efficacy and safety of sitagliptin combined with metformin versus glimepiride combined with metformin in newly diagnosed type 2 diabetes patients with severe hyperglycaemia. 【Methods】 A randomized controlled and non-inferiority trial was carried out. A total of 129 newly diagnosed type 2 diabetes patients with severe hyperglycaemia [FPG≥200 mg/mL (11.1 mmol/L) and HbA1c≥9.0%] were enrolled and numerally randomly assigned to two groups. The patients received sitagliptin combined with metformin (n=66) or glimepiride combined with metformin (n=63) for 4 weeks and then metformin alone for another 8 weeks. Glycaemic control, weight changes and β-cell insulin secretory capacity were investigated to demonstrate the efficacy and safety of these two treatments. 【Results】 Mean HbA1c reduction was 4.03% in sitagliptin group and 4.13% in glimepiride group after 3 months of treatment. The lower boundary of the two-sided 95% confidence intervals of the mean HbA1c reduction difference between the two groups was -0.648%, which was more than -0.65%, suggesting that the predefined statistical criterion for non-inferiority was achieved. FPG decreased significantly after one month of intervention in both groups (P<0.05). Significant reduction in the time of reaching euglycemia, FPG and weight decrease was observed in sitagliptin group than glimepiride group (P<0.05). The FPG control rate FPG<110 mg/mL (6.1 mmol/L) was higher in sitagliptin group than in glimepiride group (P<0.05). After the 3-month follow-up, FPG, HbA1c and incidence of hypoglycemia showed no significant differences in the two groups, while weight loss and BMI changes showed significant differences in sitagliptin group compared with glimepiride group (P<0.05). No significant differences in β-cell insulin secretory indexes were observed in the two therapy groups (P>0.05). 【Conclusion】 Our study provided evidence that sitagliptin combined with metformin in newly diagnosed diabetes patients with severe hyperglycaemia showed better outcomes in glycaemic remission compared with glimepiride for those who refused insulin injection.