AIM: To evaluation the efficacy dosages of topiramate (TMP) in treatment of patients with different types of epilepsy. METHODS : The seizure rate in baseline phase of patients with epilepsy were observed and recorded before treatment of topiramate as monotherapy for 20 weeks. The TMP st arting dosage was 25 mg?d -1 , and then increased to 25 mg?d -1 each week for 8 weeks until effective dosage or 200 mg?d -1 for 12 weeks, and the change of seizure frequency and adverse reactions were recorded. RESULTS: The seizure in 31 cases ( 51.7 %) was totally contro lled, seizure reduction of ≥75% was in 14 cases ( 23.3 %), ≥50% was in 4 cas es ( 6.7 %), and

Objective To explore the alterations of resting-state neural networks in females with migraine at attack stage in low-and high-frequency ranges compared to healthy controls. Methods Resting-state magnetoencephalography data from 20 females with migraine ( migraine group ) and 20 age-and gender-matched healthy controls ( control group ) were collected to compute the neural network parameters through graph theory analysis.Independent samples t test was used to compare the difference of the network parameters between the two groups.The Pearson coefficient was used to assess the relationship between the abnormal network parameters and clinical manifestations of migraine.Results Compared with control group, females in migraine group at attack stage showed increased functional connectivity in the 0.1 -1 Hz, 4 -8 Hz, 12 -30 Hz, 30 -80 Hz band; increased shortest path length in the 80-250 Hz band; increased clustering coefficient and degree in the 0.1 -1 Hz band;decreased clustering coefficient and degree in the 4 -8 Hz, 12 -30 Hz band ( P<0.05 -0.01 ) .The functional connectivity of females with migraine at attack stage was positively correlated with number of years with migraine in the 12-30 Hz ( r=0.56, P=0.01 ) .Conclusion These results indicate that inherent neural networks are significantly impaired in low-and high-frequency ranges in females with migraine at attack stage and may contribute to the clinical manifestations of this disorder.

Objective To investigate the satisfaction status of patients in the Community Health Service Center,and to provide the basis data for reform and development of the Community Health Service Center in future. Methods 481 patients and 9 Community Health Service Center in Shenyang were randomly recruited in this study by the cluster sampling survey.Several trained interviewers used questionnaires to collect requisite information.Results In the all community health professionals,including technical level,therapeutic efficacy,preventive health service, service attitude and requirement satiation,the trust status of patients was the highest,the rates of satisfaction and very satisfaction got to 92.8%.The satisfaction status for preventive health service was the lowest,only 67.7%.In analysis on influencing factors,medical insurance of patients was the important factor for their satisfaction status.There were significant differences in technical level (χ2 =22.61 ,P <0.01 ),therapeutic efficacy (χ2 =21 .52,P <0.01 ), preventive health service (χ2 =1 4.35,P <0.05),service attitude (χ2 =22.43,P <0.01 ),requirement satiation (χ2 =22.30,P <0.01 ),the trust status of patients (χ2 =1 7.81 ,P <0.01 ).In addition,age and education degree also were the factors on the satisfaction status of patients.There were significant differences among different age group in therapeutic efficacy (χ2 =33.38,P <0.01 ),preventive health service (χ2 =24.43,P <0.05 ),requirement satiation (χ2 =26.55,P <0.01 ),the trust status of patients (χ2 =22.39,P <0.05 ).There were significant differences among different education degree in therapeutic efficacy (χ2 =1 5.79,P <0.05),service attitude (χ2 =1 4.63,P <0.05)and the trust status of patients (χ2 =1 3.50,P <0.05).Conclusion The satisfaction status of patients for service attitude is the highest and age,education degree and medical insurance of patients are the important factors influencing satisfaction status of patients.

Objective:To study the factors influencing survival after radical resection in patients with intrahepatic cholangiocarcinoma (ICC), and to construct a nomogram on survival prediction.Methods:The clinical data of 139 patients with ICC who underwent radical resection at the People's Hospital of Zhengzhou University from June 2018 to December 2021 were retrospectively analyzed. There are 69 males and 70 females, aged (59.5±10.2) years old. These patients were divided into two groups based on a 3: 1 ratio by using the random number method: the test group ( n=104) and the validation group ( n=35). Data from the test group was used to construct a nomagram and data from the validation group was used to validate the predictive power of the nomagram. Univariate and multivariate Cox regression analyses were used to analyse factors influencing survival on the test group patients and to construct a nomogram. The predictive accuracy of the nomogram was determined by receiver operating characteristic (ROC) curves, concordance index (C-index) and calibration curves. Results:The results of the multivariate regression analysis showed that a combined hemoglobin, albumin, lymphocyte and platelet immunoinflammation (HALP) score <37.1 ( HR=1.784, 95% CI: 1.047-3.040), CA19-9 > 35U/ml ( HR=2.352, 95% CI: 1.139-4.857), poorly differentiated tumor ( HR=2.475, 95% CI: 1.237-4.953) and vascular invasion ( HR=1.897, 95% CI: 1.110-3.244) were independent risk factors that affected prognosis of patients with ICC after radical resection (all P<0.05). The AUCs of the nomogram in the test group in predicting the overall survival at 1, 2 and 3 years of patients with ICC after radical resection were 0.808, 0.853 and 0.859, respectively. There was good consistency between the prediction of the nomogram and actual observation. The predicted C-index of the total survival period of the test group was 0.765 (95% CI: 0.704-0.826), and the C-index of the validation group was 0.759 (95% CI: 0.673-0.845). Conclusion:A HALP score <37.1, CA19-9>35 U/ml, poorly differentiated tumour and vascular invasion were independent risk factors for prognosis of ICC patients after radical resection. The nomogram was established based on the above factors and showed good performance in predicting overall survival after radical resection in patients with ICC.

Objective:To construct a nomogram prediction model for survival after radical surgical resection of intrahepatic cholangiocarcinoma (ICC) based on the albumin-bilirubin index (ALBI), and to evaluate its predictive efficacy.Methods:From January 2016 to January 2020, 170 patients with ICC who underwent radical surgical resection at the People's Hospital of Zhengzhou University were retrospectively analyzed. There were 90 males and 80 females, aged (58.5±10.6) years old. Based on a ratio of 7∶3 by the random number table, the patients were divided into the training set ( n=117) and the internal validation set ( n=53). The training set was used for nomogram model construction, and the validation set was used for model validation and evaluation. Follow up was conducted through outpatient reexamination and telephone contact. The Kaplan-Meier method was used for survival analysis, and a nomogram was drawn based on variables with a P<0.05 in multivariate Cox regression analysis. The predictive strength of the predictive model was evaluated by analyzing the consistency index (C-index), calibration curve, and clinical decision curve of the training and validation sets. Results:Multivariate Cox regression analysis showed that carbohydrate antigen 19-9 (CA19-9) ≥37 U/ml ( HR=1.99, 95% CI: 1.10-3.60, P=0.024), ALBI≥-2.80 ( HR=2.43, 95% CI: 1.40-4.22, P=0.002), vascular tumor thrombus ( HR=2.34, 95% CI: 1.40-3.92, P=0.001), and the 8th edition AJCC N1 staging ( HR=2.18, 95% CI: 1.21-3.95, P=0.010) were independent risk factors affecting postoperative survival of ICC patients after curative resection. The predictive model constructed based on the above variables was then evaluated, and the C-index of the model was 0.76. Calibration curve showed the predicted survival curve of ICC patients at 3 years after surgery based on the model was well-fitted to the 45° diagonal line which represented actual survival. Clinical decision curve analysis showed that the model had a significant positive net benefit in both the training and validation sets. Conclusion:The nomograph model for survival rate after radical resection of ICC was constructed based on four variables: ALBI, CA19-9, vascular tumor thrombus, and AJCC N staging (8th edition) in this study. This model provided a reference for more accurate prognosis evaluation and treatment selection plan for ICC patients.

Objective:To establish and validate a preoperative differentiateon model of intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular carcinoma (CHC) based on the inflammatory markers and conventional clinical indicators.Methods:The clinical data of 116 patients with ICC or CHC admitted to Henan Provincial People's Hospital from January 2018 to March 2023 were retrospectively analyzed, including 74 males and 42 females, aged (58.5±9.4) years old. The data of 83 patients were used to establish the differentiation model as the training group, including 50 cases of ICC and 33 cases of CHC. The data of 33 patients were used to validate the model as the validation group, including 20 cases of ICC and 13 cases of CHC. The clinical data including the platelet-to-lymphocyte ratio (PLR), systemic immune inflammation index (SII), prognostic inflammatory index (PII), prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) were collected and analyzed. The receiver operating characteristic (ROC) curve was used to analyze the best cut-off values of PLR, SII, PII, PNI, NLR and LMR. Univariate and multivariate logistic regression analysis were used to determine the differential factors between ICC and CHC. The R software was used to draw the nomogram, calculate the area under the curve (AUC) to evaluate the model accuracy, and draw the calibration chart and the decision curve to evaluate the predictive efficacy of the model.Results:Univariate logistic regression analysis showed that liver cirrhosis, history of hepatitis, alpha fetoprotein, carbohydrate antigen 199, gamma-glutamyltransferase (GGT), PLR, PNI and inflammation score (IS) could be used to differentiate ICC from CHC (all P<0.05). The indicators identified in univariate analysis were included in multivariate logistic regression analysis. The results showed that absence of liver cirrhosis, GGT>60 U/L, PNI>49.53, and IS<2 indicated the pathology of ICC (all P<0.05). Based on the above four factors, a nomogram model was established to differentiate the ICC and CHC. The AUC of ROC curve of the nomogram model in the training and validation groups were 0.851 (95% CI: 0.769-0.933) and 0.771 (95% CI: 0.594-0.949), respectively. The sensitivities were 0.760 and 0.750, and the specificities were 0.818 and 0.769, respectively. The calibration chart showed that the predicted curve fitted well to the reference line. The decision curve showed that the model has a clear positive net benefit. Conclusion:The nomogram model based on inflammatory markers showed a good differentiation performance of ICC and CHC, which could benefits the individualized treatment.

Objective:A predictive nomogram model for the prognosis of intrahepatic cholangiocarcinoma (ICC) patients after curative resection was constructed based on the albumin-bilirubin score and tumor burden score (ATS) grade, and the predictive performance of the nomogram model was evaluated.Methods:Retrospective analysis of clinical data was made, from ICC patients who underwent curative resection at Zhengzhou University People's Hospital and Zhengzhou University Cancer Hospital from January 2016 to January 2020. A total of 258 patients were included in the study, with 140 males and 118 females, with an average age of (56.5±9.5) years. The 258 ICC patients were randomly divided into a training set ( n=174) and a testing set ( n=84) in a 7∶3 ratio. Single-factor and multi-factor Cox regression analyses were performed to identify prognostic factors for ICC patients of the training set, and then a nomogram model was constructed. The performance of the nomogram model was evaluated by using the concordance index (C-index), calibration curve, and risky decision curve analysis. Results:In the training set, univariate Cox regression analysis indicated that albumin-bilirubin (ALBI), tumor burden score (TBS), carcinoembryonic antigen (CEA), tumor differentitation, lymphvascular invasion and ATS significantly influenced overall survival after radical resection for ICC (all P<0.05). Multifactorial Cox regression analysis revealed that ATS grade, CEA, tumor differentiation, lymphovascular invasion, and AJCC N stage are independent risk factors for the prognosis of ICC patients after curative resection (all P<0.05). Assessment of the postoperative survival prediction model based on multifactorial Cox regression yielded a C-index of 0.775(95% CI: 0.747-0.841) for the training set and 0.731(95% CI: 0.668-0.828) for the testing set. The calibration curves for both the training and testing sets indicated strong predictive capability of the model. Additionally, the risk decision curve also suggested high net benefit of the model. Conclusions:The preoperative ATS grade is an independent factor affecting the survival after ICC radical resection. The nomogram model constructed based on ATS grade demonstrates excellent predictive value for postoperative prognosis in ICC patients.

Objective:To explore the prognostic value of systemic immune-inflammatory index(SII)combined with tumor burden score (TBS) (hereinafter referred to as STS) in patients with intrahepatic cholangiocarcinoma (ICC) after radical resection, and to construct a nomogram model.Methods:The clinical data (including the degree of tumor differentiation, vascular cancer thrombus, and lymph node metastasis, etc.) of 258 ICC patients who received radical resection at People′s Hospital of Zhengzhou University (170 cases, training set) and Cancer Hospital of Zhengzhou University (88 cases, validation set) from January 1, 2016 to January 31, 2020 were retrospectively analyzed and graded by SII, TBS and STS. Multivariate Cox regression analysis were used to identify independent factors affecting the prognosis of patients with ICC. Kaplan-Meier survival curve and receiver operating characteristic curve (ROC) were drawn to evaluate the predictive efficiency of SII, TBS and STS in the overall survival of patients with ICC after radical resection. The nomogram prediction model was constructed and evaluate the performance of nomogram model using consistency index (C-index) and calibration curve.Results:Among 170 ICC patients in the training set, there were 106 cases of SII grade 1 and 64 cases of SII grade 2; 137 cases of TBS grade 1 and 33 cases of TBS grade 2; and 98 cases of STS grade 1, 47 cases of STS grade 2, and 25 cases of STS grade 3. Among 88 ICC patients in the validation set, there were 33 cases of SII grade 1 and 55 cases of SII grade 2; 66 cases of TBS grade 1 and 22 cases of TBS grade 2; and 30 case of STS grade 1, 39 cases of TBS grade 2, and 19 cases of TBS grade 3.The multivariate Cox regression analysis showed that tumor differentiation degree (highly differentiated vs. moderately differentiated HR=0.157, 95% confidence interval(95% CI) 0.045 to 0.546, highly differentiated vs. poorly differentiated HR=0.452, 95% CI 0.273 to 0.750), STS (grade 3 vs. grade 2 HR=1.966, 95% CI 1.148 to 3.469; grade 3 vs. grade 1 HR=1.405, 95% CI 0.890 to 2.216), vascular cancer thrombus ( HR=2.006, 95% CI 1.313 to 3.066), nerve invasion ( HR=1.865, 95% CI 1.221 to 2.850), and lymph node metastasis ( HR=1.802, 95% CI 1.121 to 2.896) were independent influencing factors of overall survival in ICC patients after radical resection (all P<0.05). The Kaplan-Meier survival curve showed that SII, TBS, and STS were independent influencing factors of overall survival in ICC patients (all P<0.05). The results of ROC analysis showed that the areas under the curve of SII, TBS and STS in predicting overall survival of ICC patients after radical resection were 0.566 (95% CI 0.479 to 0.652), 0.585 (95% CI 0.499 to 0.672), and 0.657 (95% CI 0.522 to 0.692), respectively. Tumor differentiation, vascular tumor thrombus, nerve invassion, lymph node metastasis, and STS were included to constract the nomogram model. The C-indexes of the training set and validation set based on the nomogram model were 0.792 (95% CI 0.699 to 0.825) and 0.776 (95% CI 0.716 to 0.833), respectively. The calibration curves of the survival rate of the training set and the validation set were close to the reference lines, and the nomogram model had better predictive ability in both the training set and the validation set. Conclusions:Preoperative STS grading is an effective and practical predictor of overall survival in ICC patients after radical section. Compared with SII and TBS alone, it has better predictive value for the prognosis of patients with ICC.