Objective:To develop and validate a predictive model for massive hemorrhage during brain tumor resection in pediatric patients.Methods:A retrospective analysis was performed on the clinical data from pediatric patients who underwent elective brain tumor resection under general anesthesia at the Women and Children′s Medical Center Affiliated to Guangzhou Medical University from December 2016 to October 2023. The patients were randomly divided into model group and internal validation group in a ratio of 8∶2. Pediatric patients who underwent elective brain tumor resection under general anesthesia at Qilu Hospital of Shandong University from January 2021 to July 2024 were selected and served as external validation group. Relevant characteristic variables were screened through Lasso regression. A multivariate logistic regression was used to develop the model and plot the nomogram for intraoperative massive hemorrhage. The performance of the model was evaluated using the area under the receiver operating characteristic curve and calibration curve.Results:Through Lasso regression and multivariate logistic regression analyses, 11 independent influencing factors were identified: age ( OR=0.323, 95% confidence interval [ CI]: 0.280-0.374, P<0.001), weight ( OR=0.164, 95% CI: 0.135-0.199, P<0.001), activated partial thromboplastin time ( OR=1.133, 95% CI: 1.036-1.239, P=0.006), thrombin time ( OR=1.141, 95% CI: 1.048-1.243, P=0.002), red blood cell count ( OR=0.941, 95% CI: 0.888-0.996, P=0.035), hemoglobin concentration ( OR=0.873, 95% CI: 0.822-0.926, P<0.001), platelet count ( OR=1.062, 95% CI: 1.001-1.127, P=0.048), maximum tumor diameter ( OR=2.384, 95% CI: 2.241-2.536, P<0.001), tumor invasiveness ( OR=2.376, 95% CI: 2.071-2.726, P<0.001), hydrocephalus ( OR=2.409, 95% CI: 2.139-2.713, P<0.001), and centered midline structure ( OR=0.509, 95% CI: 0.465-0.557, P<0.001). Based on this, a nomogram prediction model was established. The receiver operating characteristic curve showed that the area under the curve of this model in predicting the risk of massive hemorrhage during brain tumor resection was 0.936 (95% CI: 0.90-0.959) in model group, 0.863 (95% CI: 0.744-0.948) in internal validation group, and 0.855 (95% CI: 0.726-0.955) in external validation group. The calibration curve indicated good model consistency, and the Hosmer-Lemeshow goodness-of-fit test result showed a P value of 0.979 ( P>0.05). Conclusions:Age, body weight, activated partial thromboplastin time, thrombin time, red blood cell count, hemoglobin concentration, platelet count, maximum tumor diameter, tumor invasiveness, hydrocephalus and midline structure are independent influencing factors for major bleeding during brain tumor resection in pediatric patients, and the prediction model established based on this histogram has high accuracy.

Objective:To develop and validate a predictive model for massive hemorrhage during brain tumor resection in pediatric patients.Methods:A retrospective analysis was performed on the clinical data from pediatric patients who underwent elective brain tumor resection under general anesthesia at the Women and Children′s Medical Center Affiliated to Guangzhou Medical University from December 2016 to October 2023. The patients were randomly divided into model group and internal validation group in a ratio of 8∶2. Pediatric patients who underwent elective brain tumor resection under general anesthesia at Qilu Hospital of Shandong University from January 2021 to July 2024 were selected and served as external validation group. Relevant characteristic variables were screened through Lasso regression. A multivariate logistic regression was used to develop the model and plot the nomogram for intraoperative massive hemorrhage. The performance of the model was evaluated using the area under the receiver operating characteristic curve and calibration curve.Results:Through Lasso regression and multivariate logistic regression analyses, 11 independent influencing factors were identified: age ( OR=0.323, 95% confidence interval [ CI]: 0.280-0.374, P<0.001), weight ( OR=0.164, 95% CI: 0.135-0.199, P<0.001), activated partial thromboplastin time ( OR=1.133, 95% CI: 1.036-1.239, P=0.006), thrombin time ( OR=1.141, 95% CI: 1.048-1.243, P=0.002), red blood cell count ( OR=0.941, 95% CI: 0.888-0.996, P=0.035), hemoglobin concentration ( OR=0.873, 95% CI: 0.822-0.926, P<0.001), platelet count ( OR=1.062, 95% CI: 1.001-1.127, P=0.048), maximum tumor diameter ( OR=2.384, 95% CI: 2.241-2.536, P<0.001), tumor invasiveness ( OR=2.376, 95% CI: 2.071-2.726, P<0.001), hydrocephalus ( OR=2.409, 95% CI: 2.139-2.713, P<0.001), and centered midline structure ( OR=0.509, 95% CI: 0.465-0.557, P<0.001). Based on this, a nomogram prediction model was established. The receiver operating characteristic curve showed that the area under the curve of this model in predicting the risk of massive hemorrhage during brain tumor resection was 0.936 (95% CI: 0.90-0.959) in model group, 0.863 (95% CI: 0.744-0.948) in internal validation group, and 0.855 (95% CI: 0.726-0.955) in external validation group. The calibration curve indicated good model consistency, and the Hosmer-Lemeshow goodness-of-fit test result showed a P value of 0.979 ( P>0.05). Conclusions:Age, body weight, activated partial thromboplastin time, thrombin time, red blood cell count, hemoglobin concentration, platelet count, maximum tumor diameter, tumor invasiveness, hydrocephalus and midline structure are independent influencing factors for major bleeding during brain tumor resection in pediatric patients, and the prediction model established based on this histogram has high accuracy.

Objective: To investigate the interaction between traditional Chinese medicine (TCM) syndromes of histiocytic necrotizing lymphadenitis (HNL) and pathological types of HNL, so as to discover the distribution rule of TCM syndromes for indiction of intervention of HNL. Methods: A total of 166 patients with HNL were included. The baseline data of the patients, clinical feature, the four diagnosis information of TCM and histopathological of cervical lymph node were collected. The syndromes of TCM were judged. The pathological types were confirmed by cervical lymph node biopsy. The Multi-way ANOVA was used to analyze the correlation between traditional Chinese medicine syndromes of HNL and its pathological types. Results: Among the 166 patients, the ratio of different types are as follow: wind-heat and phlegm-toxin syndrome (57.83%, 96/166), heat-toxin exuberance syndrome (34.34%, 57/166), and phlegm and blood stasis syndrome (7.83%, 13/166). The pathological types include proliferative type (57.83%, 96/166), necrotizing type (35.54%, 59/166), and xanthomatous type (6.63%, 11/166). There were significant differences in targeted lymph node diameter, pain scores, body temperature (F value were 3.737, 34.484, 34.805, all Ps<0.05), while the difference of WBC (F=1.194, P>0.05) among three TCM Syndrome types were notsignificant. There were significant differences in pain scores, body temperature (F value were 12.153, 25.931, all Ps<0.05), but not for the targeted lymph node diameter, WBC (F value were 2.249, 0.671, all Ps>0.05) among three pathological types. The corresponding analysis result showed that, on point sets, wind-heat and phlegm-toxin syndrome were correlated with proliferative type, heat-toxin exuberance syndrome correlated with necrotizing type, and phlegm and blood stasis syndrome correlated with xanthomatous type (χ²=235.100, P<0.001). Conclusions There is a close correlation between syndrome types of TCM and pathological types of HNL. The pathological change of wind-heat and phlegm-toxin syndrometends toproliferative type, heat-toxin exuberance syndrome tends to necrotizing type, and phlegm and blood stasis syndrome tends to xanthomatous type.

Objective To investigate the influence of fixed nurse specialists triage to improve the quality of patient triage.Methods Nurses were divided into the fixed nurse specialist triage group (group A) and the out-patient department rotation nursing group (group B),respectively,each group was responsible for triage of patients in clinic of medical department for five days.Then the number of two subdiagnosis error and the average daily working overtime for doctors were compared.Results A total of 3806 patients were in clinic triage in group A,165 patients had triage error.A total of 3812 patients were in clinic triage in group B,308 patients had triage error.The average daily working overtime of doctors in group A was(5.24 ± 0.37)hours,and(8.16 ± 0.58) hours in group B.The errors in triage and working overtime of doctors had significant differences between two groups.Conclusions Fixed specialist nurse triage can significantly improve the quality of patient triage in clinic.

OBJECTIVETo observe the uptake of tiliani in Caco-2 Cell.

METHODA human intestinal epithelial cell model Caco-2 cell in vitro cultured was applied to study the kinetics of uptake, transport and efflux kinetics of tiliani at small intestine. The effect of time, pH, drug concentration and inhibitors on the uptake of tiliani were investigated. The determination of tiliani was performed by HPLC.

RESULTTiliani in Caco-2 cell uptake was time-dependent. Tiliani in Caco-2 cell uptake was concentration-dependent at 4-16 mg x L(-1) consistent with passive diffusion process. The acid condition was good for the uptake of tiliani at pH 5-8. Compared with the control group, tiliani cell uptake was significantly higher after additional treatmeant with verapamil (1.545 +/- 0.010) mg x g(-1), (P < 0.05), and tiliani cell uptake was significantly lower after additional treatmeanet with sodium azide (0.994 +/- 0.003) mg x g(-1) (P < 0.05), with 2,4-dinitrophenol (1.174 +/- 0.030) mg x g(-1) (P < 0.05), and with phloridzin (1.098 +/- 0.021) mg x g(-1) (P < 0.05). Compared with the control group, tiliani cell uptake was not significantly after additional treatmeant with lactose (1.470 +/- 0.025) mg x g(-1), Papp of Basolateral to Apical was much more than that of Apical to Basolateral (1.10 Fold).

CONCLUSIONP-glycoproteins and SGLT1 participate in the conveying process of tiliani in Caco-2 cells. The uptake of tiliani has no relationship to LPH. passive transport and carrier-mediated transport participate in the uptake process of tiliani in Caco-2 cells.

Biological Transport ; drug effects ; Caco-2 Cells ; Chromatography, High Pressure Liquid ; Flavonoids ; pharmacokinetics ; Glycosides ; pharmacokinetics ; Humans ; Intestinal Absorption ; Kinetics ; Verapamil ; pharmacology

Three-dimensional (3D) reconstruction of medical images constructs the 3D models of organs using 2D medical image serials, which provide intuitionistic visual information for medical workers. However, most people concern about the CT images reconstruction, only few people focus on the reconstruction of Ultrasound images. In this thesis, it introduces Insight Segmentation and Registration Toolkit (ITK) and The Visualization Toolkit (VTK) firstly. Then it presents the process of Ultrasound image serials using ITK and VTK. At last, it presents the outcome of the experiment. The results show that the reconstruction of Ultrasound images can also get good effect by using ITK and VTK.