1.Determination of 3-methyl-7,8-dihydroxy-isochroman-4-one in the peel of Musa sapientum
Hai QIAN ; Wenlong HUANG ; Guangling RAO ; Liang GE ; Xiaoming WU
Journal of China Pharmaceutical University 2009;40(6):524-526
Aim: To establish an HPLC method for the determination of 3-methyl-7, 8-dihydroxy-isochroman-4-one in the peel of Musa sapientum. Methods: A column of Shimadzu ODS-C_(18) column (250 mm × 4. 6 mm,5 μm), and a mobile phase of acetonitrile-water-phosphoric acid(9:91:0. 1) were adopted. A detect wavelength of 283 nm, a flow rate of 1 mL/min, and a column temperature of 35 ℃ were set. Results: The content of 3-methyl-7,8-dihydroxy-isochroman-4-one in the peel of Musa sapientum was 0.029 5%-0.036 7%. Calibration curve was linear over the range 1. 09-13. 08 μg. The average recovery was 100. 0%. The assay variability value was 0. 64 %(n=9). Conclusion: The method can be used for the quality control of Musa sapientum.
2.Establishment and validation of nomogram prediction model for complicated acute appendicitis
Hui FENG ; Qingsheng YU ; Jingxiang WANG ; Yiyang YUAN ; Wenlong RAO ; Xun LIANG ; Shushan YU ; Feisheng WEI
Chinese Journal of Surgery 2023;61(12):1074-1079
Objective:To establish and internally validate a nomogram model for predicting complicated acute appendicitis (CA).Methods:The clinical data from 663 acute appendicitis patients from the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine from October 2015 to October 2022 were retrospectively analyzed. There were 411 males and 252 females, aged ( M (IQR)) 41 (22) years (range: 18 to 84 years). There were 516 cases of CA and 147 cases of uncomplicated acute appendicitis. The minimum absolute contraction and selection operator regression model was used to screen the potential relative factors of CA, and the screened factors were included in the Logistic regression model for multivariate analysis. Software R was used to establish a preoperative CA nomogram prediction model, the receiver operating characteristic curve of the model was drawn, and the value of area under the curve (AUC) was compared to evaluate its identification ability, and the Bootstrap method was used for internal verification. Results:The elderly (age≥60 years) ( OR=2.428, 95% CI: 1.295 to 4.549), abdominal pain time (every rise of 1 hour) ( OR=1.089, 95% CI: 1.072 to 1.107), high fever (body temperature≥39 ℃) ( OR=1.122, 95% CI: 1.078 to 1.168), total bilirubin (every rise of 1 μmol/L) ( OR=2.629, 95% CI: 1.227 to 5.635) were independent relative factors of CA (all P<0.05). The AUC of this model was 0.935 (95% CI: 0.915 to 0.956). After internal verification using the Bootstrap method, the model still had a high discrimination ability (AUC=0.933), and the predicted CA curve was still in good agreement with the actual clinical CA curve. Conclusion:The clinical prediction model based on the elderly (age≥60 years), prolonged abdominal pain time, high fever (body temperature≥39 ℃), and increased total bilirubin can help clinicians effectively identify CA.
3.Establishment and validation of nomogram prediction model for complicated acute appendicitis
Hui FENG ; Qingsheng YU ; Jingxiang WANG ; Yiyang YUAN ; Wenlong RAO ; Xun LIANG ; Shushan YU ; Feisheng WEI
Chinese Journal of Surgery 2023;61(12):1074-1079
Objective:To establish and internally validate a nomogram model for predicting complicated acute appendicitis (CA).Methods:The clinical data from 663 acute appendicitis patients from the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine from October 2015 to October 2022 were retrospectively analyzed. There were 411 males and 252 females, aged ( M (IQR)) 41 (22) years (range: 18 to 84 years). There were 516 cases of CA and 147 cases of uncomplicated acute appendicitis. The minimum absolute contraction and selection operator regression model was used to screen the potential relative factors of CA, and the screened factors were included in the Logistic regression model for multivariate analysis. Software R was used to establish a preoperative CA nomogram prediction model, the receiver operating characteristic curve of the model was drawn, and the value of area under the curve (AUC) was compared to evaluate its identification ability, and the Bootstrap method was used for internal verification. Results:The elderly (age≥60 years) ( OR=2.428, 95% CI: 1.295 to 4.549), abdominal pain time (every rise of 1 hour) ( OR=1.089, 95% CI: 1.072 to 1.107), high fever (body temperature≥39 ℃) ( OR=1.122, 95% CI: 1.078 to 1.168), total bilirubin (every rise of 1 μmol/L) ( OR=2.629, 95% CI: 1.227 to 5.635) were independent relative factors of CA (all P<0.05). The AUC of this model was 0.935 (95% CI: 0.915 to 0.956). After internal verification using the Bootstrap method, the model still had a high discrimination ability (AUC=0.933), and the predicted CA curve was still in good agreement with the actual clinical CA curve. Conclusion:The clinical prediction model based on the elderly (age≥60 years), prolonged abdominal pain time, high fever (body temperature≥39 ℃), and increased total bilirubin can help clinicians effectively identify CA.