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.

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.