BMC surgery · 2026
Analysis of predictive factors and development of a nomogram for complicated acute appendicitis in adults.
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Yu Jin, Li Shixing, Ma Yulin
Аннотация
BACKGROUND: The number of patients receiving conservative treatment for acute appendicitis is currently increasing. However, for complicated acute appendicitis (CAA), surgical treatment yields more definitive outcomes, and delayed surgery increases the risk of complications. Therefore, this study aimed to analyze the predictive factors for CAA and establish a nomogram.
METHODS: Patients who underwent appendectomy between January 2023 and October 2025 were included. Univariate and multivariate analyses were performed to identify predictive factors and independent predictive factors, respectively. A nomogram prediction model was constructed to visualize these factors. The performance of the prediction model was evaluated via receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).
RESULTS: The incidence of CAA was 25.24%. Analysis revealed six factors as independent predictors associated with CAA in acute appendicitis: age [OR 3.697 (95% CI 1.774-7.704)], body temperature [OR 3.235 (95% CI 1.367-7.656)], neutrophil percentage [OR 2.317 (95% CI 1.123-4.782)], C-reactive protein (CRP) [OR 12.434 (95% CI 5.525-27.982)], appendix diameter [OR 30.731 (95% CI 15.189-62.177)], and appendiceal fecalith [OR 6.968 (95% CI 3.544-13.698)]. A risk prediction model was developed on the basis of these factors and presented as a nomogram. The area under the ROC curve was 0.959, with a sensitivity of 87.3% and specificity of 90.3%. The calibration curve showed a mean absolute error of 0.014, and the DCA indicated favorable clinical net benefit.
CONCLUSION: Age, body temperature, neutrophil percentage, CRP level, appendix diameter, and the presence of an appendiceal fecalith are predictive factors for CAA. The established nomogram can effectively predict the risk of CAA.
METHODS: Patients who underwent appendectomy between January 2023 and October 2025 were included. Univariate and multivariate analyses were performed to identify predictive factors and independent predictive factors, respectively. A nomogram prediction model was constructed to visualize these factors. The performance of the prediction model was evaluated via receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).
RESULTS: The incidence of CAA was 25.24%. Analysis revealed six factors as independent predictors associated with CAA in acute appendicitis: age [OR 3.697 (95% CI 1.774-7.704)], body temperature [OR 3.235 (95% CI 1.367-7.656)], neutrophil percentage [OR 2.317 (95% CI 1.123-4.782)], C-reactive protein (CRP) [OR 12.434 (95% CI 5.525-27.982)], appendix diameter [OR 30.731 (95% CI 15.189-62.177)], and appendiceal fecalith [OR 6.968 (95% CI 3.544-13.698)]. A risk prediction model was developed on the basis of these factors and presented as a nomogram. The area under the ROC curve was 0.959, with a sensitivity of 87.3% and specificity of 90.3%. The calibration curve showed a mean absolute error of 0.014, and the DCA indicated favorable clinical net benefit.
CONCLUSION: Age, body temperature, neutrophil percentage, CRP level, appendix diameter, and the presence of an appendiceal fecalith are predictive factors for CAA. The established nomogram can effectively predict the risk of CAA.