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Chinese Journal of Operative Procedures of General Surgery(Electronic Edition) ›› 2025, Vol. 19 ›› Issue (01): 48-51. doi: 10.3877/cma.j.issn.1674-3946.2025.01.014.

• Original Articles • Previous Articles    

Risk factors prediction model of parastostomy hernia based on sarcopenia

Ling Xi1, Hanwen Tong2, Ji Miao3, Yonghuan Mao3, Xiaofei Shen3,(), Junfeng Du4,(), Ye Liu1,()   

  1. 1.Department of Geriatrics,Geriatric Hospital of Nanjing Medical University,Nanjing Jiangsu Province 210024,China
    2.Department of Emergency,Nanjing Drum Tower Hospital,Nanjing Jiangsu Province 210008,China
    3.Department of General Surgery,Nanjing Drum Tower Hospital,Nanjing Jiangsu Province 210008,China
    4.Department of General Surgery,The 7th Medical Center,Chinese People’s Liberation Army (PLA) General Hospital,Beijing 100700,China
  • Received:2024-03-16 Online:2025-02-26 Published:2024-12-12
  • Contact: Xiaofei Shen, Junfeng Du, Ye Liu

Abstract:

Objective

To investigate whether sarcopenia is an independent risk factor for parastostomy hernia, and build a prediction model based on sarcopenia.

Methods

Data of 126 patients undergoing enterostomy from January 2018 to December 2022 were retrospectively analyzed.Skeletal muscle index (SMI) was calculated by preoperative abdominal CT scan.Sarcosis was defined as female <32.4cm2/m2 and male <44.3cm2/m2.According to whether the patients had postoperative parastostomy hernia, the patients were divided into parastostomy hernia group (n=17 cases) and non-parastostomy hernia group (n=109 cases).The baseline, intraoperative and postoperative data of the patients were analyzed to determine whether sarcopenia was an independent risk factor for parastostomy hernia by univariate and multifactorial analysis, and Nomogram was drawn to show the risk factors for parastostomy hernia.SPSS 25.0 and R 4.1.3 statistical software were used for analysis.Continuous variables are expressed as (x± s).Chi-square test, Fisher exact probability method and t test were used to analyze the difference between categorical variables and continuous variables.P<0.05 was considered to be statistically significant.

Results

Among the 126 patients, the incidence of sarcopenia was 38.9% (49/126), and the incidence of parastostomy hernia was 24.5% (12/49) in the sarcopenia group, while the incidence of parastostomy hernia was 6.5% (5/77) in the non-sarcopenia group, suggesting a correlation between sarcopenia and parastostomy hernia (P=0.004).Further univariate and multivariate Logistic regression analysis indicated that age ≥71 years, colostomy and sarcopenia were independent risk factors for parastostomy hernia.

Conclusion

Abdominal CT is a simple method to evaluate SMI in the diagnosis of sarcopenia.Sarcopenia is an important risk factor for parastostomy hernia after enterostomy (P=0.015), and the prediction model of parastostomy hernia based on sarcopenia has good clinical practicability.Preoperative screening of enterostomy patients for sarcopenia and corresponding intervention measures may reduce the incidence of parastostomy hernia and improve symptoms.

Key words: Sarcopenia, Enterostomy, Parastostomal Hernia, Prediction Model

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