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A New Nomogram-Based Prediction Model for Postoperative Outcome after Sigmoid Resection for Diverticular Disease

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  • معلومة اضافية
    • بيانات النشر:
      MDPI AG, 2023.
    • الموضوع:
      2023
    • نبذة مختصرة :
      Background and Objectives: Sigmoid resection still bears a considerable risk of complications. The primary aim was to evaluate and incorporate influencing factors of adverse perioperative outcomes following sigmoid resection into a nomogram-based prediction model. Materials and Methods: Patients from a prospectively maintained database (2004–2022) who underwent either elective or emergency sigmoidectomy for diverticular disease were enrolled. A multivariate logistic regression model was constructed to identify patient-specific, disease-related, or surgical factors and preoperative laboratory results that may predict postoperative outcome. Results: Overall morbidity and mortality rates were 41.3% and 3.55%, respectively, in 282 included patients. Logistic regression analysis revealed preoperative hemoglobin levels (p = 0.042), ASA classification (p = 0.040), type of surgical access (p = 0.014), and operative time (p = 0.049) as significant predictors of an eventful postoperative course and enabled the establishment of a dynamic nomogram. Postoperative length of hospital stay was influenced by low preoperative hemoglobin (p = 0.018), ASA class 4 (p = 0.002), immunosuppression (p = 0.010), emergency intervention (p = 0.024), and operative time (p = 0.010). Conclusions: A nomogram-based scoring tool will help stratify risk and reduce preventable complications.
    • File Description:
      application/pdf
    • ISSN:
      1648-9144
    • الرقم المعرف:
      10.3390/medicina59061083
    • Rights:
      CC BY
    • الرقم المعرف:
      edsair.doi.dedup.....4eefde50cae65de92c2f09f5ad81de84