• Sascha Vaghiri, Sarah Krieg, Dimitrios Prassas, Sven Heiko Loosen, Christoph Roderburg, Tom Luedde, Wolfram Trudo Knoefel, and Andreas Krieg.
• Department of Surgery (A), Heinrich-Heine-University, University Hospital Duesseldorf, 40225 Duesseldorf, Germany.
• Medicina (Kaunas). 2023 Jun 4; 59 (6).

AbstractBackground 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.

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