Dokument: A New Nomogram-Based Prediction Model for Postoperative Outcome after Sigmoid Resection for Diverticular Disease
| Titel: | A New Nomogram-Based Prediction Model for Postoperative Outcome after Sigmoid Resection for Diverticular Disease | |||||||
| URL für Lesezeichen: | https://docserv.uni-duesseldorf.de/servlets/DocumentServlet?id=67093 | |||||||
| URN (NBN): | urn:nbn:de:hbz:061-20241017-135347-8 | |||||||
| Kollektion: | Publikationen | |||||||
| Sprache: | Englisch | |||||||
| Dokumententyp: | Wissenschaftliche Texte » Artikel, Aufsatz | |||||||
| Medientyp: | Text | |||||||
| Autoren: | Vaghiri, Sascha [Autor] Krieg, Sarah [Autor] Prassas, Dimitrios [Autor] Loosen, Sven H. [Autor] Roderburg, Christoph [Autor] Luedde, Tom [Autor] Knoefel, Wolfram Trudo [Autor] Krieg, Andreas [Autor] | |||||||
| Dateien: |
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| Stichwörter: | sigmoid diverticulitis, nomogram-based prediction, postoperative length of stay, morbidity and mortality | |||||||
| Beschreibung: | 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. | |||||||
| Rechtliche Vermerke: | Originalveröffentlichung:
Vaghiri, S., Krieg, S., Prassas, D., Loosen, S. H., Roderburg, C., Lüdde, T., Knoefel, W. T., & Krieg, A. (2023). A New Nomogram-Based Prediction Model for Postoperative Outcome after Sigmoid Resection for Diverticular Disease [OnlineRessource]. Medicina, 59(6), Article 1083. https://doi.org/10.3390/medicina59061083 | |||||||
| Lizenz: |  Dieses Werk ist lizenziert unter einer Creative Commons Namensnennung 4.0 International Lizenz | |||||||
| Fachbereich / Einrichtung: | Medizinische Fakultät | |||||||
| Dokument erstellt am: | 17.10.2024 | |||||||
| Dateien geändert am: | 17.10.2024 |
