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Robot-assisted Total Mesorectal Excision and Lateral Pelvic Lymph Node Dissection for Locally Advanced Middle-low Rectal Cancer
Published on: February 12, 2022
Postoperative morbidity following chemoradiation for locally advanced low rectal cancer
Ingrid Stelzmueller1, Matthias Zitt, Felix Aigner
1Department of Visceral, Transplant, and Thoracic Surgery, Center of Operative Medicine, Innsbruck Medical University, Anichstrasse 35, 6020, Innsbruck, Austria.
Background:
Postoperative morbidity remains a significant clinical problem and may alter long-term outcome particularly after neoadjuvant chemoradiation in patients with locally advanced low rectal cancer. The aim of the present study was to identify a potential long-term effect of postoperative morbidity.
Methods:
Analysis of prospectively collected data of 90 consecutive patients who underwent neoadjuvant chemoradiation and curative mesorectal excision for locally advanced (cT3/4, Nx, M0/1) adenocarcinoma of the mid and lower third of the rectum during a 7-year period (1996-2002).
Results:
Major postoperative complications occurred in 17.8% and minor complications in 26.6% of patients. Hospital mortality and 30-day mortality was 0%. Infectious complications were seen in 34.5%. The leading causes of infectious complications were anastomotic leakage and perineal wound infection. Postoperative morbidity was statistically significantly associated with gender (P < 0.05), pre-therapeutic haemoglobin level (P < 0.05), ASA score (P < 0.05), hospitalisation (P < 0.001) and clinical long-time course (P < 0.01). Moreover, early postoperative morbidity was proven as an independent prognostic factor concerning disease-free (P < 0.05) and overall survival (P < 0.05).
Conclusion:
Early postoperative morbidity in patients with preoperative chemoradiation due to locally advanced low rectal cancer is demonstrated as an independent prognosticator. Gender, pre-therapeutic haemoglobin level and ASA score indicate patients at risk for early postoperative complications and may therefore serve as predictive features.
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