Prioritization, patient selection, and multimodal perioperative management of colorectal cancer facing health-care system saturation

Abstract

Objective: The aim is to analyze the usefulness of pre-operative COVID-19 screening to detect asymptomatic patients, the capability of our patient selection algorithm to detect patients with more advanced tumors and the results of colorectal cancer surgery managed with a multimodal approach. We propose the use of a preoperative patient selection algorithm to prioritize the surgical treatment of patients with worse oncological prognosis and lower perioperative risk in situations of health system saturation. Material and methods: Prospective descriptive study including 71 patients operated on for colorectal cancer during COVID-19's high incidence period. A division was made into two periods of time that were later compared with the aim of assessing whether the scale used identified those patients with lower surgical risk and higher oncological priority for their priority scheduling. Results: Post-operative severe acute respiratory syndrome coronavirus 2 infection occurred in one patient (1.4%). Pre-operative polymerase chain reaction detected one asymptomatic patient (3%). Tumor stage was ≥ IIIA in 39% and node positive in 39% of patients in the first period, while 26% and 21% in the second period, respectively (p = 0.320; p = 0.179), without increasing the surgical stay or complications. Median hospital stay was 5 days. Grades III and IV morbidity were 4.4% and 1.4%. Conclusion: The use of an algorithm and Patient Selection Scale can detect patients with more advanced tumors to be operated before. Multimodal management/ERAS have a role in achieving short stay and low morbidity.