The Consequences of the COVID-19 Pandemic on Emergency Surgery for Colorectal Cancer.
Catalin Vladut Ionut FeierSonia RatiuCalin MunteanSorin OlariuPublished in: International journal of environmental research and public health (2023)
The aim of this study is to analyze the impact of the COVID-19 pandemic on the emergency treatment of patients with colorectal cancer in a university surgery clinic. Data from patients undergoing emergency surgery during the pandemic period (2020-2021) was taken into consideration and the results were analyzed and compared with the periods 2016-2017 and 2018-2019. A significant decrease in the number of patients undergoing emergency surgery was reported ( p = 0.028). The proportion of patients who presented more severe symptoms at the hospital was significantly higher ( p = 0.007). There was an increase in the average duration of surgical interventions compared to pre-pandemic periods ( p = 0.021). An increase in the percentage of stomas performed during the pandemic was reported. The average duration of postoperative hospitalization was shorter during the pandemic. A postoperative mortality of 25.7% was highlighted. Conclusions: The pandemic generated by COVID-19 had significant consequences on the emergency treatment of patients with colon cancer. A smaller number of patients showed up at the hospital, and with more severe symptoms. In order to reduce the risk of infection with SARS-CoV-2 virus, the postoperative hospitalization period was shortened and a higher number of protective stomas were performed.
Keyphrases
- sars cov
- patients undergoing
- coronavirus disease
- minimally invasive
- public health
- coronary artery bypass
- emergency department
- healthcare
- respiratory syndrome coronavirus
- surgical site infection
- end stage renal disease
- primary care
- early onset
- chronic kidney disease
- type diabetes
- cardiovascular events
- peritoneal dialysis
- risk factors
- depressive symptoms
- prognostic factors
- acute coronary syndrome
- coronary artery disease
- ejection fraction
- acute care
- deep learning
- replacement therapy
- artificial intelligence
- combination therapy
- data analysis