Abstract
Acute appendicitis is the most common general surgical emergency worldwide; however, its diagnosis remains challenging, particularly in rural or remote areas such as Tibet. This study aimed to investigate the clinical characteristics and applicability of the routine risk prediction models of acute appendicitis for rural Tibetan populations. Data of patients who underwent appendectomy at the Chaya People's Hospital between 1 April 2018 and 30 September 2021 were retrospectively collected. Multivariate logistic regression analysis was performed to identify risk factors associated with complicated appendicitis. The appendicitis risk prediction model scores for each patient were calculated by the binary logistic regression model based on the data. The index of union method was applied to identify the optimal cut-off value for the critical values of risk prediction models. We included 127 patients with suspected acute appendicitis in the study, consisting of 96 surgically and 31 non-surgically treated. The diagnoses of 93 patients who underwent appendectomy included 55 (59.1%) cases of uncomplicated appendicitis. Patients with complicated appendicitis had a significantly longer postoperative hospital stay (11.0 (interquartile range 8.8-13.3) days v 8.0 (interquartile range 6.0-11.0) days; p<0.001) and higher hospital costs (US$2147.2 (interquartile range US$1625.1-2516.6) v US$1487.9 (interquartile range US$1202.6-1809.2); p24 hours, age >30 years, and male sex were independent risk factors associated with complicated appendicitis. The appendicitis inflammatory response score showed the best performance among the prediction models. Incorporating imaging features in the prediction models may provide better diagnostic value for appendicitis. Acute appendicitis in the rural Tibetan population has unique clinical features. To reduce the incidence of complicated appendicitis, local health workers must balance religious beliefs and professional services for residents.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.