Wei P.-L.Lin H.-C.Kao L.-T.Chen Y.-H.Lee, Cha-ZeCha-ZeLee2021-02-022021-02-0220160002-9610https://www.scopus.com/inward/record.uri?eid=2-s2.0-84975221983&doi=10.1016%2fj.amjsurg.2015.08.041&partnerID=40&md5=14c2237fc50a8cb33daf8a3fd82a76e9https://scholars.lib.ntu.edu.tw/handle/123456789/545824Background The purpose of this study was to investigate the relationship between perforated appendicitis and patient with diabetes using a population-based data set. Methods This study used data from the Longitudinal Health Insurance Database 2005 in Taiwan. We identified 4,806 patients hospitalized with acute appendicitis. The independent variable was whether a patient had ever received a diagnosis of diabetes before the index hospitalization. We performed a conditional logistic regression model to explore the odds ratio and its corresponding 95% confidence interval of perforated appendicitis. Results Rates of perforated appendicitis for patients with and those without diabetes were 46.2% and 28.3%, respectively. A chi-square test revealed that there was a significant difference in rates of perforated appendicitis between patients with and those without diabetes (P < .001). The conditional logistic regression model revealed that the adjusted odds ratio of perforated appendicitis for patients with diabetes was 1.35 (95% confidence interval = 1.11 to 1.65) compared with patients without diabetes. Conclusions Our study demonstrated that a history of diabetes is an important factor with regard to the rate of perforated appendicitis. ? 2016 Elsevier Inc.Appendix; Diabetes; Perforated appendicitis[SDGs]SDG3acute appendicitis; adult; appendix perforation; Article; controlled study; data base; diabetes mellitus; disease association; evidence based medicine; female; health insurance; human; major clinical study; male; population research; priority journal; Taiwan; appendicitis; diabetes mellitus; factual database; middle aged; risk factor; statistical model; Adult; Appendicitis; Databases, Factual; Diabetes Mellitus; Female; Humans; Logistic Models; Male; Middle Aged; Risk Factors; Taiwanjournal article10.1016/j.amjsurg.2015.08.041272557802-s2.0-84975221983