Construction of a Model for Predicting the Severity of Diverticular Bleeding in an Elderly Population

INTERNAL MEDICINE(2022)

引用 0|浏览0
暂无评分
摘要
Objective To identify the risk factors for severe diverticular bleeding in an elderly population. Methods Using a comprehensive computerized hospital database, severe and non-severe diverticular bleeding cases were compared for 19 factors: the age, sex, body mass index, comorbid conditions (hypertension, cardiovascular disease, cerebrovascular disease, and chronic renal failure, including those undergoing dialysis), history of diverticular bleeding, use of low-dose aspirin, use of antiplatelet agent besides aspirin, use of anticoagulant agent, use of prednisolone, use of non-steroidal anti-inflammatory drugs, use of cyclooxygenase-2 selective inhibitors, changes in vital signs, hypoalbuminemia, bilateral diverticula, identification of bleeding lesion, and rebleeding. Severe bleeding was defined as the need for blood transfusion, emergency surgery, or vascular embolization. Patients A total of 258 patients were admitted for lower gastrointestinal bleeding between August 2010 and July 2020, among whom 120 patients over 65 years old diagnosed with diverticular bleeding were included in this study. Results Fifty-one patients (43%) had severe diverticular bleeding. Independent risk factors for severe diverticular bleeding were as follows: change in vital signs [odds ratio (OR), 5.23; 95% confidence interval (CI), 1.9-14.4; p=0.0014], hypoalbuminemia (OR, 12.3; 95% CI, 1.97-77.3; p=0.0073), bilateral diverticula (OR, 3.47; 95% CI, 1.33-9.02; p=0.011), and rebleeding (OR, 5.92; 95% CI, 2.21-15.8; p<0.001). The area under the receiver operating characteristic curve was 0.79 after cross validation. Conclusion Severe diverticular bleeding in elderly population may be predicted by changes in their vital signs, hypoalbuminemia, bilateral diverticula, and rebleeding.
更多
查看译文
关键词
Key words, diverticular bleeding, severity, elderly population
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要