Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Front Cell Infect Microbiol. 2021 Sep 6;11:723666. doi: 10.3389/fcimb.2021.723666. eCollection 2021.
Risk factors for the development of pneumonia among patients with diabetes mellitus are unclear. The aim of our study was to elucidate the potential risk factors and attempt to predict the probability of pneumonia based on the history of diabetes.
We performed a population-based, prospective multicenter cohort study of 1,043 adult patients with diabetes in China during 2017-2019. Demographic information, comorbidities, or laboratory examinations were collected.
The study included 417 diabetic patients with pneumonia and 626 no-pneumonia-onset diabetic patients. The predictive risk factors were chosen on the basis of a multivariate logistic regression model to predict pneumonia among patients with diabetes including male sex [odds ratio (OR) = 1.72, 95% confidence interval (CI): 1.27-2.33, p < 0.001], age ≥ 75 years (OR = 2.31, 95% CI: 1.61-3.31, p < 0.001), body mass index < 25 (OR = 2.59, 95% CI: 1.92-3.50, p < 0.001), chronic obstructive pulmonary disease (OR = 6.58, 95% CI: 2.09-20.7, p = 0.001), hypertension (OR = 4.27, 95% CI: 3.12-5.85, p < 0.001), coronary heart disease (OR = 2.98, 95% CI: 1.61-5.52, p < 0.001), renal failure (OR = 1.82, 95% CI: 1.002-3.29, p = 0.049), cancer (OR = 3.57, 95% CI: 1.80-7.06, p < 0.001), use of insulin (OR = 2.28, 95% CI: 1.60-3.25, p < 0.001), and hemoglobin A1c ≥ 9% (OR = 2.70, 95% CI: 1.89-3.85, p < 0.001). A predictive nomogram was established. This model showed c-statistics of 0.811, and sensitivity and specificity were 0.717 and 0.780, respectively, under cut-off of 125 score.
We designed a clinically predictive tool for assessing the risk of pneumonia among adult patients with diabetes. This tool stratifies patients into relevant risk categories and may provide a basis for individually tailored intervention for the purpose of early prevention.
糖尿病患者发生肺炎的危险因素尚不清楚。本研究旨在阐明潜在的危险因素,并尝试根据糖尿病病史预测肺炎发生的概率。
我们对 2017 年至 2019 年期间中国的 1043 名成年糖尿病患者进行了一项基于人群的前瞻性多中心队列研究。收集了人口统计学信息、合并症或实验室检查结果。
本研究纳入了 417 例糖尿病合并肺炎患者和 626 例无肺炎发作的糖尿病患者。基于多变量逻辑回归模型选择预测肺炎的危险因素,包括男性(比值比 [OR] = 1.72,95%置信区间 [CI]:1.27-2.33,p < 0.001)、年龄≥75 岁(OR = 2.31,95%CI:1.61-3.31,p < 0.001)、体重指数<25(OR = 2.59,95%CI:1.92-3.50,p < 0.001)、慢性阻塞性肺疾病(OR = 6.58,95%CI:2.09-20.7,p = 0.001)、高血压(OR = 4.27,95%CI:3.12-5.85,p < 0.001)、冠心病(OR = 2.98,95%CI:1.61-5.52,p < 0.001)、肾衰竭(OR = 1.82,95%CI:1.002-3.29,p = 0.049)、癌症(OR = 3.57,95%CI:1.80-7.06,p < 0.001)、使用胰岛素(OR = 2.28,95%CI:1.60-3.25,p < 0.001)和糖化血红蛋白≥9%(OR = 2.70,95%CI:1.89-3.85,p < 0.001)。建立了一个预测模型。该模型的 C 统计量为 0.811,截断值为 125 分时,敏感性和特异性分别为 0.717 和 0.780。
我们设计了一种用于评估成年糖尿病患者肺炎风险的临床预测工具。该工具将患者分为相关风险类别,可能为早期预防提供个体化干预的依据。