Na Xi, Martin Alan J, Sethi Saurabh, Kyne Lorraine, Garey Kevin W, Flores Sarah W, Hu Mary, Shah Dhara N, Shields Kelsey, Leffler Daniel A, Kelly Ciarán P
Division of Gastroenterology, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, United States of America.
Department of Medicine for the Older Person, Mater Misericordiae University Hospital and University College Dublin, Dublin, Ireland.
PLoS One. 2015 Apr 23;10(4):e0123405. doi: 10.1371/journal.pone.0123405. eCollection 2015.
Prediction of severe clinical outcomes in Clostridium difficile infection (CDI) is important to inform management decisions for optimum patient care. Currently, treatment recommendations for CDI vary based on disease severity but validated methods to predict severe disease are lacking. The aim of the study was to derive and validate a clinical prediction tool for severe outcomes in CDI.
A cohort totaling 638 patients with CDI was prospectively studied at three tertiary care clinical sites (Boston, Dublin and Houston). The clinical prediction rule (CPR) was developed by multivariate logistic regression analysis using the Boston cohort and the performance of this model was then evaluated in the combined Houston and Dublin cohorts.
The CPR included the following three binary variables: age ≥ 65 years, peak serum creatinine ≥ 2 mg/dL and peak peripheral blood leukocyte count of ≥ 20,000 cells/μL. The Clostridium difficile severity score (CDSS) correctly classified 76.5% (95% CI: 70.87-81.31) and 72.5% (95% CI: 67.52-76.91) of patients in the derivation and validation cohorts, respectively. In the validation cohort, CDSS scores of 0, 1, 2 or 3 were associated with severe clinical outcomes of CDI in 4.7%, 13.8%, 33.3% and 40.0% of cases respectively.
We prospectively derived and validated a clinical prediction rule for severe CDI that is simple, reliable and accurate and can be used to identify high-risk patients most likely to benefit from measures to prevent complications of CDI.
艰难梭菌感染（CDI）严重临床结局的预测对于指导最佳患者护理的管理决策至关重要。目前，CDI的治疗建议因疾病严重程度而异，但缺乏预测严重疾病的有效方法。本研究的目的是推导并验证一种用于CDI严重结局的临床预测工具。
在三个三级医疗临床地点（波士顿、都柏林和休斯顿）对总共638例CDI患者进行了前瞻性研究。临床预测规则（CPR）通过使用波士顿队列进行多变量逻辑回归分析得出，然后在休斯顿和都柏林联合队列中评估该模型的性能。
CPR包括以下三个二元变量：年龄≥65岁、血清肌酐峰值≥2mg/dL和外周血白细胞计数峰值≥20,000个细胞/μL。艰难梭菌严重程度评分（CDSS）在推导队列和验证队列中分别正确分类了76.5%（95%CI：70.87-81.31）和72.5%（95%CI：67.52-76.91）的患者。在验证队列中，CDSS评分为0、1、2或3分别与4.7%、13.8%、33.3%和40.0%的CDI严重临床结局相关。
我们前瞻性地推导并验证了一种用于严重CDI的临床预测规则，该规则简单、可靠且准确，可用于识别最有可能从预防CDI并发症措施中获益的高危患者。
