Validation of Clinical Risk Models for Clostridioides difficile-Attributable Outcomes.
Validation of Clinical Risk Models for Clostridioides difficile-Attributable Outcomes.
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DOI：
10.1128/aac.00676-22
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发表时间：
2022-07-19
影响因子：
4.9
通讯作者：
中科院分区：
文献类型：
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作者：
艰难梭状芽孢杆菌是主要的卫生保健相关病原体，导致相当大的发病率和死亡率；然而，没有被广泛接受的模型来预测艰难梭菌感染的严重程度。大多数目前可用的模型表现不佳，或者被校准以预测与临床无关的结果。我们试图验证六个主要的风险模型(年龄治疗、白细胞白蛋白-血清肌酐(ATLAS)、艰难梭菌病(CDD)、ZAR、Hensgen、Shivarhankar和艰难梭菌严重程度评分(CDSS))、指南严重程度标准和预测艰难梭菌引起的严重结局(住院死亡率、结肠切除/回肠吻合术或败血症重症监护)的聚合酶链式反应周期阈值。模型使用诊断后±48 小时内可用的电子数据(分配了零点的不可用实验室测量)计算，使用跨越10 年的3,327名住院患者的大型回顾队列进行校准，并使用接受者操作特征和精确召回曲线进行比较。Atlas获得的ROC曲线下面积(AUROC)最高为0.781，明显好于表现次之的模型(ZAR 0.745；AUROC差异的95%可信区间0.0094-0.6222；P = 0.008)，以及精度-召回曲线下的最高面积0.232。目前的IDSA/SHEA严重程度标准表现中等(AUROC 0.738)，而聚合酶链式反应周期阈值表现最差(0.531)。所有模型的总体预测价值都很低，最大阳性预测值为37.9%(ATLAS截止≥9)。没有一个临床模型在外部验证上表现良好，但在预测艰难梭菌临床相关诊断结果方面，ATLAS确实优于其他模型。应该寻求新的标记物来增强或取代表现不佳的仅用于临床的模型。
Clostridioides difficile is the leading health care-associated pathogen, leading to substantial morbidity and mortality; however, there is no widely accepted model to predict C. difficile infection severity. Most currently available models perform poorly or were calibrated to predict outcomes that are not clinically relevant. We sought to validate six of the leading risk models (Age Treatment Leukocyte Albumin Serum Creatinine (ATLAS), C. difficile Disease (CDD), Zar, Hensgens, Shivashankar, and C. difficile Severity Score (CDSS)), guideline severity criteria, and PCR cycle threshold for predicting C. difficile-attributable severe outcomes (inpatient mortality, colectomy/ileostomy, or intensive care due to sepsis). Models were calculated using electronic data available within ±48 h of diagnosis (unavailable laboratory measurements assigned zero points), calibrated using a large retrospective cohort of 3,327 inpatient infections spanning 10 years, and compared using receiver operating characteristic (ROC) and precision-recall curves. ATLAS achieved the highest area under the ROC curve (AuROC) of 0.781, significantly better than the next best performing model (Zar 0.745; 95% confidence interval of AuROC difference 0.0094–0.6222; P = 0.008), and highest area under the precision-recall curve of 0.232. Current IDSA/SHEA severity criteria demonstrated moderate performance (AuROC 0.738) and PCR cycle threshold performed the worst (0.531). The overall predictive value for all models was low, with a maximum positive predictive value of 37.9% (ATLAS cutoff ≥9). No clinical model performed well on external validation, but ATLAS did outperform other models for predicting clinically relevant C. difficile-attributable outcomes at diagnosis. Novel markers should be pursued to augment or replace underperforming clinical-only models.
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DOI：
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发表时间：
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期刊：
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影响因子：
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发表时间：
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期刊：
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