Risk prediction models for mortality in patients with ventilator-associated pneumonia: A systematic review and meta-analysis

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• 作者：Johan Larsson ; MD ; ^{johanlarsson923@gmail.com} ; Theis Skovsgaard Itenov ; MD ^{theis.skovsgaard.itenov@regionh.dk} ; Morten Heiberg Bestle ; MD ; PhD ^{morten.bestle@regionh.dk}
• 关键词：Ventilator-associated pneumonia ; Intensive care unit ; Severity score ; Receiver operator characteristic curve ; Area under the curve ; Mortality
• 刊名：Journal of Critical Care
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：37
• 期：Complete
• 页码：112-118
• 全文大小：846 K
• 卷排序：37

文摘

Ventilator-associated pneumonia (VAP) is a common and serious complication in patients requiring mechanical ventilation in the intensive care unit. The aims of this study were to identify models used to predict mortality in VAP patients and to assess their prognostic accuracy.MethodsThe PubMed and EMBASE were searched in February 2016. We included studies in English that evaluated models' ability to predict the risk of mortality in patients with VAP. The reported mortality with the longest follow-up was used in the meta-analysis. Prognostic accuracy was measured with the area under the receiver operator characteristic curve (AUC).ResultsWe identified 19 articles studying 7 different models' ability to predict mortality in VAP patients. The models were Acute Physiology and Chronic Health Evaluation (APACHE) II (9 studies, n = 1398); Clinical Pulmonary Infection Score (4 studies, n = 303); “Immunodeficiency, Blood pressure, Multilobular infiltrates on chest radiograph, Platelets and hospitalization 10 days before onset of VAP” (3 studies, n = 406); “VAP Predisposition, Insult Response and Organ dysfunction” (2 studies, n = 589); Sequential Organ Failure Assessment (7 studies, n = 1019); Simplified Acute Physiology Score II (6 studies, n = 1043); and APACHE III (1 study, n = 198). APACHE II had the highest pooled AUC (95% confidence intervals), 0.72 (0.64-0.80), and CPIS had the lowest pooled AUC, 0.64 (0.55-0.72).ConclusionWe identified 7 models that have been evaluated for their ability to predict mortality in patients with VAP. The models had nearly equal predictive accuracies, although some models are more complex and time consuming.