TY - JOUR
T1 - Risk prediction models for mortality in patients with ventilator-associated pneumonia
T2 - A systematic review and meta-analysis
AU - Larsson, Johan E
AU - Itenov, Theis Skovsgaard
AU - Bestle, Morten Heiberg
N1 - Copyright © 2016 Elsevier Inc. All rights reserved.
PY - 2017/2/1
Y1 - 2017/2/1
N2 - PURPOSE: 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.METHODS: The 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).RESULTS: We 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).CONCLUSION: We 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.
AB - PURPOSE: 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.METHODS: The 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).RESULTS: We 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).CONCLUSION: We 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.
KW - Review
KW - Journal Article
U2 - 10.1016/j.jcrc.2016.09.003
DO - 10.1016/j.jcrc.2016.09.003
M3 - Review
C2 - 27676171
SN - 0883-9441
VL - 37
SP - 112
EP - 118
JO - Journal of Critical Care
JF - Journal of Critical Care
ER -