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Risk factors for ventilator-associated pneumonia in the neonatal intensive care unit: a meta-analysis of observational studies
Bin Tan, Fan Zhang, Xian Zhang, Ya-Ling Huang, Yu-Shuang Gao, Xiao Liu, Ying-Li Li & Jing-Fu Qiu
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Critical Care Physicians
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Pre-Use of PICS Designation
Ventilator-associated pneumonia (VAP) is a common and serious problem among mechanically ventilated patients in intensive care units (ICU), especially for the newborn. However, limited literatures have been reviewed to synthesize the finding of previous papers to investigate the risk factors for VAP although it has been a serious complication of mechanical ventilation (MV) with a high morbidity and mortality in the newborn. We performed this meta-analysis to extend previous knowledge for developing VAP prevention strategies by identifying the potential risk factors related to VAP in the neonatal intensive care unit (NICU). The relevant literatures published up to July 2013 were searched in the databases of PubMed, Cochrane Central Register of Controlled Trials, Embase, and Web of Science. Three reviewers screened those literatures and extracted data according to the inclusion and exclusion criteria independently. A total of eight studies including 370 cases and 1,071 controls were identified. Ten risk factors were found to be related to neonatal VAP which were listed as follows in order by odds ratios (ORs): length of stay in NICU (OR 23.45), reintubation (OR 9.18), enteral feeding (OR 5.59), mechanical ventilation (OR 4.04), transfusion (OR 3.32), low birth weight (OR 3.16), premature infants (OR 2.66), parenteral nutrition (OR 2.30), bronchopulmonary dysplasia (OR 2.21), and tracheal intubation (OR 1.12). Conclusion: We identified ten variables as independent risk factors for the development of VAP: length of stay in NICU, reintubation, enteral feeding, mechanical ventilation, transfusion, low birth weight, premature infants, parenteral nutrition, bronchopulmonary dysplasia, and tracheal intubation. Due to several limitations in the present study, further large and well-designed studies are needed to confirm the conclusion.
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