Value of the Oxygenation Index During One Lung Ventilation For Predicting Respiratory Complications After Thoracic Surgery
Abstract Purpose Thoracic surgery requiring one-lung ventilation (OLV) is associated with significant postoperative pulmonary complications due to patient and surgery specific risk factors. The aim of this study is to determine whether the oxygenation index (OI)[FiO2 * Mean Airway Pressure / PaO2 ]...
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Veröffentlicht in: | Journal of critical care 2016 |
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Sprache: | eng |
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Zusammenfassung: | Abstract Purpose Thoracic surgery requiring one-lung ventilation (OLV) is associated with significant postoperative pulmonary complications due to patient and surgery specific risk factors. The aim of this study is to determine whether the oxygenation index (OI)[FiO2 * Mean Airway Pressure / PaO2 ] during OLV predicts the development of postoperative pulmonary complications (PPC). Materials and Methods The Society of Thoracic Surgeons General Thoracic Surgery Database (STS-GTSD) at the University of Virginia was used to identify all thoracic cases during 2012–2014. All subjects requiring OLV and in whom a blood gas was available for analysis were included. Univariate and multivariate analysis was performed to determine whether the OI predicted the development of PPC. Results A total of 296 subjects had OLV with a calculable OI during the study period. Composite PPC was identified in 97 (33%) of subjects. In the PPC group mortality at thirty days was 7.2% while no deaths were identified in the non-PPC group. In both univariate and multivariate analysis, OI was not predictive of PPC analysis (OR: 1.0 95% CI 0.9–1.1, P = .8). The only predictors of mortality were forced expiratory volume (FEV1) (OR: 0.98 95% CI 0.96–0.99, P = .03) and diffusion capacity of carbon monoxide (DLCO)(OR: 0.98 95% CI 0.96–0.99, P = .03). Conclusion The calculated OI during OLV is not predictive of PPC in our sample. Additional studies in a larger cohort of patients are needed to identify intraoperative ventilation parameters during OLV that can predict the risk of PPC. |
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ISSN: | 0883-9441 |
DOI: | 10.1016/j.jcrc.2016.09.001 |