医学
机械通风
优势比
入射(几何)
呼吸衰竭
潮气量
外科
麻醉
内科学
呼吸系统
光学
物理
作者
Dharshi Karalapillai,Laurence Weinberg,Serpa Neto A,Philip J. Peyton,Louise Ellard,Raymond Hu,Brett Pearce,Chong Oon Tan,David Story,Mark O’Donnell,Patrick Hamilton,Chad Oughton,Jonathan Galtieri,Anthony J. Wilson,Glenn M. Eastwood,Rinaldo Bellomo,Daryl Jones
标识
DOI:10.1097/eja.0000000000001601
摘要
Studies in critically ill patients suggest a relationship between mechanical power (an index of the energy delivered by the ventilator, which includes driving pressure, respiratory rate, tidal volume and inspiratory pressure) and complications.We aimed to assess the association between intra-operative mechanical power and postoperative pulmonary complications (PPCs).Post hoc analysis of a large randomised clinical trial.University-affiliated academic tertiary hospital in Melbourne, Australia, from February 2015 to February 2019.Adult patients undergoing major noncardiothoracic, nonintracranial surgery.Dynamic mechanical power was calculated using the power equation adjusted by the respiratory system compliance (CRS). Multivariable models were used to assess the independent association between mechanical power and outcomes.The primary outcome was the incidence of PPCs within the first seven postoperative days. The secondary outcome was the incidence of acute respiratory failure.We studied 1156 patients (median age [IQR]: 64 [55 to 72] years, 59.5% men). Median mechanical power adjusted by CRS was 0.32 [0.22 to 0.51] (J min-1)/(ml cmH2O-1). A higher mechanical power was also independently associated with increased risk of PPCs [odds ratio (OR 1.34, 95% CI, 1.17 to 1.52); P < 0.001) and acute respiratory failure (OR 1.40, 95% CI, 1.21 to 1.61; P < 0.001).In patients receiving ventilation during major noncardiothoracic, nonintracranial surgery, exposure to a higher mechanical power was independently associated with an increased risk of PPCs and acute respiratory failure.Australia and New Zealand Clinical Trials Registry no: 12614000790640.
科研通智能强力驱动
Strongly Powered by AbleSci AI