Hammond Brandon G, Garcia-Filion Pamela, Kang Paul, Rao Mounica Y, Willis Brigham C, Dalton Heidi J
Division of Critical Care Medicine
University of Arizona College of Medicine, Phoenix, Arizona.
Respir Care. 2017 Oct;62(10):1249-1254. doi: 10.4187/respcare.05092. Epub 2017 Jun 20.
The objective of this work was to examine current oxygenation index (OI) data and outcomes using electronic medical record data to identify a specific OI value associated with mortality.
This study was a retrospective electronic medical record data review from the pediatric ICU of Phoenix Children's Hospital, with data mining for variables to calculate OIs on subjects age 1 month to 20 y mechanically ventilated > 24 h, excluding those with known intracardiac shunts or cyanotic heart disease. Age, length of hospital stay, duration of mechanical ventilation, and outcomes were also assessed. The Wilcoxon signed-rank test was used to compare continuous variables, receiver operating characteristic analysis was used in determining discriminant ability, and logistic regression was conducted to determine the odds ratio (OR) for risk of death with increasing OI.
OI was calculated on 65 subjects, of whom 6 died (9%). The median maximum OI was 10 for all subjects, 17 for non-survivors, and 8 for survivors ( = .14 via Wilcoxon rank-sum test). ORs indicated a 2.4-fold increase in the odds of death ( = .09, 95% CI 0.9-6.6) for each increasing point in maximum OI. Mean OI OR revealed a 1.9-fold increase in the odds of death ( = .25, 95% CI 0.6-5.9). Receiver operating characteristic analysis indicated a higher discriminate ability for maximum OI (area under the curve = 0.68) than mean OI (area under the curve = 0.58). OI cut-points for mortality were established. Mortality was unchanged until maximum OI > 17, for which mortality nearly tripled at a value of 18% versus 6-7% for range 0-17.
Limitations exist in obtaining serial OI values from current electronic medical records. Serial assessment of OI values may allow creation of alert values for increased mortality risk. Consideration of escalation of therapies for respiratory failure, such as high-frequency ventilation, inhaled nitric oxide, or extracorporeal membrane oxygenation may be warranted at lower OIs than historically reported.
本研究旨在利用电子病历数据检查当前的氧合指数(OI)数据及结果,以确定与死亡率相关的特定OI值。
本研究是对凤凰城儿童医院儿科重症监护病房的电子病历数据进行回顾性分析,通过数据挖掘获取变量,计算年龄在1个月至20岁、机械通气时间>24小时的受试者的OI,排除已知有心内分流或紫绀型心脏病的患者。同时评估年龄、住院时间、机械通气时间及结果。采用Wilcoxon符号秩检验比较连续变量,通过受试者工作特征分析确定判别能力,并进行逻辑回归以确定随着OI增加死亡风险的比值比(OR)。
对65名受试者计算了OI,其中6人死亡(9%)。所有受试者的最大OI中位数为10,非幸存者为17,幸存者为8(通过Wilcoxon秩和检验,P = 0.14)。OR表明,最大OI每增加1个点,死亡几率增加2.4倍(P = 0.09,95%CI 0.9 - 6.6)。平均OI的OR显示死亡几率增加1.9倍(P = 0.25,95%CI 0.6 - 5.9)。受试者工作特征分析表明,最大OI的判别能力更高(曲线下面积 = 0.68),高于平均OI(曲线下面积 = 0.58)。确定了死亡率的OI切点。在最大OI>17之前死亡率不变,当最大OI为18%时死亡率几乎增加两倍,而在0 - 17范围内为6 - 7%。
从当前电子病历中获取连续OI值存在局限性。对OI值进行连续评估可能有助于创建死亡率风险增加的警报值。对于呼吸衰竭治疗方案的升级,如高频通气、吸入一氧化氮或体外膜肺氧合,可能需要在比以往报道更低的OI时就予以考虑。