Division of Pulmonary and Critical Care Medicine and the Mindful Breathing Laboratory, Department of Internal Medicine, Mayo Clinic, Rochester, MN.
Division of Pulmonary and Critical Care Medicine and the Mindful Breathing Laboratory, Department of Internal Medicine, Mayo Clinic, Rochester, MN.
Mayo Clin Proc. 2014 May;89(5):638-43. doi: 10.1016/j.mayocp.2013.12.004. Epub 2014 Mar 19.
The objective of this study was to develop a model to aid clinicians in better predicting 1-year mortality rate for patients with an acute exacerbation of chronic obstructive pulmonary disease admitted to the medical intensive care unit (ICU) with the goal of earlier initiation of palliative care and end-of-life communications in this patient population. This retrospective cohort study included patients from a medical ICU from April 1, 1995, to November 30, 2009. Data collected from the Acute Physiology and Chronic Health Evaluation III database included demographic characteristics; severity of illness scores; noninvasive and invasive mechanical ventilation time; ICU and hospital length of stay; and ICU, hospital, and 1-year mortality. Statistically significant univariate variables for 1-year mortality were entered into a multivariate model, and the independent variables were used to generate a scoring system to predict 1-year mortality rate. At 1-year follow-up, 295 of 591 patients died (50%). Age and hospital length of stay were identified as independent determinants of mortality at 1 year by using multivariate analysis, and the predictive model developed had an area under the operating curve of 0.68. Bootstrap analysis with 1000 iterations validated the model, age, and hospital length of stay, entered the model 100% of the time (area under the operating curve=0.687; 95% CI, 0.686-0.688). A simple model using age and hospital length of stay may be informative for providers willing to identify patients with chronic obstructive pulmonary disease with high 1-year mortality rate who may benefit from end-of-life communications and from palliative care.
本研究旨在开发一种模型,以帮助临床医生更好地预测慢性阻塞性肺疾病急性加重患者在入住医疗重症监护病房(ICU)后的 1 年死亡率,以便在该患者群体中更早地启动姑息治疗和临终沟通。这是一项回顾性队列研究,纳入了 1995 年 4 月 1 日至 2009 年 11 月 30 日期间 ICU 的患者。从急性生理学和慢性健康评估 III 数据库中收集的数据包括人口统计学特征;疾病严重程度评分;无创和有创机械通气时间;ICU 和住院时间;以及 ICU、医院和 1 年死亡率。对 1 年死亡率有统计学意义的单变量变量被纳入多变量模型,然后使用这些独立变量生成一个评分系统来预测 1 年死亡率。在 1 年随访时,591 名患者中有 295 名(50%)死亡。多变量分析确定年龄和住院时间是 1 年死亡的独立决定因素,所开发的预测模型的工作曲线下面积为 0.68。经过 1000 次迭代的自举分析验证了该模型、年龄和住院时间,模型 100%时间都包含这些因素(工作曲线下面积=0.687;95%置信区间,0.686-0.688)。一个简单的模型,使用年龄和住院时间,可能为愿意识别具有高 1 年死亡率的慢性阻塞性肺疾病患者的提供者提供信息,这些患者可能受益于临终沟通和姑息治疗。