Zimmerman J E, Wagner D P, Draper E A, Knaus W A
Department of Anesthesiology, George Washington University Medical Center.
Crit Care Med. 1994 Sep;22(9):1373-84.
To develop predictive equations, estimating the probability that an individual intensive care unit (ICU) patient will receive life support within the next 24 hrs.
Prospective, multicenter, inception cohort study.
Forty-two ICUs in 40 U.S. hospitals, including 26 that were randomly selected and 14 volunteer hospitals, primarily university or large tertiary care centers.
A consecutive sample of 17,440 ICU admissions.
None.
A series of multivariate equations were developed to create daily estimates of probability of life support in the next 24 hrs. These equations used demographic, physiologic, and treatment information obtained at the time of ICU admission and during the first 7 ICU days. The most important determinants of next day risk for life support were the current day's therapy and Acute Physiology Score of the Acute Physiology and Chronic Health Evaluation (APACHE) III score. Other predictor variables included diagnosis, age, chronic health status, emergency surgery, previous day Acute Physiology Score, and hospital stay and location before ICU admission. The cross-validated ICU day 1, 2, and 3 predictive equations had receiver operating characteristic areas of 0.90. Survival, ICU readmission rate, and the number and type of therapies received by patients predicted at < 10% risk for active treatment suggest that discharge of patients meeting these criteria to an intermediate care unit or hospital ward could reduce ICU bed demand without compromising patient safety.
Accurate, objective predictions of next day risk for life support can be developed, using readily available patient information. Supplementing physician judgment with these objective risk assessments deserves evaluation for the role of these assessments in enhancing patient safety and improving ICU resource utilization.
开发预测方程，以估计个体重症监护病房（ICU）患者在未来24小时内接受生命支持的概率。
前瞻性、多中心、起始队列研究。
美国40家医院的42个ICU，其中包括随机选择的26个和14个志愿医院，主要是大学或大型三级护理中心。
连续抽取17440例ICU入院患者样本。
无。
开发了一系列多变量方程，以创建对未来24小时生命支持概率的每日估计。这些方程使用了ICU入院时及ICU最初7天内获得的人口统计学、生理学和治疗信息。次日生命支持风险的最重要决定因素是当日治疗及急性生理学与慢性健康状况评估（APACHE）III评分中的急性生理学评分。其他预测变量包括诊断、年龄、慢性健康状况、急诊手术、前一日急性生理学评分以及ICU入院前的住院时间和地点。经交叉验证的第1、2和3天ICU预测方程的受试者工作特征曲线下面积为0.90。对于预测为积极治疗风险<10%的患者，其生存率、ICU再入院率以及接受的治疗数量和类型表明，将符合这些标准的患者转至中级护理单元或医院病房可减少ICU床位需求，而不会危及患者安全。
利用易于获取的患者信息，可对次日生命支持风险进行准确、客观的预测。用这些客观风险评估补充医生的判断，值得评估其在提高患者安全和改善ICU资源利用方面的作用。
