Mayo Clinic, Rochester, MN 55905, USA.
Am J Respir Crit Care Med. 2011 Feb 15;183(4):462-70. doi: 10.1164/rccm.201004-0549OC. Epub 2010 Aug 27.
Accurate, early identification of patients at risk for developing acute lung injury (ALI) provides the opportunity to test and implement secondary prevention strategies.
To determine the frequency and outcome of ALI development in patients at risk and validate a lung injury prediction score (LIPS).
In this prospective multicenter observational cohort study, predisposing conditions and risk modifiers predictive of ALI development were identified from routine clinical data available during initial evaluation. The discrimination of the model was assessed with area under receiver operating curve (AUC). The risk of death from ALI was determined after adjustment for severity of illness and predisposing conditions.
Twenty-two hospitals enrolled 5,584 patients at risk. ALI developed a median of 2 (interquartile range 1-4) days after initial evaluation in 377 (6.8%; 148 ALI-only, 229 adult respiratory distress syndrome) patients. The frequency of ALI varied according to predisposing conditions (from 3% in pancreatitis to 26% after smoke inhalation). LIPS discriminated patients who developed ALI from those who did not with an AUC of 0.80 (95% confidence interval, 0.78-0.82). When adjusted for severity of illness and predisposing conditions, development of ALI increased the risk of in-hospital death (odds ratio, 4.1; 95% confidence interval, 2.9-5.7).
ALI occurrence varies according to predisposing conditions and carries an independently poor prognosis. Using routinely available clinical data, LIPS identifies patients at high risk for ALI early in the course of their illness. This model will alert clinicians about the risk of ALI and facilitate testing and implementation of ALI prevention strategies. Clinical trial registered with www.clinicaltrials.gov (NCT00889772).
准确、早期识别发生急性肺损伤(ALI)风险的患者,为测试和实施二级预防策略提供了机会。
确定有风险的患者中 ALI 发展的频率和结局,并验证肺损伤预测评分(LIPS)。
在这项前瞻性多中心观察性队列研究中,从初始评估期间可获得的常规临床数据中确定了预测 ALI 发展的诱发因素和风险修饰因素。采用受试者工作特征曲线下面积(AUC)评估模型的区分度。在调整疾病严重程度和诱发因素后,确定 ALI 死亡风险。
22 家医院共纳入了 5584 例有风险的患者。ALI 中位数在初始评估后 2 天(四分位距 1-4 天)发展,共有 377 例(6.8%;148 例 ALI 仅有,229 例成人呼吸窘迫综合征)患者发生 ALI。ALI 的发生率根据诱发因素而不同(从胰腺炎的 3%到吸入烟雾后的 26%)。LIPS 鉴别出发生和未发生 ALI 的患者,AUC 为 0.80(95%置信区间,0.78-0.82)。在调整疾病严重程度和诱发因素后,ALI 的发生增加了院内死亡的风险(比值比,4.1;95%置信区间,2.9-5.7)。
ALI 的发生根据诱发因素而不同,且具有独立的不良预后。使用常规临床数据,LIPS 可以在疾病早期识别出发生 ALI 的高危患者。该模型将提醒临床医生 ALI 的风险,并有助于测试和实施 ALI 预防策略。临床试验注册于 www.clinicaltrials.gov(NCT00889772)。