Yepes-Temiño Maria J, Monedero Pablo, Pérez-Valdivieso José Ramón
From the Department of Anaesthesia and Intensive Care Medicine, University of Navarra; Clínica Universidad de Navarra (MJ-YT, PM); and Complejo Hospitalario de Navarra, Irunlarrea, Pamplona, Spain (JR-PV).
Eur J Anaesthesiol. 2016 May;33(5):326-33. doi: 10.1097/EJA.0000000000000354.
Patients undergoing lung surgery are at risk of postoperative pulmonary complications (PPCs). Identifying those patients is important to optimise individual perioperative management. The Clinical Prediction Rule for Pulmonary Complications (CPRPCs) after thoracic surgery, developed by the Memorial Sloan-Kettering Cancer Center, might be an ideal predictor. The hypothesis was that CPRPC performs well for the prediction of PPCs.
The aim of our study was to provide the external validation of the CPRPC after lung resection for primary tumours, before universal acceptance. In case of poor discrimination, we planned, as a second objective, to derive a new predictive index for PPCs.
Retrospective, observational multicentre study.
A total of 559 adult consecutive patients who underwent pulmonary resection. Inclusion criteria were adult patients (aged over 17 years).
Thirteen Spanish hospitals during the first half of 2011.
A record of the PPCs defined, as in the original publication, as the presence of any of the following events: atelectasis; pneumonia; pulmonary embolism; respiratory failure; and need for supplemental oxygen at hospital discharge.
The performance of the CPRPC was determined in order to examine its ability to discriminate and calibrate the presence of PPCs.
The study included 559 patients, of whom 75 (11.6%) suffered PPCs. The CPRPC did not show enough discriminatory power for our cohort area under the receiver operating characteristic (ROC) curve 0.47 (95% confidence interval 0.37 to 0.57)]. After a fitting step by stepwise multivariate logistic regression, we identified three main predictors of PPCs: age; smoking status; and predicted postoperative forced expiratory volume in 1 s. Combining them into a simple risk score, we were able to obtain an area under the ROC curve of 0.74 (95% confidence interval 0.68 to 0.79).
In this external validation, the CPRPC performed poorly despite its simplicity. The CPRPC was not a useful scale in our cohort. In contrast, we used a more accurate score to predict the occurrence of PPCs in our cohort. It is based on age, smoking status and predicted postoperative forced expiratory volume in 1 s. We propose that our formula should be externally validated.
接受肺部手术的患者有发生术后肺部并发症（PPCs）的风险。识别这些患者对于优化个体围手术期管理很重要。纪念斯隆凯特琳癌症中心制定的胸外科手术后肺部并发症临床预测规则（CPRPCs）可能是一个理想的预测指标。假设是CPRPC在预测PPCs方面表现良好。
我们研究的目的是在CPRPC被广泛接受之前，对其在原发性肿瘤肺切除术后预测PPCs的能力进行外部验证。如果区分能力差，作为第二个目标，我们计划推导一个新的PPCs预测指数。
回顾性观察性多中心研究。
共有559例连续接受肺切除术的成年患者。纳入标准为成年患者（年龄超过17岁）。
2011年上半年的13家西班牙医院。
按照原始出版物的定义，记录PPCs，即出现以下任何一种情况：肺不张；肺炎；肺栓塞；呼吸衰竭；出院时需要补充氧气。
确定CPRPC的性能，以检验其区分和校准PPCs存在的能力。
该研究纳入559例患者，其中75例（11.6%）发生PPCs。CPRPC对我们队列的区分能力不足（受试者操作特征曲线下面积为0.47，95%置信区间为0.37至0.57）。经过逐步多因素逻辑回归的拟合步骤，我们确定了PPCs的三个主要预测因素：年龄；吸烟状况；预计术后1秒用力呼气量。将它们组合成一个简单的风险评分，我们能够获得受试者操作特征曲线下面积为0.74（95%置信区间为0.68至0.79）。
在这项外部验证中，尽管CPRPC简单，但表现不佳。在我们的队列中，CPRPC不是一个有用的量表。相比之下，我们使用了一个更准确的评分来预测我们队列中PPCs的发生。它基于年龄、吸烟状况和预计术后1秒用力呼气量。我们建议对我们的公式进行外部验证。
