Mureddu Gian Francesco
Italian Association of Cardiovascular Prevention and Rehabilitation.
Monaldi Arch Chest Dis. 2017 Jul 18;87(2):848. doi: 10.4081/monaldi.2017.848.
Several indexes to predict perioperative cardiovascular risk have been proposed overtime. The most widely used is the Revised Cardiac Risk Index (RCRI) developed by Lee since 1999. It predicts major cardiac outcomes from five independent clinical determinants: history of ischemic heart disease, history of cardiovascular disease, heart failure, insulin-dependent diabetes mellitus, and chronic renal failure (i.e. serum creatinine >2 mg/dl). In external validation studies, the RCRI showed high negative predictive value in all groups of age, indicating that it may be used to identify people at low risk for perioperative adverse cardiovascular events in noncardiac surgery. However its accuracy is suboptimal in many clinical settings. More recently the National Surgical Quality Improvement Program database) (NSQIP) hasdeveloped a new index to predict perioperative myocardial infarction (MI) or cardiac arrest (MICA) from a cohort of 211,410 patients (the Gupta index) and afterwards a universal surgical risk estimation tool has been developed, using standardized clinical data from 393 ACSNSQIP hospitals in US (a cohort based on 1,414,006 patients), showing a good performance for mortality (C-statistic = 0.944) and morbidity (C-statistic =0.816) as compared with procedure-specific models. Other risk scores include the Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION), which has evaluated cardiac complications in 15,065 patients, the Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) and the large Preoperative Score to Predict Postoperative Mortality (POSPOM) that was built up from data collected in the National Hospital Discharge Data Base (NHDBB) including a cohort of 7.059.447 patients. In Italy a new risk index (the Orion score) builkt up from a cohort of 9000 patients generated four classes of major cardiovascular adverse events perioperative risk ranging from 1 (0.6%); 2 (2.4%); 3 (7.4%) and 4 (23.1%). The AUROC curves showed higher accuracy as compared to the RCRI score both in the derivation than in the validation cohort (AUROC= 0.872 ± 0.028 vs 0.807 ± 0.037). Thus, many risk indices are available nowadays. Despite the latest European guidelines recommended them for risk stratification (class I, level of evidence B), their use in clinical practice is still scarce.
长期以来，人们提出了多种预测围手术期心血管风险的指标。使用最广泛的是Lee于1999年制定的修订心脏风险指数（RCRI）。它通过五个独立的临床决定因素预测主要心脏结局：缺血性心脏病史、心血管疾病史、心力衰竭、胰岛素依赖型糖尿病和慢性肾衰竭（即血清肌酐>2mg/dl）。在外部验证研究中，RCRI在所有年龄组中均显示出较高的阴性预测价值，这表明它可用于识别非心脏手术中围手术期发生不良心血管事件风险较低的人群。然而，在许多临床环境中，其准确性并不理想。最近，国家外科质量改进计划数据库（NSQIP）根据211410例患者的数据制定了一项新的指标，用于预测围手术期心肌梗死（MI）或心脏骤停（MICA）（古普塔指数），随后开发了一种通用的手术风险评估工具，该工具使用了美国393家美国外科医师学会国家外科质量改进计划（ACSNSQIP）医院的标准化临床数据（基于1414006例患者的队列），与特定手术模型相比，该工具在预测死亡率（C统计量=0.944）和发病率（C统计量=0.816）方面表现良好。其他风险评分包括非心脏手术患者血管事件队列评估（VISION），该评估对15065例患者的心脏并发症进行了评估；生理和手术严重程度评分系统（POSSUM）以及根据国家医院出院数据库（NHDBB）收集的数据建立的大型术前预测术后死亡率评分系统（POSPOM），NHDBB的数据来自7059447例患者的队列。在意大利，根据9000例患者的队列建立了一种新的风险指数（猎户座评分），该指数将围手术期主要心血管不良事件风险分为四类，范围从1（0.6%）；2（2.4%）；3（7.4%）到4（23.1%）。受试者工作特征曲线（AUROC曲线）显示，与RCRI评分相比，该指数在推导队列和验证队列中的准确性更高（AUROC=0.872±0.028 vs 0.807±0.037）。因此，如今有许多风险指数可供使用。尽管最新的欧洲指南推荐将它们用于风险分层（I类，证据等级B），但它们在临床实践中的应用仍然很少。
