BACKGROUND Risk prediction scores are used to guide clinical decision-making. Our primary objective was to externally validate two patient-specific risk scores for 30-day in-hospital mortality using the Multicenter Perioperative Outcomes Group (MPOG) registry: the Pediatric Risk Assessment (PRAm) score and the intrinsic surgical risk score. The secondary objective was to recalibrate these scores. METHODS Data from 56 US and Dutch hospitals with paediatric caseloads were included. The primary outcome was 30-day mortality. To assess model discrimination, the area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUC-PR) were calculated. Model calibration was assessed by plotting the observed and predicted probabilities. Decision analytic curves were fit. RESULTS The 30-day mortality was 0.14% (822/606 488). The AUROC for the PRAm upon external validation was 0.856 (95% confidence interval 0.844-0.869), and the AUC-PR was 0.008. Upon recalibration, the AUROC was 0.873 (0.861-0.886), and the AUC-PR was 0.031. The AUROC for the external validation of the intrinsic surgical risk score was 0.925 (0.914-0.936) and AUC-PR was 0.085. Upon recalibration, the AUROC was 0.925 (0.915-0.936), and the AUC-PR was 0.094. Calibration metrics for both scores were favourable because of the large cluster of cases with low probabilities of mortality. Decision curve analyses showed limited benefit to using either score. CONCLUSIONS The intrinsic surgical risk score performed better than the PRAm, but both resulted in large numbers of false positives. Both scores exhibited decreased performance compared with the original studies. ASA physical status scores in sicker patients drove the superior performance of the intrinsic surgical risk score, suggesting the use of a risk score does not improve prediction.

中文翻译：

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儿科患者 30 天院内死亡率术前风险评分的国际多机构外部验证。


背景 风险预测评分用于指导临床决策。我们的主要目标是使用多中心围手术期结果组 （MPOG） 登记处对 30 天院内死亡率的两个患者特异性风险评分进行外部验证：儿科风险评估 （PRAm） 评分和内在手术风险评分。次要目标是重新校准这些分数。方法 纳入了来自 56 家美国和荷兰儿科病例医院的数据。主要结局是 30 天死亡率。为了评估模型鉴别力，计算了受试者工作特征曲线下面积 （AUROC） 和精确召回曲线下面积 （AUC-PR）。通过绘制观测和预测概率来评估模型校准。决策分析曲线拟合。结果 30 天死亡率为 0.14% （822/606 488）。外部验证时 PRAm 的 AUROC 为 0.856 （95% 置信区间 0.844-0.869），AUC-PR 为 0.008。重新校准后，AUROC 为 0.873 （0.861-0.886），AUC-PR 为 0.031。用于内在手术风险评分外部验证的 AUROC 为 0.925 （0.914-0.936） 和 AUC-PR 为 0.085。重新校准后，AUROC 为 0.925 （0.915-0.936），AUC-PR 为 0.094。由于死亡概率较低的大量病例，因此两个分数的校准指标都是有利的。决策曲线分析显示使用任一评分的好处有限。结论 内在手术风险评分优于 PRAm，但均导致大量假阳性。与原始研究相比，两项评分均表现出性能下降。 病情较重患者的 ASA 身体状况评分推动了内在手术风险评分的卓越性能，表明使用风险评分并不能改善预测。