BACKGROUND CONTEXT

Numerous prediction tools are available for estimating postoperative risk following spine surgery. External validation and comparison of these tools is critical prior to clinical use. No model for adverse events after spine surgery has undergone decision curve analysis.

PURPOSE

External validation, comparison, and decision curve analysis of 3 previously described models [SpineSage, Risk Assessment Tool (RAT), National Surgical Quality Improvement Program Risk Calculator (NSQIP)] for predicting 30-day postoperative complications after spine surgery

STUDY DESIGN

Retrospective cohort study.

PATIENT SAMPLE

Three hundred fifteen patients who underwent spine surgery at a tertiary academic surgical center in New Zealand between January 2019 and April 2020.

OUTCOME MEASURES

As defined by each risk prediction tool and objectively using the Comprehensive Complication Index.

METHODS

We retrospectively reviewed risk of postoperative complication was calculated for each patient according to the 3 models. Overall model fit, calibration, discrimination, and decision curve analysis for each model were assessed in line with the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines.

RESULTS

100 (35%) patients experienced complications. SpineSage and RAT were well calibrated, NSQIP systematically underestimated risk. Area under the curve was greatest for SpineSage (0.75) compared with the NSQIP (0.72) and the RAT (0.69). Decision curve analysis showed SpineSage resulted in greatest net benefit across all risk thresholds.

CONCLUSIONS

Of the models studied, SpineSage most accurately predicted risk and can be expected to perform better than a strategy of treating all patients if patient or surgeon deem complication risk >10% significant. NSQIP may not be suitable for the clinical use in our local population.

中文翻译：

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预测脊柱手术并发症：三种模型的外部验证

背景语境

许多预测工具可用于估计脊柱手术后的术后风险。在临床使用之前，对这些工具进行外部验证和比较至关重要。没有经过决策曲线分析的脊柱手术后不良事件模型。

目的

用于预测脊柱手术后 30 天术后并发症的 3 个先前描述的模型 [Spin​​eSage、风险评估工具 (RAT)、国家外科质量改进计划风险计算器 (NSQIP)] 的外部验证、比较和决策曲线分析

学习规划

回顾性队列研究。

患者样本

2019 年 1 月至 2020 年 4 月期间在新西兰一家三级学术外科中心接受脊柱手术的 315 名患者。

结果测量

由每个风险预测工具定义并客观地使用综合并发症指数。

方法

我们回顾性地审查了根据 3 种模型计算每位患者术后并发症的风险。根据个体预后或诊断 (TRIPOD) 指南的多变量预测模型的透明报告，对每个模型的整体模型拟合、校准、辨别和决策曲线分析进行了评估。

结果

100 名 (35%) 患者出现并发症。SpineSage 和 RAT 校准良好，NSQIP 系统地低估了风险。与 NSQIP (0.72) 和 RAT (0.69) 相比，SpineSage (0.75) 的曲线下面积最大。决策曲线分析显示 SpineSage 在所有风险阈值中产生了最大的净收益。

结论

在所研究的模型中，SpineSage 最准确地预测了风险，如果患者或外科医生认为并发症风险 >10% 显着，预计其表现优于治疗所有患者的策略。NSQIP 可能不适合我们当地人群的临床使用。