Introduction:

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. Mortality rates are high, exceeding 50% in patients with septic shock. The sepsis severity score (SSS) was developed to determine the severity of sepsis and as a prognostic model. The aim of this study was to externally validate the SSS model.

Methods:

Calibration and discrimination of the SSS were retrospectively evaluated using data from a single-center sepsis registry.

Results:

Data from 156 septic patients were recorded; 56% of them had septic shock, 94% of patients required mechanical ventilation. The observed hospital mortality was 60.3%. The mean SSS value was 94.4 (95% CI 90.5–98.3). The SSS presented excellent discrimination with an area under the receiver operating characteristic curve (AUC) of 0.806 (95% CI 0.734–0.866). The pairwise comparison of APACHE II (AUC = 0.789; 95% CI 0.715–0.851) with SSS and 1st day SOFA (AUC = 0.75; 95% CI 0.673–0.817) with SSS revealed no significant differences in discrimination between the models. The calibration of the SSS was good with the Hosmer-Lemeshow goodness-of-fit H test 9.59, P > 0.05. Analyses of calibration curve show absence of accurate predictions in lower deciles of lower risk (2nd and 4th).

Conclusion:

The SSS demonstrated excellent discrimination. The calibration evaluation gave conflicting results; the H-L test result indicated a good calibration, while the visual analysis of the calibration curve suggested the opposite. The SSS requires further evaluation before it can be safely recommended as an outcome prediction model.

中文翻译：

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脓毒症严重程度评分的外部验证。

介绍：

脓毒症被定义为由宿主对感染反应失调引起的危及生命的器官功能障碍。感染性休克患者的死亡率很高，超过 50%。脓毒症严重程度评分（SSS）旨在确定脓毒症的严重程度并作为预后模型。本研究的目的是从外部验证 SSS 模型。

方法：

使用单中心脓毒症登记处的数据对 SSS 的校准和区分进行回顾性评估。

结果：

记录了 156 名脓毒症患者的数据；其中56%出现感染性休克，94%的患者需要机械通气。观察到的医院死亡率为 60.3%。平均 SSS 值为 94.4 (95% CI 90.5–98.3)。SSS 具有出色的辨别力，受试者工作特征曲线下面积 (AUC) 为 0.806 (95% CI 0.734–0.866)。APACHE II（AUC = 0.789；95% CI 0.715-0.851）与 SSS 以及第一天 SOFA（AUC = 0.75；95% CI 0.673-0.817）与 SSS 的配对比较显示，模型之间的区分度没有显着差异。SSS 的校准良好，Hosmer-Lemeshow 拟合优度 H 检验为 9.59，P > 0.05。校准曲线分析显示，缺乏对较低风险的十分位数（第二和第四）的准确预测。

结论：

SSS 表现出了出色的辨别能力。校准评估给出了相互矛盾的结果；HL 测试结果表明校准良好，而校准曲线的目视分析表明结果相反。SSS 需要进一步评估才能被安全地推荐为结果预测模型。