Sepsis surveillance: an examination of parameter sensitivity and alert reliability

Objective: To examine performance of a sepsis surveillance system in a simulated environment where modifications to parameters and settings for identification of at-risk patients can be explored in-depth.

Materials and Methods: This was a multiple center observational cohort study. The study population comprised 14 917 adults hospitalized in 2016. An expert-driven rules algorithm was applied against 15.1 million data points to simulate a system with binary notification of sepsis events. Three system scenarios were examined: a scenario as derived from the second version of the Consensus Definitions for Sepsis and Septic Shock (SEP-2), the same scenario but without systolic blood pressure (SBP) decrease criteria (near SEP-2), and a conservative scenario with limited parameters. Patients identified by scenarios as being at-risk for sepsis were assessed for suspected infection. Multivariate binary logistic regression models estimated mortality risk among patients with suspected infection.

Results: First, the SEP-2-based scenario had a hyperactive, unreliable parameter SBP decrease >40 mm Hg from baseline. Second, the near SEP-2 scenario demonstrated adequate reliability and sensitivity. Third, the conservative scenario had modestly higher reliability, but sensitivity degraded quickly. Parameters differed in predicting mortality risk and represented a substitution effect between scenarios.

Discussion: Configuration of parameters and alert criteria have implications for patient identification and predicted outcomes.

Conclusion: Performance of scenarios was associated with scenario design. A single hyperactive, unreliable parameter may negatively influence adoption of the system. A trade-off between modest improvements in alert reliability corresponded to a steep decline in condition sensitivity in scenarios explored.

研究目标：在模拟环境中检验脓毒症监测系统（sepsis surveillance system）的性能，该环境可深入探索针对高危患者识别的参数与设置调整方案。

材料与方法：本研究为多中心观察性队列研究。研究人群由2016年住院的14917名成年患者组成。采用专家驱动的规则算法，对1510万个数据点进行处理，以模拟可输出脓毒症事件二元分类通知的系统。共考察三种系统场景：其一为基于《脓毒症与脓毒性休克共识定义第二版》（SEP-2）的标准场景；其二为移除收缩压（systolic blood pressure, SBP）降低判定标准的近似SEP-2场景；其三为参数受限的保守场景。对各场景识别出的脓毒症高危患者，开展疑似感染评估。采用多变量二元逻辑回归模型（multivariate binary logistic regression models），估算疑似感染患者的死亡风险。

研究结果：第一，基于SEP-2的标准场景存在一项过度活跃且可靠性不足的参数——收缩压较基线降低＞40mmHg。第二，近似SEP-2场景展现出良好的可靠性与敏感度。第三，保守场景的可靠性略高，但敏感度下降迅速。不同参数在死亡风险预测方面存在差异，且各场景间存在参数替代效应。

讨论：参数与预警判定标准的配置，会对患者识别及预测结局产生影响。

结论：各场景的性能与其设计方案密切相关。单一过度活跃且可靠性不足的参数，可能对系统的临床应用产生负面影响。本研究考察的场景中，预警可靠性的小幅提升，往往伴随疾病识别敏感度的大幅下降，二者存在权衡关系。