Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Shatin, Hong Kong, China.
Department of Anaesthesia and Intensive Care, Prince of Wales Hospital, Shatin, Hong Kong, China.
BMC Infect Dis. 2020 Sep 7;20(1):652. doi: 10.1186/s12879-020-05330-x.
Currently there are only two population studies on sepsis incidence in Asia. The burden of sepsis in Hong Kong is unknown. We developed a sepsis surveillance method to estimate sepsis incidence from a population electronic health record (EHR) in Hong Kong using objective clinical data. The study objective was to assess our method's performance in identifying sepsis using a retrospective cohort. We compared its accuracy to administrative sepsis surveillance methods such as Angus' and Martin's methods.
In this single centre retrospective study we applied our sepsis surveillance method on adult patients admitted to a tertiary hospital in Hong Kong. Two clinicians independently reviewed the clinical notes to determine which patients had sepsis. Performance was assessed by sensitivity, specificity, positive predictive value, negative predictive value and area under the curve (AUC) of Angus', Martin's and our surveillance methods using clinical review as "gold standard."
Between January 1 and February 28, 2018, our sepsis surveillance method identified 1352 adult patients hospitalised with suspected infection. We found that 38.9% (95%CI 36.3-41.5) of these patients had sepsis. Using a 490 patient validation cohort, two clinicians had good agreement with weighted kappa of 0.75 (95% CI 0.69-0.81) before coming to consensus on diagnosis of uncomplicated infection or sepsis for all patients. Our method had sensitivity 0.93 (95%CI 0.89-0.96), specificity 0.86 (95%CI 0.82-0.90) and an AUC 0.90 (95%CI 0.87-0.92) when validated against clinician review. In contrast, Angus' and Martin's methods had AUCs 0.56 (95%CI 0.53-0.58) and 0.56 (95%CI 0.52-0.59), respectively.
A sepsis surveillance method based on objective data from a population EHR in Hong Kong was more accurate than administrative methods. It may be used to estimate sepsis population incidence and outcomes in Hong Kong.
This study was retrospectively registered at clinicaltrials.gov on October 3, 2019 ( NCT04114214 ).
目前仅有两项关于亚洲脓毒症发病率的人群研究。香港的脓毒症负担尚不清楚。我们开发了一种脓毒症监测方法，以便使用香港人群电子健康记录（EHR）中的客观临床数据来估计脓毒症的发病率。本研究的目的是使用回顾性队列评估我们的方法识别脓毒症的性能。我们将其准确性与行政性脓毒症监测方法（如 Angus 和 Martin 方法）进行了比较。
在这项单中心回顾性研究中，我们将我们的脓毒症监测方法应用于香港一家三级医院收治的成年患者。两名临床医生独立审查了临床记录，以确定哪些患者患有脓毒症。使用临床审查作为“金标准”，通过敏感性、特异性、阳性预测值、阴性预测值和曲线下面积（AUC）来评估 Angus、Martin 和我们的监测方法的性能。
2018 年 1 月 1 日至 2 月 28 日，我们的脓毒症监测方法识别出 1352 名疑似感染住院的成年患者。我们发现这些患者中有 38.9%（95%CI 36.3-41.5）患有脓毒症。在对所有患者的简单感染或脓毒症诊断达成共识之前，使用 490 名患者的验证队列，两名临床医生具有良好的一致性，加权 Kappa 值为 0.75（95%CI 0.69-0.81）。当与临床医生的审查进行比较时，我们的方法具有 0.93 的敏感性（95%CI 0.89-0.96）、0.86 的特异性（95%CI 0.82-0.90）和 0.90 的 AUC（95%CI 0.87-0.92）。相比之下，Angus 和 Martin 方法的 AUC 分别为 0.56（95%CI 0.53-0.58）和 0.56（95%CI 0.52-0.59）。
基于香港人群 EHR 中的客观数据的脓毒症监测方法比行政方法更准确。它可以用于估计香港的脓毒症人群发病率和结局。
这项研究于 2019 年 10 月 3 日在 clinicaltrials.gov 进行了回顾性注册（NCT04114214）。
