Espinosa-Gonzalez Ana Belen, Neves Ana Luisa, Fiorentino Francesca, Prociuk Denys, Husain Laiba, Ramtale Sonny Christian, Mi Emma, Mi Ella, Macartney Jack, Anand Sneha N, Sherlock Julian, Saravanakumar Kavitha, Mayer Erik, de Lusignan Simon, Greenhalgh Trisha, Delaney Brendan C
Department of Surgery and Cancer, Imperial College London, London, United Kingdom.
Patient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, United Kingdom.
JMIR Res Protoc. 2021 May 25;10(5):e29072. doi: 10.2196/29072.
During the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection.
The objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes.
The study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use of an electronic template that incorporates a list of items (known as RECAP-V0) thought to be associated with disease outcome according to previous qualitative work. Data collected will be linked to patient outcomes in highly secure environments. We will then use multivariate logistic regression analyses for model development and validation.
Recruitment of participants started in October 2020. Initially, only the NWL CCGs and RCGP RSC arms were active. As of March 24, 2021, we have recruited a combined sample of 3827 participants in these two arms. CCAS and Doctaly joined the study in February 2021, with CCAS starting the recruitment process on March 15, 2021. The first part of the analysis (RECAP-V1 model development) is planned to start in April 2021 using the first half of the NWL CCGs and RCGP RSC combined data set. Posteriorly, the model will be validated with the rest of the NWL CCGs and RCGP RSC data as well as the CCAS and Doctaly data sets. The study was approved by the Research Ethics Committee on May 27, 2020 (Integrated Research Application System number: 283024, Research Ethics Committee reference number: 20/NW/0266) and badged as National Institute of Health Research Urgent Public Health Study on October 14, 2020.
We believe the validated RECAP-V1 early warning score will be a valuable tool for the assessment of severity in patients with suspected COVID-19 in the community, either in face-to-face or remote consultations, and will facilitate the timely escalation of treatment with the potential to improve patient outcomes.
ISRCTN registry ISRCTN13953727; https://www.isrctn.com/ISRCTN13953727.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29072.
在疫情期间，远程会诊已成为评估有新冠病毒病症状和体征患者的常态，以降低传播风险。这加剧了基层医疗临床医生在评估疑似新冠病毒病患者时已经面临的临床不确定性，并促使使用风险预测评分，如国家早期预警评分（NEWS2），来评估病情严重程度并指导治疗。然而，现有的风险预测工具尚未在社区环境中得到验证，也并非为捕捉新冠病毒感染的特性而设计。
本研究的目的是生成一个多变量风险预测工具，即RECAP-V1（基层医疗中的远程新冠病毒病评估），以支持基层医疗临床医生识别那些病情恶化风险较高的新冠病毒病患者，并促进其治疗的早期升级，旨在改善患者预后。
本研究采用前瞻性队列观察设计，对在基层医疗中出现提示新冠病毒病症状和体征的患者进行随访，并将其数据与医院结局（住院和死亡）相关联。数据收集将由四个部门的基层医疗临床医生进行：伦敦西北部临床委托小组（NWL CCGs）、牛津 - 皇家全科医师学院（RCGP）研究与监测中心（RSC）、新冠临床评估服务（CCAS）以及伦敦东南部CCGs（Doctaly平台）。该研究使用一个电子模板，其中包含根据先前定性研究认为与疾病结局相关的一系列条目（称为RECAP-V0）。收集到的数据将在高度安全的环境中与患者结局相关联。然后，我们将使用多变量逻辑回归分析进行模型开发和验证。
参与者招募于2020年10月开始。最初，只有NWL CCGs和RCGP RSC部门处于活动状态。截至2021年3月24日，我们在这两个部门共招募了3827名参与者的合并样本。CCAS和Doctaly于2021年2月加入该研究，CCAS于2021年3月15日开始招募过程。分析的第一部分（RECAP-V1模型开发）计划于2021年4月开始，使用NWL CCGs和RCGP RSC合并数据集的前半部分。随后，该模型将用NWL CCGs和RCGP RSC的其余数据以及CCAS和Doctaly数据集进行验证。该研究于2020年5月27日获得研究伦理委员会批准（综合研究申请系统编号：283024，研究伦理委员会参考编号：20/NW/0266），并于2020年10月14日被标记为国家卫生研究院紧急公共卫生研究。
我们相信，经过验证的RECAP-V1早期预警评分将成为在社区中评估疑似新冠病毒病患者病情严重程度的宝贵工具，无论是在面对面还是远程会诊中，并将促进治疗的及时升级，有可能改善患者预后。
ISRCTN注册库ISRCTN13953727；https://www.isrctn.com/ISRCTN13953727。
国际注册报告标识符（IRRID）：DERR1-10.2196/29072。
