Diagnosing and predicting risk in children with SARS-CoV-2- related illness

在COVID-19大流行之后，儿童多系统炎症综合征（MIS-C） 对接触SARS-CoV-2的儿童来说是一种新的威胁。目前没有诊断 也没有工具来预测疾病的进展。通过 在美国建立，资助，多中心联盟（CHARMS：MIS-C和 它与川崎病的关系由PCARI资助）和英国（钻石），我们有 收集临床数据和样本，以支持诊断和 MIS-C的预后测试。在本项目的第1阶段（R61 HD 105590，1-2年），我们使用了这些 设计基于机器学习的临床决策支持工具（KIDMATCH）， 临床医生在诊断MIS-C和其他原因引起的儿童发热。该提案的重点是 软件即医疗器械（SaMD）的开发和该SaMD的临床部署 在临床环境中。此外，我们的目标是建立质量管理体系（QMS）， 根据FDA要求，最大限度地减少和管理与患者安全相关的意外结局 监管批准。为此，本提案旨在进一步开发跨平台SMART- on-FHIR应用程序，用于显示KIDMATCH输出，以便集成到电子健康记录中。 在我们的临床和数据科学团队的密切合作下，我们将评估 KIDMATCH应用程序设置，用户工作流程和医生偏好通过结构化访谈， 模拟和直接反馈。最后，我们的目标是完成一个正在进行的申请， 紧急使用授权（EUA），以实现更广泛的部署和商业化 KIDMATCH SaMD.本提案中调查小组的协同专长提供了 为患有SARS谱系的儿童创造诊断工具的独特机会- CoV-2疾病 1

In the wake of COVID-19 pandemic, Multisystem Inflammatory Syndrome in Children (MIS-C) has evolved as a new threat to children exposed to SARS-CoV-2. Currently there are no diagnostic tests to readily identify these patients nor are there tools to predict disease progression. Through established, funded, multi-center consortia in the U.S. (CHARMS: Characterization of MIS-C and its Relationship to Kawasaki Disease funded by PCORI) and the UK (DIAMONDS), we have collected clinical data and samples to support development and testing of diagnostic and prognostic tests for MIS-C. In phase 1 of this project (R61HD105590, years 1-2), we used these data to devise machine learning-based clinical decision support tool (KIDMATCH) to assist clinicians in diagnosis of MIS-C and other causes of fever in children. This proposal focuses on the development of a Software as a Medical Device (SaMD) and clinical deployment of this SaMD in a clinical setting. Additionally, we aim to develop a quality management system (QMS) to minimize and manage unintentional outcomes related to patient safety as required for FDA regulatory approval. To this end, this proposal aims to further develop a cross-platform SMART- on-FHIR app for display of the KIDMATCH outputs for integration within electronic health records. In close collaboration between our clinical and data science teams, we will evaluate the KIDMATCH app set-up, user workflow and physician preferences through structured interviews, simulations, and direct feedback. Finally, we aim to complete an ongoing application for Emergency Use Authorization (EUA) to enable wider deployment and commercialization of the KIDMATCH SaMD. The synergistic expertise of the investigative team in this proposal provides a unique opportunity to create diagnostic tools for children suffering from the spectrum of SARS- CoV-2 illnesses. 1