UCL Great Ormond Street Institute of Child Health, London, UK.
Paediatric Infectious Diseases Research Group, St. George's University of London, London, UK.
BMC Med. 2022 Nov 30;20(1):465. doi: 10.1186/s12916-022-02664-y.
To update and internally validate a model to predict children and young people (CYP) most likely to experience long COVID (i.e. at least one impairing symptom) 3 months after SARS-CoV-2 PCR testing and to determine whether the impact of predictors differed by SARS-CoV-2 status.
Data from a nationally matched cohort of SARS-CoV-2 test-positive and test-negative CYP aged 11-17 years was used. The main outcome measure, long COVID, was defined as one or more impairing symptoms 3 months after PCR testing. Potential pre-specified predictors included SARS-CoV-2 status, sex, age, ethnicity, deprivation, quality of life/functioning (five EQ-5D-Y items), physical and mental health and loneliness (prior to testing) and number of symptoms at testing. The model was developed using logistic regression; performance was assessed using calibration and discrimination measures; internal validation was performed via bootstrapping and the final model was adjusted for overfitting.
A total of 7139 (3246 test-positives, 3893 test-negatives) completing a questionnaire 3 months post-test were included. 25.2% (817/3246) of SARS-CoV-2 PCR-positives and 18.5% (719/3893) of SARS-CoV-2 PCR-negatives had one or more impairing symptoms 3 months post-test. The final model contained SARS-CoV-2 status, number of symptoms at testing, sex, age, ethnicity, physical and mental health, loneliness and four EQ-5D-Y items before testing. Internal validation showed minimal overfitting with excellent calibration and discrimination measures (optimism-adjusted calibration slope: 0.96575; C-statistic: 0.83130).
We updated a risk prediction equation to identify those most at risk of long COVID 3 months after a SARS-CoV-2 PCR test which could serve as a useful triage and management tool for CYP during the ongoing pandemic. External validation is required before large-scale implementation.
更新并内部验证一个预测模型,以预测儿童和青少年(CYP)在 SARS-CoV-2 PCR 检测后 3 个月最有可能出现长期 COVID(即至少有一个影响生活的症状),并确定预测因素的影响是否因 SARS-CoV-2 状态而异。
使用来自 SARS-CoV-2 检测阳性和阴性 CYP 年龄在 11-17 岁的全国匹配队列的数据。主要结局指标为 PCR 检测后 3 个月出现一个或多个影响生活的症状。潜在的预先指定的预测因素包括 SARS-CoV-2 状态、性别、年龄、种族、贫困程度、生活质量/功能(五个 EQ-5D-Y 项目)、身心健康和孤独感(在检测前)以及检测时的症状数量。使用逻辑回归建立模型;使用校准和区分度测量评估性能;通过自举进行内部验证,并对最终模型进行过度拟合调整。
共有 7139 人(3246 名 SARS-CoV-2 检测阳性,3893 名 SARS-CoV-2 检测阴性)在检测后 3 个月完成了问卷调查。3246 名 SARS-CoV-2 PCR 阳性者中有 25.2%(817 人),3893 名 SARS-CoV-2 PCR 阴性者中有 18.5%(719 人)在检测后 3 个月出现一个或多个影响生活的症状。最终模型包含 SARS-CoV-2 状态、检测时的症状数量、性别、年龄、种族、身心健康、孤独感和检测前的四个 EQ-5D-Y 项目。内部验证显示,模型有轻微的过度拟合,但校准和区分度测量非常好(乐观调整校准斜率:0.96575;C 统计量:0.83130)。
我们更新了一个预测模型,以识别那些在 SARS-CoV-2 PCR 检测后 3 个月最有可能出现长期 COVID 的人,这可以作为大流行期间 CYP 的有用分诊和管理工具。在大规模实施之前,需要进行外部验证。