新型冠状病毒肺炎风险预测模型的验证：PERIL前瞻性队列研究

Validation of a risk prediction model for COVID-19: the PERIL prospective cohort study.

作者信息

Mohammedain Shahd A, Badran Saif, Elzouki AbdelNaser Y, Salim Halla, Chalaby Ayesha, Siddiqui Mya, Hussein Yehia Y, Rahim Hanan Abdul, Thalib Lukman, Alam Mohammed Fasihul, Al-Badriyeh Daoud, Al-Maadeed Sumaya, Doi Suhail Ar

机构信息

Department of Population Medicine, College of Medicine, QU Health, Qatar University, Doha, Qatar.

Department of Plastic Surgery, Hamad Medical Corporation, Doha, Qatar.

出版信息

Future Virol. 2023 Oct. doi: 10.2217/fvl-2023-0036. Epub 2023 Nov 7.

DOI:10.2217/fvl-2023-0036

PMID:37970094

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10630949/

Abstract

This study aims to perform an external validation of a recently developed prognostic model for early prediction of the risk of progression to severe COVID-19. Patients were recruited at their initial diagnosis at two facilities within Hamad Medical Corporation in Qatar. 356 adults were included for analysis. Predictors for progression of COVID-19 were all measured at disease onset and first contact with the health system. The C statistic was 83% (95% CI: 78%-87%) and the calibration plot showed that the model was well-calibrated. The published prognostic model for the progression of COVID-19 infection showed satisfactory discrimination and calibration and the model is easy to apply in clinical practice.d.

摘要

本研究旨在对最近开发的用于早期预测进展为重症COVID-19风险的预后模型进行外部验证。在卡塔尔哈马德医疗公司的两家机构，患者在初次诊断时被招募。纳入356名成年人进行分析。COVID-19进展的预测指标均在疾病发作和首次接触卫生系统时进行测量。C统计量为83%（95%CI：78%-87%），校准图显示该模型校准良好。已发表的COVID-19感染进展的预后模型显示出令人满意的区分度和校准，且该模型易于在临床实践中应用。