Differentiating patients admitted primarily due to coronavirus disease 2019 (COVID-19) from those admitted with incidentally detected severe acute respiratory syndrome corona-virus type 2 (SARS-CoV-2) at hospital admission: A cohort analysis of German hospital records

Author:

Strobl RalfORCID,Misailovski MartinORCID,Blaschke SabineORCID,Berens Milena,Beste Andreas,Krone ManuelORCID,Eisenmann MichaelORCID,Ebert Sina,Hoehn Anna,Mees JulianeORCID,Kaase MartinORCID,Chackalackal Dhia J.ORCID,Koller DanielaORCID,Chrampanis Julia,Kosub Jana-Michelle,Srivastava Nikita,Albashiti FadyORCID,Groß Uwe,Fischer Andreas,Grill EvaORCID,Scheithauer SimoneORCID

Abstract

AbstractObjective:The number of hospitalized patients with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) does not differentiate between patients admitted due to coronavirus disease 2019 (COVID-19) (ie, primary cases) and incidental SARS-CoV-2 infection (ie, incidental cases). We developed an adaptable method to distinguish primary cases from incidental cases upon hospital admission.Design:Retrospective cohort study.Setting:Data were obtained from 3 German tertiary-care hospitals.Patients:The study included patients of all ages who tested positive for SARS-CoV-2 by a standard quantitative reverse-transcription polymerase chain reaction (RT-PCR) assay upon admission between January and June 2022.Methods:We present 2 distinct models: (1) a point-of-care model that can be used shortly after admission based on a limited range of parameters and (2) a more extended point-of-care model based on parameters that are available within the first 24–48 hours after admission. We used regression and tree-based classification models with internal and external validation.Results:In total, 1,150 patients were included (mean age, 49.5±28.5 years; 46% female; 40% primary cases). Both point-of-care models showed good discrimination with area under the curve (AUC) values of 0.80 and 0.87, respectively. As main predictors, we used admission diagnosis codes (ICD-10-GM), ward of admission, and for the extended model, we included viral load, need for oxygen, leucocyte count, and C-reactive protein.Conclusions:We propose 2 predictive algorithms based on routine clinical data that differentiate primary COVID-19 from incidental SARS-CoV-2 infection. These algorithms can provide a precise surveillance tool that can contribute to pandemic preparedness. They can easily be modified to be used in future pandemic, epidemic, and endemic situations all over the world.

Publisher

Cambridge University Press (CUP)

Reference29 articles.

1. 2. Fragen und Antworten zur Kostenerstattung für wahlärztliche Leistungen bei Testungen auf eine Infektion mit dem Coronavirus SARS-CoV- 2. Federal Ministry of Health of Germany website. https://www.bundesgesundheitsministerium.de/coronavirus/nationale-teststrategie/faq-wahlleistungen.html2021. Accessed January 16, 2023.

2. 1. Neue Indikatoren zur Beurteilung der Infektionslage. Federal government of Germany website. https://www.bundesregierung.de/breg-de/aktuelles/infektionsschutzgesetz- 19580862021. Accessed January 16, 2023.

3. Clinical severity of, and effectiveness of mRNA vaccines against, COVID-19 from omicron, delta, and alpha SARS-CoV-2 variants in the United States: prospective observational study;Lauring;BMJ,2022

4. A more accurate measurement of the burden of coronavirus disease 2019 hospitalizations;Vu;Open Forum Infect Dis,2022

5. Achieving integration in mixed methods designs—principles and practices;Fetters;Health Serv Res,2013

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3