Download PDF
NOTARZT 2021; 37(04): 209-218
DOI: 10.1055/a-1438-2019
Originalarbeit

COVID-19: ambulante oder stationäre Betreuung? – Risikoscore zur prospektiven Differenzierung leichter und schwerer Verläufe

COVID-19: In- or Outpatient Care? – Risk Score to Differentiate Expected Mild and Severe Cases
Lynn Peters 
1   Klinik für Innere Medizin III, Sektion Infektiologie, Universitätsklinikum Ulm, Deutschland
,
Sanne Burkert
1   Klinik für Innere Medizin III, Sektion Infektiologie, Universitätsklinikum Ulm, Deutschland
,
Alexander Dinse-Lambracht
2   Zentrum für Klinische Akut- und Notfallmedizin, Kliniken Aurich-Emden-Norden, Aurich, Deutschland
,
Johannes Peifer
3   Zentrale interdisziplinäre Notaufnahme, Universitätsklinikum Ulm, Deutschland
,
Beate Grüner
1   Klinik für Innere Medizin III, Sektion Infektiologie, Universitätsklinikum Ulm, Deutschland
› Author Affiliations
› Further Information
Also available at
    Permissions and Reprints

Zusammenfassung

Während die Zahl an Personen, die sich mit SARS-CoV-2 infizierte, über eine lange Zeit stieg, nahmen die Behandlungskapazitäten in den Krankenhäusern entsprechend ab. Um Patienten nicht zu gefährden und gleichzeitig Ressourcen zu schonen, ist eine frühzeitige Differenzierung zwischen prognostisch leichten und schweren Verläufen erforderlich. Zur Identifikation von COVID-19-Fällen mit stationärem Behandlungsbedarf wurde zu Beginn der Pandemie ein COVID-19-Risikoscore basierend auf einer Literaturrecherche und ersten klinischen Erfahrungen erstellt und im Rahmen einer retrospektiven Kohortenstudie mit 155 Patienten validiert. Aufgrund des hohen prädiktiven Wertes und der Diskriminierungsfähigkeit kann der etablierte COVID-19-Risikoscore ein unterstützendes Instrument für klinisch tätige Ärzte an der Sektorengrenze zwischen ambulantem und stationärem Bereich darstellen.

Abstract

The number of people in Germany infected with SARS-CoV-2 was increasing for a long time while capacities for inpatient treatment continued to decrease. In order to secure patient safety yet avoiding an excessive expend of limited resources, early differentiation between expected mild and severe courses of COVID-19 is needed. We established a literature-based COVID-19 risk score to identify COVID-19 cases requiring inpatient treatment and conducted a retrospective cohort study with 155 patients to validate our approach. Due to the high predictive value and discriminatory power, the presented COVID-19 risk score can be a valuable tool to support clinicians in their decision-making.

Schlüsselwörter

SARS-CoV-2 - Risikofaktoren - Risikoscore - schwerer Verlauf - COVID-19

Key words

SARS-CoV-2 - risk factors - risk score - severe course - COVID-19


Publication History

Article published online:
09 April 2021

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • Literatur

  • 1 Robert Koch-Institut (RKI). Täglicher Lagebericht des RKI zur Coronavirus-Krankheit-2019 (COVID-19). 15.11.2020 – Aktualisierter Stand für Deutschland. Im Internet (Stand: 20.12.2020): https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Situationsberichte/Nov_2020/2020-11-15-de.pdf?__blob=publicationFile
    Google Scholar
  • 2 Yang X, Yu Y, Xu J. et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020; 8: 475-481
    CrossrefPubMedGoogle Scholar
  • 3 Wang D, Hu B, Hu C. et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA 2020; 323: 1061-1069
    CrossrefPubMedGoogle Scholar
  • 4 Newgard CD, Haukoos JS. Advanced Statistics: Missing Data in Clinical Research–Part 2: Multiple Imputation. Acad Emerg Med 2007; 14: 669-678
    PubMedGoogle Scholar
  • 5 Liu X. Classification accuracy and cut point selection. Stat Med 2012; 31: 2676-2686
    CrossrefPubMedGoogle Scholar
  • 6 Youden WJ. Index for rating diagnostic tests. Cancer 1950; 3: 32-35
    CrossrefPubMedGoogle Scholar
  • 7 Liang W, Liang H, Ou L. et al. Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19. JAMA Intern Med 2020; 180: 1081-1089
    CrossrefPubMedGoogle Scholar
  • 8 Zhou F, Yu T, Du R. et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395: 1054-1062
    CrossrefPubMedGoogle Scholar
  • 9 Clift AK, Coupland CAC, Keogh RH. et al. Living risk prediction algorithm (QCOVID) for risk of hospital admission and mortality from coronavirus 19 in adults: national derivation and validation cohort study. BMJ 2020; 371: m3731
    CrossrefPubMedGoogle Scholar
  • 10 Williamson EJ, Walker AJ, Bhaskaran K. et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020; 584: 430-436
    Google Scholar
  • 11 McGurnaghan SJ, Weir A, Bishop J. et al. Risks of and risk factors for COVID-19 disease in people with diabetes: a cohort study of the total population of Scotland. Lancet Diabetes Endocrinol 2021; 9: 82-93
    CrossrefPubMedGoogle Scholar
  • 12 Jin J, Agarwala N, Kundu P. et al. Individual and community-level risk for COVID-19 mortality in the United States. Nat Med 2021; 27: 264-269
    CrossrefPubMedGoogle Scholar
  • 13 Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China. JAMA 2020; 323: 1239-1242
    CrossrefPubMedGoogle Scholar
  • 14 Ruan Q, Yang K, Wang W. et al. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med 2020; 46: 846-848
    CrossrefPubMedGoogle Scholar
  • 15 Guan W, Ni Z, Hu Y. et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020; 382: 1708-1720
    CrossrefPubMedGoogle Scholar
  • 16 Mousavi-Nasab SD, Mardani R, Nasr Azadani H. et al. Neutrophil to lymphocyte ratio and C-reactive protein level as prognostic markers in mild versus severe COVID-19 patients. Gastroenterol Hepatol Bed Bench 2020; 13: 361-366
    PubMedGoogle Scholar
  • 17 Du RH, Liang LR, Yang CQ. et al. Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study. Eur Respir J 2020; 55: 2000524
    CrossrefPubMedGoogle Scholar
  • 18 Salameh JP, Leeflang MMG, Hooft L. et al. Thoracic imaging tests for the diagnosis of COVID-19. Cochrane Database Syst Rev 2020; (09) CD013639
    PubMedGoogle Scholar
  • 19 Wang M, Xia C, Huang L. et al. Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation. Lancet Digit Health 2020; 2: e506-e515
    CrossrefPubMedGoogle Scholar
  • 20 Xia L, Chen J, Friedemann T. et al. The Course of Mild and Moderate COVID-19 Infections–The Unexpected Long-Lasting Challenge. Open Forum Infect Dis 2020; 7: ofaa286
    CrossrefPubMedGoogle Scholar
  • 21 Yasin R, Gouda W. Chest X-ray findings monitoring COVID-19 disease course and severity. Egypt J Radiol Nucl Med 2020; 51: 193
    CrossrefPubMedGoogle Scholar