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Deforth M, Gebhard CE, Bengs S, Buehler PK, Schuepbach RA, Zinkernagel AS, Brugger SD, Acevedo CT, Patriki D, Wiggli B, Twerenbold R, Kuster GM, Pargger H, Schefold JC, Spinetti T, Wendel-Garcia PD, Hofmaenner DA, Gysi B, Siegemund M, Heinze G, Regitz-Zagrosek V, Gebhard C, Held U. Development and validation of a prognostic model for the early identification of COVID-19 patients at risk of developing common long COVID symptoms. Diagn Progn Res 2022; 6:22. [PMID: 36384641 PMCID: PMC9668400 DOI: 10.1186/s41512-022-00135-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 09/30/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID symptoms at least 60 days after acute COVID-19. METHODS The prognostic model was built based on data from a multicentre prospective Swiss cohort study. Included were adult patients diagnosed with COVID-19 between February and December 2020 and treated as outpatients, at ward or intensive/intermediate care unit. Perceived long-term health impairments, including reduced exercise tolerance/reduced resilience, shortness of breath and/or tiredness (REST), were assessed after a follow-up time between 60 and 425 days. The data set was split into a derivation and a geographical validation cohort. Predictors were selected out of twelve candidate predictors based on three methods, namely the augmented backward elimination (ABE) method, the adaptive best-subset selection (ABESS) method and model-based recursive partitioning (MBRP) approach. Model performance was assessed with the scaled Brier score, concordance c statistic and calibration plot. The final prognostic model was determined based on best model performance. RESULTS In total, 2799 patients were included in the analysis, of which 1588 patients were in the derivation cohort and 1211 patients in the validation cohort. The REST prevalence was similar between the cohorts with 21.6% (n = 343) in the derivation cohort and 22.1% (n = 268) in the validation cohort. The same predictors were selected with the ABE and ABESS approach. The final prognostic model was based on the ABE and ABESS selected predictors. The corresponding scaled Brier score in the validation cohort was 18.74%, model discrimination was 0.78 (95% CI: 0.75 to 0.81), calibration slope was 0.92 (95% CI: 0.78 to 1.06) and calibration intercept was -0.06 (95% CI: -0.22 to 0.09). CONCLUSION The proposed model was validated to identify COVID-19-infected patients at high risk for REST symptoms. Before implementing the prognostic model in daily clinical practice, the conduct of an impact study is recommended.
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Affiliation(s)
- Manja Deforth
- Department of Biostatistics at Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
| | - Caroline E Gebhard
- Intensive Care Unit, Department of Acute Medicine, University Hospital Basel, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Susan Bengs
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, Schlieren, Switzerland
| | - Philipp K Buehler
- Institute of Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Reto A Schuepbach
- Institute of Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland
- University of Zurich, Zurich, Switzerland
| | - Annelies S Zinkernagel
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Silvio D Brugger
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Claudio T Acevedo
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Dimitri Patriki
- Department of Internal Medicine, Cantonal Hospital Baden, Baden, Switzerland
| | - Benedikt Wiggli
- Department of Infectiology and Infection Control, Cantonal Hospital Baden, Baden, Switzerland
| | - Raphael Twerenbold
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- University Center of Cardiovascular Science & Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK) Partner Site Hamburg-Kiel-Lübeck, Berlin, Germany
| | - Gabriela M Kuster
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
| | - Hans Pargger
- Intensive Care Unit, Department of Acute Medicine, University Hospital Basel, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Joerg C Schefold
- Department of Intensive Care Medicine, University Hospital Bern, Bern, Switzerland
| | - Thibaud Spinetti
- Department of Intensive Care Medicine, University Hospital Bern, Bern, Switzerland
| | - Pedro D Wendel-Garcia
- Institute of Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Daniel A Hofmaenner
- Institute of Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Bianca Gysi
- Intensive Care Unit, Department of Acute Medicine, University Hospital Basel, Basel, Switzerland
| | - Martin Siegemund
- Intensive Care Unit, Department of Acute Medicine, University Hospital Basel, Basel, Switzerland
- Department Clinical Research, University of Basel, Basel, Switzerland
| | - Georg Heinze
- Center for Medical Statistics, Informatics and Intelligent Systems, Section for Clinical Biometrics, Medical University of Vienna, Vienna, Austria
| | - Vera Regitz-Zagrosek
- University of Zurich, Zurich, Switzerland
- Charité, University Medicine Berlin, Berlin, Germany
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Catherine Gebhard
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, Schlieren, Switzerland
- University of Zurich, Zurich, Switzerland
| | - Ulrike Held
- Department of Biostatistics at Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
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