COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysis.

Publication date: Feb 08, 2025

The SARS-CoV-2 pandemic was a challenge for health care systems worldwide. People with pre-existing chronic diseases have been identified as vulnerable patient groups. Furthermore, some of the drugs used for these chronic diseases such as antihypertensive drugs have been discussed as possible influencing factors on the progression of COVID-19. This study examines the effect of medication- and morbidity-associated risk factors suspected to moderate the disease course and progression of COVID-19. The study is based on claims data of the Techniker Krankenkasse, Germany’s largest statutory health insurance. The data cover the years 2020 to 2022 and include insured persons with COVID-19 diagnosis from both the outpatient and inpatient sectors and a control of insured persons without COVID-19 diagnosis. We conducted a matched case-control study and matched each patient with an inpatient diagnosis of COVID-19 to (a) 10 control patients and (b) one patient with an outpatient diagnosis of COVID-19 to form two study cohorts. We performed a descriptive analysis to describe the proportion of patients in the two cohorts who were diagnosed with comorbidities or medication use known to influence the risk of COVID-19 progression. Multiple logistic regression models were used to identify risk factors for disease progression. In the first study period the first study cohort comprised a total of 150,018 patients (13,638 cases hospitalised with COVID-19 and 136,380 control patients without a COVID-19 infection). Study cohort 2 included 27,238 patients (13,619 patients hospitalised with COVID-19 and 13,619 control patients with an outpatient COVID-19 diagnosis). Immunodeficiencies and use of immunosuppressives were strongest risk modifying factors for hospitalization in both study populations. Other comorbidities associated with hospitalization were diabetes, hypertension, and depression. We have shown that hospitalisation with COVID-19 is associated with past medical history and medication use. Furthermore, we have demonstrated the ability of claims data as a timely available data source to identify risk factors for COVID-19 severity based on large numbers of patients. Given our results, claims data have the potential to be useful as part of a surveillance protocol allowing early-stage access to epidemiological data in future pandemics.

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Concepts Keywords
Diabetes Adolescent
Germany Adult
Hospitalisation Aged
Models Aged, 80 and over
Case-Control Studies
Case-control study
Child
Child, Preschool
Claims data
Comorbidity
Coronavirus
COVID-19
COVID-19
Databases, Factual
Disease Progression
Epidemiology
Female
Germany
Hospitalization
Humans
Male
Middle Aged
Risk Factors
SARS-CoV-2
SARS-CoV-2
Young Adult

Semantics

Type Source Name
disease MESH COVID-19
disease MESH chronic diseases
disease MESH morbidity
disease IDO disease course
disease MESH disease progression
disease MESH infection
disease MESH hypertension
disease MESH depression
disease IDO history
disease MESH data source
disease MESH Long Covid
pathway REACTOME Reproduction
disease MESH pneumonia
disease MESH cardiovascular risk factors
disease MESH cardiac disease
disease MESH COPD
disease MESH death
drug DRUGBANK Timonacic
disease IDO process
drug DRUGBANK Cefradine
drug DRUGBANK Methionine
disease MESH re infection
disease MESH comorbidity
disease MESH ischemic heart disease
disease MESH benign neoplasms
drug DRUGBANK Coenzyme M
disease MESH Asthma
pathway KEGG Asthma
disease MESH respiratory diseases
disease MESH Liver diseases
drug DRUGBANK Metformin
disease IDO immunodeficiency
drug DRUGBANK Tretamine
disease MESH mood disorders
disease MESH bipolar disorders
drug DRUGBANK Fluvoxamine
drug DRUGBANK Trestolone
disease MESH missing diagnoses
disease IDO country
disease MESH viral infection
disease MESH life style
disease MESH obesity
disease IDO algorithm
disease MESH Neurodegenerative Diseases
pathway REACTOME Neurodegenerative Diseases
drug DRUGBANK (S)-Des-Me-Ampa
disease MESH Acute respiratory distress syndrome
disease MESH cytokine storm
disease MESH critically ill
disease MESH Allergy
drug DRUGBANK Guanosine
disease MESH diabetes mellitus
disease MESH syndromes
disease IDO immunosuppression
disease MESH mental disorders
drug DRUGBANK Serotonin
disease MESH complications

Original Article

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