COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysis
Abstract Background 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 discusse...
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BMC
2025-02-01
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| Online Access: | https://doi.org/10.1186/s12889-024-21110-7 |
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| author | Roland Linder Jonas Peltner Anatoli Astvatsatourov Willy Gomm Britta Haenisch |
| author_facet | Roland Linder Jonas Peltner Anatoli Astvatsatourov Willy Gomm Britta Haenisch |
| author_sort | Roland Linder |
| collection | DOAJ |
| description | Abstract Background 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. Methods 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. Results 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. Conclusion 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. |
| format | Article |
| id | doaj-art-aee690bee76648fa93d7e2a0679e5568 |
| institution | Kabale University |
| issn | 1471-2458 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj-art-aee690bee76648fa93d7e2a0679e55682025-02-09T12:58:11ZengBMCBMC Public Health1471-24582025-02-0125111410.1186/s12889-024-21110-7COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysisRoland Linder0Jonas Peltner1Anatoli Astvatsatourov2Willy Gomm3Britta Haenisch4Techniker KrankenkasseGerman Center for Neurodegenerative Diseases (DZNE) e.VClinical Trials Division, Federal Institute for Drugs and Medical DevicesGerman Center for Neurodegenerative Diseases (DZNE) e.VGerman Center for Neurodegenerative Diseases (DZNE) e.VAbstract Background 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. Methods 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. Results 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. Conclusion 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.https://doi.org/10.1186/s12889-024-21110-7Case-control studyCOVID-19CoronavirusSARS-CoV-2EpidemiologyClaims data |
| spellingShingle | Roland Linder Jonas Peltner Anatoli Astvatsatourov Willy Gomm Britta Haenisch COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysis BMC Public Health Case-control study COVID-19 Coronavirus SARS-CoV-2 Epidemiology Claims data |
| title | COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysis |
| title_full | COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysis |
| title_fullStr | COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysis |
| title_full_unstemmed | COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysis |
| title_short | COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysis |
| title_sort | covid 19 in the years 2020 to 2022 in germany effects of comorbidities and co medications based on a large scale database analysis |
| topic | Case-control study COVID-19 Coronavirus SARS-CoV-2 Epidemiology Claims data |
| url | https://doi.org/10.1186/s12889-024-21110-7 |
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