% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Linder:276747,
      author       = {Linder, Roland and Peltner, Jonas and Astvatsatourov,
                      Anatoli and Gomm, Willy and Haenisch, Britta},
      title        = {{COVID}-19 in the years 2020 to 2022 in {G}ermany: effects
                      of comorbidities and co-medications based on a large-scale
                      database analysis.},
      journal      = {BMC public health},
      volume       = {25},
      number       = {1},
      issn         = {1471-2458},
      address      = {London},
      publisher    = {BioMed Central},
      reportid     = {DZNE-2025-00305},
      pages        = {525},
      year         = {2025},
      abstract     = {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.},
      keywords     = {Humans / COVID-19: epidemiology / Germany: epidemiology /
                      Comorbidity / Male / Female / Middle Aged / Adult /
                      Case-Control Studies / Aged / Databases, Factual / Risk
                      Factors / Adolescent / Young Adult / Aged, 80 and over /
                      SARS-CoV-2 / Hospitalization: statistics $\&$ numerical data
                      / Disease Progression / Child / Child, Preschool / COVID-19
                      (Other) / Case-control study (Other) / Claims data (Other) /
                      Coronavirus (Other) / Epidemiology (Other) / SARS-CoV-2
                      (Other)},
      cin          = {AG Hänisch},
      ddc          = {610},
      cid          = {I:(DE-2719)1013010},
      pnm          = {354 - Disease Prevention and Healthy Aging (POF4-354)},
      pid          = {G:(DE-HGF)POF4-354},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:39923000},
      doi          = {10.1186/s12889-024-21110-7},
      url          = {https://pub.dzne.de/record/276747},
}