Susceptibility to and severity of SARS-CoV-2 infection according to prescription drug use-an observational study of 46,506 Danish healthcare workers
It is not well investigated whether exposure to specific drug classes is associated with COVID-19. We investigated the risk of SARS-CoV-2 infection and severe COVID-19 among healthcare workers according to prescription drug use. We conducted an observational study among Danish healthcare workers. SA...
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| creator | Eiken, Aleksander Bliddal, Sofie Villumsen, Marie Iversen, Kasper K Bundgaard, Henning Hasselbach, Rasmus B Kristensen, Jonas H Nielsen, Pernille B Pries-Heje, Mia M Knudsen, Andreas D Fogh, Kamille Norsk, Jakob B Andersen, Ove Fischer, Thea K Dessau, Ram B Ostrowski, Sisse R Torp-Pedersen, Christian Ditlev, Sisse B Gybel-Brask, Mikkel Sørensen, Erik Harritshøj, Lene H Folke, Fredrik Benfield, Thomas Engsig, Frederik N Poulsen, Henrik E Ullum, Henrik Feldt-Rasmussen, Ulla Nielsen, Susanne D Rungby, Jørgen |
| description | It is not well investigated whether exposure to specific drug classes is associated with COVID-19. We investigated the risk of SARS-CoV-2 infection and severe COVID-19 among healthcare workers according to prescription drug use. We conducted an observational study among Danish healthcare workers. SARS-CoV-2 positivity was defined as a positive PCR/ELISA test throughout 2020 and severe COVID-19 as any above 48-hour hospitalization within 14 days after infection. Patient characteristics came from online surveys while data on SARS-CoV-2, drugs and hospitalizations came from Danish Health Registers. Infected individuals were matched with uninfected controls based on age, sex, and chronic diseases. Drug exposure was defined as any prescription redemption in the past six and one month(s) before infection for each drug class. Models assessing the risk of infection (conditional logistic regression) and severe COVID-19 (logistic regressions) versus drug usage were adjusted for BMI, smoking, alcohol, education, region, and patient contact when possible. We matched 5,710 SARS-CoV-2-infected cases with 57,021 controls. The odds of infection were reduced by calcium channel blocker (adjusted odds ratio (aOR) 0.81, 95% Confidence Interval (CI): 0.66-1.00) and vasoprotective drug (aOR 0.77, CI: 0.62-0.95) usage during the six months before infection compared to no usage. Exposure to antibacterials in the past month increased the odds of infection (aOR 1.27, CI: 1.09-1.48). Among infected participants, the odds of severe COVID-19 were higher with usage of almost any investigated drug, especially, diuretics (crude odds radio (OR) 4.82, CI:2.15-10.83), obstructive airway disease drugs (OR 4.49, CI: 2.49-8.08), and antibacterials (OR 2.74 CI:1.62-4.61). In conclusion, antibacterials were associated with more SARS-CoV-2 infections and calcium channel blockers with less. Once infected, users of prescription drugs had higher odds of developing severe COVID-19. These findings suggest a need for studies to clarify interactions between specific drug groups, behaviour, known risk factors, and disease susceptibility/severity. |
| doi_str_mv | 10.1371/journal.pone.0311260 |
| format | Article |
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We investigated the risk of SARS-CoV-2 infection and severe COVID-19 among healthcare workers according to prescription drug use. We conducted an observational study among Danish healthcare workers. SARS-CoV-2 positivity was defined as a positive PCR/ELISA test throughout 2020 and severe COVID-19 as any above 48-hour hospitalization within 14 days after infection. Patient characteristics came from online surveys while data on SARS-CoV-2, drugs and hospitalizations came from Danish Health Registers. Infected individuals were matched with uninfected controls based on age, sex, and chronic diseases. Drug exposure was defined as any prescription redemption in the past six and one month(s) before infection for each drug class. Models assessing the risk of infection (conditional logistic regression) and severe COVID-19 (logistic regressions) versus drug usage were adjusted for BMI, smoking, alcohol, education, region, and patient contact when possible. We matched 5,710 SARS-CoV-2-infected cases with 57,021 controls. The odds of infection were reduced by calcium channel blocker (adjusted odds ratio (aOR) 0.81, 95% Confidence Interval (CI): 0.66-1.00) and vasoprotective drug (aOR 0.77, CI: 0.62-0.95) usage during the six months before infection compared to no usage. Exposure to antibacterials in the past month increased the odds of infection (aOR 1.27, CI: 1.09-1.48). Among infected participants, the odds of severe COVID-19 were higher with usage of almost any investigated drug, especially, diuretics (crude odds radio (OR) 4.82, CI:2.15-10.83), obstructive airway disease drugs (OR 4.49, CI: 2.49-8.08), and antibacterials (OR 2.74 CI:1.62-4.61). In conclusion, antibacterials were associated with more SARS-CoV-2 infections and calcium channel blockers with less. Once infected, users of prescription drugs had higher odds of developing severe COVID-19. These findings suggest a need for studies to clarify interactions between specific drug groups, behaviour, known risk factors, and disease susceptibility/severity.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0311260</identifier><identifier>PMID: 39602471</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Allergic diseases ; Antihypertensive drugs ; Asthma ; Biology and life sciences ; Body mass index ; Calcium ; Calcium channel blockers ; Calcium Channel Blockers - therapeutic use ; Calcium channels ; Cardiovascular disease ; Case-Control Studies ; Chronic diseases ; Chronic illnesses ; Chronic infection ; COVID-19 ; COVID-19 - epidemiology ; Denmark - epidemiology ; Diabetes ; Disease prevention ; Disease Susceptibility ; Disease transmission ; Diuretics ; Drug interaction ; Drug use ; Drugs ; Enzymes ; Evaluation ; Exposure ; Female ; Health aspects ; Health care ; Health Personnel ; Health risks ; Hospitals ; Humans ; Hypertension ; Immune system ; Infection ; Infections ; Kidney diseases ; Lung diseases ; Male ; Medical personnel ; Medical research ; Medicine and health sciences ; Medicine, Experimental ; Middle Aged ; Observational studies ; Occupational exposure ; Pandemics ; People and Places ; Prescribing ; Prescription drugs ; Prescription Drugs - therapeutic use ; Questionnaires ; Regression analysis ; Research and Analysis Methods ; Respiratory tract diseases ; Risk assessment ; Risk Factors ; Risk taking ; SARS-CoV-2 - isolation & purification ; Self report ; Severe acute respiratory syndrome coronavirus 2 ; Severity of Illness Index ; Social Sciences ; Statistical analysis ; Steroids ; Surveys ; Viral diseases ; Workers</subject><ispartof>PloS one, 2024-11, Vol.19 (11), p.e0311260</ispartof><rights>Copyright: © 2024 Eiken et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Eiken et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Eiken et al 2024 Eiken et al</rights><rights>2024 Eiken et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c4870-b154386ed54ba4cbecaf12e444ee341cbd49b7a2134cd6c578238e13081de6e3</cites><orcidid>0000-0001-8454-4686 ; 0000-0002-5903-3355 ; 0000-0001-9067-548X ; 0000-0003-4417-9711 ; 0000-0002-1497-6309 ; 0000-0002-2456-1019 ; 0000-0003-2892-6131 ; 0000-0002-5716-5899 ; 0000-0003-4274-6268</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602038/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602038/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39602471$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Jacobsen, Ramune</contributor><creatorcontrib>Eiken, Aleksander</creatorcontrib><creatorcontrib>Bliddal, Sofie</creatorcontrib><creatorcontrib>Villumsen, Marie</creatorcontrib><creatorcontrib>Iversen, Kasper K</creatorcontrib><creatorcontrib>Bundgaard, Henning</creatorcontrib><creatorcontrib>Hasselbach, Rasmus B</creatorcontrib><creatorcontrib>Kristensen, Jonas H</creatorcontrib><creatorcontrib>Nielsen, Pernille B</creatorcontrib><creatorcontrib>Pries-Heje, Mia M</creatorcontrib><creatorcontrib>Knudsen, Andreas D</creatorcontrib><creatorcontrib>Fogh, Kamille</creatorcontrib><creatorcontrib>Norsk, Jakob B</creatorcontrib><creatorcontrib>Andersen, Ove</creatorcontrib><creatorcontrib>Fischer, Thea K</creatorcontrib><creatorcontrib>Dessau, Ram B</creatorcontrib><creatorcontrib>Ostrowski, Sisse R</creatorcontrib><creatorcontrib>Torp-Pedersen, Christian</creatorcontrib><creatorcontrib>Ditlev, Sisse B</creatorcontrib><creatorcontrib>Gybel-Brask, Mikkel</creatorcontrib><creatorcontrib>Sørensen, Erik</creatorcontrib><creatorcontrib>Harritshøj, Lene H</creatorcontrib><creatorcontrib>Folke, Fredrik</creatorcontrib><creatorcontrib>Benfield, Thomas</creatorcontrib><creatorcontrib>Engsig, Frederik N</creatorcontrib><creatorcontrib>Poulsen, Henrik E</creatorcontrib><creatorcontrib>Ullum, Henrik</creatorcontrib><creatorcontrib>Feldt-Rasmussen, Ulla</creatorcontrib><creatorcontrib>Nielsen, Susanne D</creatorcontrib><creatorcontrib>Rungby, Jørgen</creatorcontrib><title>Susceptibility to and severity of SARS-CoV-2 infection according to prescription drug use-an observational study of 46,506 Danish healthcare workers</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>It is not well investigated whether exposure to specific drug classes is associated with COVID-19. We investigated the risk of SARS-CoV-2 infection and severe COVID-19 among healthcare workers according to prescription drug use. We conducted an observational study among Danish healthcare workers. SARS-CoV-2 positivity was defined as a positive PCR/ELISA test throughout 2020 and severe COVID-19 as any above 48-hour hospitalization within 14 days after infection. Patient characteristics came from online surveys while data on SARS-CoV-2, drugs and hospitalizations came from Danish Health Registers. Infected individuals were matched with uninfected controls based on age, sex, and chronic diseases. Drug exposure was defined as any prescription redemption in the past six and one month(s) before infection for each drug class. Models assessing the risk of infection (conditional logistic regression) and severe COVID-19 (logistic regressions) versus drug usage were adjusted for BMI, smoking, alcohol, education, region, and patient contact when possible. We matched 5,710 SARS-CoV-2-infected cases with 57,021 controls. The odds of infection were reduced by calcium channel blocker (adjusted odds ratio (aOR) 0.81, 95% Confidence Interval (CI): 0.66-1.00) and vasoprotective drug (aOR 0.77, CI: 0.62-0.95) usage during the six months before infection compared to no usage. Exposure to antibacterials in the past month increased the odds of infection (aOR 1.27, CI: 1.09-1.48). Among infected participants, the odds of severe COVID-19 were higher with usage of almost any investigated drug, especially, diuretics (crude odds radio (OR) 4.82, CI:2.15-10.83), obstructive airway disease drugs (OR 4.49, CI: 2.49-8.08), and antibacterials (OR 2.74 CI:1.62-4.61). In conclusion, antibacterials were associated with more SARS-CoV-2 infections and calcium channel blockers with less. Once infected, users of prescription drugs had higher odds of developing severe COVID-19. These findings suggest a need for studies to clarify interactions between specific drug groups, behaviour, known risk factors, and disease susceptibility/severity.</description><subject>Adult</subject><subject>Allergic diseases</subject><subject>Antihypertensive drugs</subject><subject>Asthma</subject><subject>Biology and life sciences</subject><subject>Body mass index</subject><subject>Calcium</subject><subject>Calcium channel blockers</subject><subject>Calcium Channel Blockers - therapeutic use</subject><subject>Calcium channels</subject><subject>Cardiovascular disease</subject><subject>Case-Control Studies</subject><subject>Chronic diseases</subject><subject>Chronic illnesses</subject><subject>Chronic infection</subject><subject>COVID-19</subject><subject>COVID-19 - epidemiology</subject><subject>Denmark - epidemiology</subject><subject>Diabetes</subject><subject>Disease prevention</subject><subject>Disease Susceptibility</subject><subject>Disease transmission</subject><subject>Diuretics</subject><subject>Drug interaction</subject><subject>Drug use</subject><subject>Drugs</subject><subject>Enzymes</subject><subject>Evaluation</subject><subject>Exposure</subject><subject>Female</subject><subject>Health aspects</subject><subject>Health care</subject><subject>Health Personnel</subject><subject>Health risks</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Immune system</subject><subject>Infection</subject><subject>Infections</subject><subject>Kidney diseases</subject><subject>Lung diseases</subject><subject>Male</subject><subject>Medical personnel</subject><subject>Medical research</subject><subject>Medicine and health sciences</subject><subject>Medicine, Experimental</subject><subject>Middle Aged</subject><subject>Observational studies</subject><subject>Occupational exposure</subject><subject>Pandemics</subject><subject>People and Places</subject><subject>Prescribing</subject><subject>Prescription drugs</subject><subject>Prescription Drugs - therapeutic use</subject><subject>Questionnaires</subject><subject>Regression analysis</subject><subject>Research and Analysis Methods</subject><subject>Respiratory tract diseases</subject><subject>Risk assessment</subject><subject>Risk Factors</subject><subject>Risk taking</subject><subject>SARS-CoV-2 - isolation & purification</subject><subject>Self report</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Severity of Illness Index</subject><subject>Social Sciences</subject><subject>Statistical analysis</subject><subject>Steroids</subject><subject>Surveys</subject><subject>Viral 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to and severity of SARS-CoV-2 infection according to prescription drug use-an observational study of 46,506 Danish healthcare workers</title><author>Eiken, Aleksander ; Bliddal, Sofie ; Villumsen, Marie ; Iversen, Kasper K ; Bundgaard, Henning ; Hasselbach, Rasmus B ; Kristensen, Jonas H ; Nielsen, Pernille B ; Pries-Heje, Mia M ; Knudsen, Andreas D ; Fogh, Kamille ; Norsk, Jakob B ; Andersen, Ove ; Fischer, Thea K ; Dessau, Ram B ; Ostrowski, Sisse R ; Torp-Pedersen, Christian ; Ditlev, Sisse B ; Gybel-Brask, Mikkel ; Sørensen, Erik ; Harritshøj, Lene H ; Folke, Fredrik ; Benfield, Thomas ; Engsig, Frederik N ; Poulsen, Henrik E ; Ullum, Henrik ; Feldt-Rasmussen, Ulla ; Nielsen, Susanne D ; Rungby, Jørgen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4870-b154386ed54ba4cbecaf12e444ee341cbd49b7a2134cd6c578238e13081de6e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adult</topic><topic>Allergic diseases</topic><topic>Antihypertensive drugs</topic><topic>Asthma</topic><topic>Biology and life sciences</topic><topic>Body mass index</topic><topic>Calcium</topic><topic>Calcium channel blockers</topic><topic>Calcium Channel Blockers - therapeutic use</topic><topic>Calcium channels</topic><topic>Cardiovascular disease</topic><topic>Case-Control Studies</topic><topic>Chronic diseases</topic><topic>Chronic illnesses</topic><topic>Chronic infection</topic><topic>COVID-19</topic><topic>COVID-19 - epidemiology</topic><topic>Denmark - epidemiology</topic><topic>Diabetes</topic><topic>Disease prevention</topic><topic>Disease Susceptibility</topic><topic>Disease transmission</topic><topic>Diuretics</topic><topic>Drug interaction</topic><topic>Drug use</topic><topic>Drugs</topic><topic>Enzymes</topic><topic>Evaluation</topic><topic>Exposure</topic><topic>Female</topic><topic>Health aspects</topic><topic>Health care</topic><topic>Health Personnel</topic><topic>Health risks</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Immune system</topic><topic>Infection</topic><topic>Infections</topic><topic>Kidney diseases</topic><topic>Lung diseases</topic><topic>Male</topic><topic>Medical personnel</topic><topic>Medical research</topic><topic>Medicine and health sciences</topic><topic>Medicine, Experimental</topic><topic>Middle Aged</topic><topic>Observational studies</topic><topic>Occupational exposure</topic><topic>Pandemics</topic><topic>People and Places</topic><topic>Prescribing</topic><topic>Prescription drugs</topic><topic>Prescription Drugs - therapeutic use</topic><topic>Questionnaires</topic><topic>Regression analysis</topic><topic>Research and Analysis Methods</topic><topic>Respiratory tract diseases</topic><topic>Risk assessment</topic><topic>Risk Factors</topic><topic>Risk taking</topic><topic>SARS-CoV-2 - isolation & purification</topic><topic>Self report</topic><topic>Severe acute respiratory syndrome coronavirus 2</topic><topic>Severity of Illness Index</topic><topic>Social Sciences</topic><topic>Statistical analysis</topic><topic>Steroids</topic><topic>Surveys</topic><topic>Viral diseases</topic><topic>Workers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Eiken, Aleksander</creatorcontrib><creatorcontrib>Bliddal, Sofie</creatorcontrib><creatorcontrib>Villumsen, Marie</creatorcontrib><creatorcontrib>Iversen, Kasper K</creatorcontrib><creatorcontrib>Bundgaard, Henning</creatorcontrib><creatorcontrib>Hasselbach, Rasmus B</creatorcontrib><creatorcontrib>Kristensen, Jonas H</creatorcontrib><creatorcontrib>Nielsen, Pernille B</creatorcontrib><creatorcontrib>Pries-Heje, Mia M</creatorcontrib><creatorcontrib>Knudsen, Andreas D</creatorcontrib><creatorcontrib>Fogh, Kamille</creatorcontrib><creatorcontrib>Norsk, Jakob B</creatorcontrib><creatorcontrib>Andersen, Ove</creatorcontrib><creatorcontrib>Fischer, Thea K</creatorcontrib><creatorcontrib>Dessau, Ram B</creatorcontrib><creatorcontrib>Ostrowski, Sisse R</creatorcontrib><creatorcontrib>Torp-Pedersen, Christian</creatorcontrib><creatorcontrib>Ditlev, Sisse B</creatorcontrib><creatorcontrib>Gybel-Brask, Mikkel</creatorcontrib><creatorcontrib>Sørensen, Erik</creatorcontrib><creatorcontrib>Harritshøj, Lene H</creatorcontrib><creatorcontrib>Folke, Fredrik</creatorcontrib><creatorcontrib>Benfield, Thomas</creatorcontrib><creatorcontrib>Engsig, Frederik N</creatorcontrib><creatorcontrib>Poulsen, Henrik E</creatorcontrib><creatorcontrib>Ullum, Henrik</creatorcontrib><creatorcontrib>Feldt-Rasmussen, Ulla</creatorcontrib><creatorcontrib>Nielsen, Susanne D</creatorcontrib><creatorcontrib>Rungby, Jørgen</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Opposing Viewpoints in Context (Gale)</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids 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Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Eiken, Aleksander</au><au>Bliddal, Sofie</au><au>Villumsen, Marie</au><au>Iversen, Kasper K</au><au>Bundgaard, Henning</au><au>Hasselbach, Rasmus B</au><au>Kristensen, Jonas H</au><au>Nielsen, Pernille B</au><au>Pries-Heje, Mia M</au><au>Knudsen, Andreas D</au><au>Fogh, Kamille</au><au>Norsk, Jakob B</au><au>Andersen, Ove</au><au>Fischer, Thea K</au><au>Dessau, Ram B</au><au>Ostrowski, Sisse R</au><au>Torp-Pedersen, Christian</au><au>Ditlev, Sisse B</au><au>Gybel-Brask, Mikkel</au><au>Sørensen, Erik</au><au>Harritshøj, Lene H</au><au>Folke, Fredrik</au><au>Benfield, Thomas</au><au>Engsig, Frederik N</au><au>Poulsen, Henrik E</au><au>Ullum, Henrik</au><au>Feldt-Rasmussen, Ulla</au><au>Nielsen, Susanne D</au><au>Rungby, Jørgen</au><au>Jacobsen, Ramune</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Susceptibility to and severity of SARS-CoV-2 infection according to prescription drug use-an observational study of 46,506 Danish healthcare workers</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2024-11-27</date><risdate>2024</risdate><volume>19</volume><issue>11</issue><spage>e0311260</spage><pages>e0311260-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>It is not well investigated whether exposure to specific drug classes is associated with COVID-19. We investigated the risk of SARS-CoV-2 infection and severe COVID-19 among healthcare workers according to prescription drug use. We conducted an observational study among Danish healthcare workers. SARS-CoV-2 positivity was defined as a positive PCR/ELISA test throughout 2020 and severe COVID-19 as any above 48-hour hospitalization within 14 days after infection. Patient characteristics came from online surveys while data on SARS-CoV-2, drugs and hospitalizations came from Danish Health Registers. Infected individuals were matched with uninfected controls based on age, sex, and chronic diseases. Drug exposure was defined as any prescription redemption in the past six and one month(s) before infection for each drug class. Models assessing the risk of infection (conditional logistic regression) and severe COVID-19 (logistic regressions) versus drug usage were adjusted for BMI, smoking, alcohol, education, region, and patient contact when possible. We matched 5,710 SARS-CoV-2-infected cases with 57,021 controls. The odds of infection were reduced by calcium channel blocker (adjusted odds ratio (aOR) 0.81, 95% Confidence Interval (CI): 0.66-1.00) and vasoprotective drug (aOR 0.77, CI: 0.62-0.95) usage during the six months before infection compared to no usage. Exposure to antibacterials in the past month increased the odds of infection (aOR 1.27, CI: 1.09-1.48). Among infected participants, the odds of severe COVID-19 were higher with usage of almost any investigated drug, especially, diuretics (crude odds radio (OR) 4.82, CI:2.15-10.83), obstructive airway disease drugs (OR 4.49, CI: 2.49-8.08), and antibacterials (OR 2.74 CI:1.62-4.61). In conclusion, antibacterials were associated with more SARS-CoV-2 infections and calcium channel blockers with less. Once infected, users of prescription drugs had higher odds of developing severe COVID-19. These findings suggest a need for studies to clarify interactions between specific drug groups, behaviour, known risk factors, and disease susceptibility/severity.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>39602471</pmid><doi>10.1371/journal.pone.0311260</doi><tpages>e0311260</tpages><orcidid>https://orcid.org/0000-0001-8454-4686</orcidid><orcidid>https://orcid.org/0000-0002-5903-3355</orcidid><orcidid>https://orcid.org/0000-0001-9067-548X</orcidid><orcidid>https://orcid.org/0000-0003-4417-9711</orcidid><orcidid>https://orcid.org/0000-0002-1497-6309</orcidid><orcidid>https://orcid.org/0000-0002-2456-1019</orcidid><orcidid>https://orcid.org/0000-0003-2892-6131</orcidid><orcidid>https://orcid.org/0000-0002-5716-5899</orcidid><orcidid>https://orcid.org/0000-0003-4274-6268</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2024-11, Vol.19 (11), p.e0311260 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_3133645098 |
| source | Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adult Allergic diseases Antihypertensive drugs Asthma Biology and life sciences Body mass index Calcium Calcium channel blockers Calcium Channel Blockers - therapeutic use Calcium channels Cardiovascular disease Case-Control Studies Chronic diseases Chronic illnesses Chronic infection COVID-19 COVID-19 - epidemiology Denmark - epidemiology Diabetes Disease prevention Disease Susceptibility Disease transmission Diuretics Drug interaction Drug use Drugs Enzymes Evaluation Exposure Female Health aspects Health care Health Personnel Health risks Hospitals Humans Hypertension Immune system Infection Infections Kidney diseases Lung diseases Male Medical personnel Medical research Medicine and health sciences Medicine, Experimental Middle Aged Observational studies Occupational exposure Pandemics People and Places Prescribing Prescription drugs Prescription Drugs - therapeutic use Questionnaires Regression analysis Research and Analysis Methods Respiratory tract diseases Risk assessment Risk Factors Risk taking SARS-CoV-2 - isolation & purification Self report Severe acute respiratory syndrome coronavirus 2 Severity of Illness Index Social Sciences Statistical analysis Steroids Surveys Viral diseases Workers |
| title | Susceptibility to and severity of SARS-CoV-2 infection according to prescription drug use-an observational study of 46,506 Danish healthcare workers |
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