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The Association between Previous Antibiotic Consumption and SARS-CoV-2 Infection: A Population-Based Case-Control Study

Dugot et al., Antibiotics, doi:10.3390/antibiotics12030587
Mar 2023  
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Case 12% Improvement Relative Risk Azithromycin for COVID-19  Dugot et al.  Prophylaxis Does azithromycin reduce COVID-19 infections? Retrospective 156,299 patients in Israel (March - December 2020) Fewer cases with azithromycin (p=0.000078) c19early.org Dugot et al., Antibiotics, March 2023 Favorsazithromycin Favorscontrol 0 0.5 1 1.5 2+
Retrospective 31,260 COVID-19 cases and 125,039 matched controls, showing lower risk of COVID-19 with previous azithromycin use.
risk of case, 11.8% lower, OR 0.88, p < 0.001, treatment 1,297 of 31,260 (4.1%) cases, 5,919 of 125,039 (4.7%) controls, NNT 47, adjusted per study, case control OR, multivariable.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Dugot et al., 15 Mar 2023, retrospective, Israel, peer-reviewed, 7 authors, study period 1 March, 2020 - 31 December, 2020. Contact: matan.dugot@gmail.com (corresponding author), emarzon@leumit.co.il, shaias@ariel.ac.il.
This PaperMiscellaneousAll
The Association between Previous Antibiotic Consumption and SARS-CoV-2 Infection: A Population-Based Case-Control Study
Matan Dugot, Eugene Merzon, Shai Ashkenazi, Shlomo Vinker, Ilan Green, Avivit Golan-Cohen, Ariel Israel
Antibiotics, doi:10.3390/antibiotics12030587
Background: The susceptibility to SARS-CoV-2 infection is complex and not yet fully elucidated, being related to many variables; these include human microbiome and immune status, which are both affected for a long period by antibiotic use. We therefore aimed to examine the association of previous antibiotic consumption and SARS-CoV-2 infection in a large-scale population-based study with control of known confounders. Methods: A matched case-control study was performed utilizing the electronic medical records of a large Health Maintenance Organization. Cases were subjects with confirmed SARS-CoV-2 infection (n = 31,260), matched individually (1:4 ratio) to controls without a positive SARS-CoV-2 test (n = 125,039). The possible association between previous antibiotic use and SARS-CoV-2 infection was determined by comparing antibiotic consumption in the previous 6 and 12 months between the cases and controls. For each antibiotic consumed we calculated the odds ratio (OR) for documented SARS-CoV-2 infection, 95% confidence interval (CI), and p-value using univariate and multivariate analyses. Results: The association between previous antibiotic consumption and SARS-CoV-2 infection was complex and bi-directional. In the multivariate analysis, phenoxymethylpenicillin was associated with increased rate of SARS-CoV-2 infection (OR 1.110, 95% CI: 1.036-1.191) while decreased rates were associated with previous consumption of trimethoprim-sulfonamides (OR 0.783, 95% CI: 0.632-0.971) and azithromycin (OR 0.882, 95% CI: 0.829-0.938). Fluroquinolones were associated with decreased rates (OR 0.923, 95% CI: 0.861-0.989) only in the univariate analysis. Previous consumption of other antibiotics had no significant association with SARS-CoV-2 infection. Conclusions: Previous consumption of certain antibiotic agents has an independent significant association with increased or decreased rates of SARS-CoV-2 infection. Plausible mechanisms, that should be further elucidated, are mainly antibiotic effects on the human microbiome and immune modulation.
Conflicts of Interest: The authors declare no conflict of interest.
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Methods: A matched ' 'case–control study was performed utilizing the electronic medical records of a large Health ' 'Maintenance Organization. Cases were subjects with confirmed SARS-CoV-2 infection (n = ' '31,260), matched individually (1:4 ratio) to controls without a positive SARS-CoV-2 test (n = ' '125,039). The possible association between previous antibiotic use and SARS-CoV-2 infection ' 'was determined by comparing antibiotic consumption in the previous 6 and 12 months between ' 'the cases and controls. For each antibiotic consumed we calculated the odds ratio (OR) for ' 'documented SARS-CoV-2 infection, 95% confidence interval (CI), and p-value using univariate ' 'and multivariate analyses. Results: The association between previous antibiotic consumption ' 'and SARS-CoV-2 infection was complex and bi-directional. In the multivariate analysis, ' 'phenoxymethylpenicillin was associated with increased rate of SARS-CoV-2 infection (OR 1.110, ' '95% CI: 1.036–1.191) while decreased rates were associated with previous consumption of ' 'trimethoprim-sulfonamides (OR 0.783, 95% CI: 0.632–0.971) and azithromycin (OR 0.882, 95% CI: ' '0.829–0.938). Fluroquinolones were associated with decreased rates (OR 0.923, 95% CI: ' '0.861–0.989) only in the univariate analysis. Previous consumption of other antibiotics had ' 'no significant association with SARS-CoV-2 infection. Conclusions: Previous consumption of ' 'certain antibiotic agents has an independent significant association with increased or ' 'decreased rates of SARS-CoV-2 infection. 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Pract.'}], 'container-title': 'Antibiotics', 'original-title': [], 'language': 'en', 'link': [ { 'URL': 'https://www.mdpi.com/2079-6382/12/3/587/pdf', 'content-type': 'unspecified', 'content-version': 'vor', 'intended-application': 'similarity-checking'}], 'deposited': { 'date-parts': [[2023, 3, 15]], 'date-time': '2023-03-15T13:10:04Z', 'timestamp': 1678885804000}, 'score': 1, 'resource': {'primary': {'URL': 'https://www.mdpi.com/2079-6382/12/3/587'}}, 'subtitle': [], 'short-title': [], 'issued': {'date-parts': [[2023, 3, 15]]}, 'references-count': 53, 'journal-issue': {'issue': '3', 'published-online': {'date-parts': [[2023, 3]]}}, 'alternative-id': ['antibiotics12030587'], 'URL': 'http://dx.doi.org/10.3390/antibiotics12030587', 'relation': {}, 'ISSN': ['2079-6382'], 'subject': [ 'Pharmacology (medical)', 'Infectious Diseases', 'Microbiology (medical)', 'General Pharmacology, Toxicology and Pharmaceutics', 'Biochemistry', 'Microbiology'], 'container-title-short': 'Antibiotics', 'published': {'date-parts': [[2023, 3, 15]]}}
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