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http://dx.doi.org/10.25673/36370
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DC Field | Value | Language |
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dc.contributor.author | Urbach, Dietmar | - |
dc.contributor.author | Awiszus, Friedemann | - |
dc.contributor.author | Leiß, Sven | - |
dc.contributor.author | Venton, Tamsin | - |
dc.contributor.author | Specht, Alexander Vincent | - |
dc.contributor.author | Apfelbacher, Christian | - |
dc.date.accessioned | 2021-04-23T08:41:43Z | - |
dc.date.available | 2021-04-23T08:41:43Z | - |
dc.date.issued | 2020 | - |
dc.date.submitted | 2020 | - |
dc.identifier.uri | https://opendata.uni-halle.de//handle/1981185920/36602 | - |
dc.identifier.uri | http://dx.doi.org/10.25673/36370 | - |
dc.description.abstract | Background: As the COVID-19 pandemic continues to spread across the globe, the search for an effective medication to treat the symptoms of COVID-19 continues as well. It would be desirable to identify a medication that is already in use for another condition and whose side effect profile and safety data are already known and approved. Objective: The objective of this study was to evaluate the effect of different medications on typical COVID-19 symptoms by using data from an online surveillance survey. Methods: Between early April and late-July 2020, a total of 3654 individuals in Lower Saxony, Germany, participated in an online symptom-tracking survey conducted through the app covid-nein-danke.de. The questionnaire comprised items on typical COVID-19 symptoms, age range, gender, employment in patient-facing healthcare, housing status, postal code, previous illnesses, permanent medication, vaccination status, results of reverse transcription polymerase chain reaction (RT-PCR) and antibody tests for COVID-19 diagnosis, and consequent COVID-19 treatment if applicable. Odds ratio estimates with corresponding 95% CIs were computed for each medication and symptom by using logistic regression models. Results: Data analysis suggested a statistically significant inverse relationship between typical COVID-19 symptoms self-reported by the participants and self-reported statin therapy and, to a lesser extent, antihypertensive therapy. When COVID-19 diagnosis was based on restrictive symptom criteria (ie, presence of 4 out of 7 symptoms) or a positive RT-PCR test, a statistically significant association was found solely for statins (odds ratio 0.28, 95% CI 0.1-0.78). Conclusions: Individuals taking statin medication are more likely to have asymptomatic COVID-19, in which case they may be at an increased risk of transmitting the disease unknowingly. We suggest that the results of this study be incorporated into symptoms-based surveillance and decision-making protocols in regard to COVID-19 management. Whether statin therapy has a beneficial effect in combating COVID-19 cannot be deduced based on our findings and should be investigated by further study. | eng |
dc.description.sponsorship | DFG-Publikationsfonds 2020 | - |
dc.language.iso | eng | - |
dc.relation.ispartof | http://publichealth.jmir.org/ | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | COVID-19 | eng |
dc.subject | SARS-CoV-2 | eng |
dc.subject | Statins | eng |
dc.subject | Antihypertensives | eng |
dc.subject | Surveillance | eng |
dc.subject | Hydroxymethyl-glutaryl-coenzyme A reductase inhibitors | eng |
dc.subject.ddc | 610.72 | - |
dc.title | Associations of medications with lower odds of typical COVID-19 symptoms : cross-sectional symptom surveillance study | eng |
dc.type | Article | - |
dc.identifier.urn | urn:nbn:de:gbv:ma9:1-1981185920-366025 | - |
local.versionType | publishedVersion | - |
local.bibliographicCitation.journaltitle | JMIR public health and surveillance | - |
local.bibliographicCitation.volume | 6 | - |
local.bibliographicCitation.issue | 4 | - |
local.bibliographicCitation.pagestart | 1 | - |
local.bibliographicCitation.pageend | 10 | - |
local.bibliographicCitation.publishername | JMIR Publications | - |
local.bibliographicCitation.publisherplace | Toronto | - |
local.bibliographicCitation.doi | 10.2196/22521 | - |
local.openaccess | true | - |
dc.identifier.ppn | 1743000138 | - |
local.bibliographicCitation.year | 2020 | - |
cbs.sru.importDate | 2021-04-23T08:35:22Z | - |
local.bibliographicCitation | Enthalten in JMIR public health and surveillance - Toronto : JMIR Publications, 2015 | - |
local.accessrights.dnb | free | - |
Appears in Collections: | Medizinische Fakultät (OA) |
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File | Description | Size | Format | |
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Urbach et al._Associations_2020.pdf | Zweitveröffentlichung | 117.91 kB | Adobe PDF | View/Open |