{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Cade BE"],"funding":["NHLBI NIH HHS","NHGRI NIH HHS","NIAMS NIH HHS"],"pubmed_abstract":["<h4>Rationale</h4>Multiple pulmonary, sleep, and other disorders are associated with the severity of Covid-19 infections but may or may not directly affect the etiology of acute Covid-19 infection. Identifying the relative importance of concurrent risk factors may prioritize respiratory disease outbreaks research.<h4>Objectives</h4>To identify associations of common preexisting pulmonary and sleep disease on acute Covid-19 infection severity, investigate the relative contributions of each disease and selected risk factors, identify sex-specific effects, and examine whether additional electronic health record (EHR) information would affect these associations.<h4>Methods</h4>45 pulmonary and 6 sleep diseases were examined in 37,020 patients with Covid-19. We analyzed three outcomes: death; a composite measure of mechanical ventilation and/or ICU admission; and inpatient admission. The relative contribution of pre-infection covariates including other diseases, laboratory tests, clinical procedures, and clinical note terms was calculated using LASSO. Each pulmonary/sleep disease model was then further adjusted for covariates.<h4>Measurements and main results</h4>37 pulmonary/sleep diseases were associated with at least one outcome at Bonferroni significance, 6 of which had increased relative risk in LASSO analyses. Multiple prospectively collected non-pulmonary/sleep diseases, EHR terms and laboratory results attenuated the associations between preexisting disease and Covid-19 infection severity. Adjustment for counts of prior \"blood urea nitrogen\" phrases in clinical notes attenuated the odds ratio point estimates of 12 pulmonary disease associations with death in women by ≥1.<h4>Conclusions</h4>Pulmonary diseases are commonly associated with Covid-19 infection severity. Associations are partially attenuated by prospectively-collected EHR data, which may aid in risk stratification and physiological studies."],"journal":["medRxiv : the preprint server for health sciences"],"pagination":["2023.02.19.23286148"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9980259"],"repository":["biostudies-literature"],"pubmed_title":["Impact of Pulmonary and Sleep Disorders on COVID-19 Infection Severity in a Large Clinical Biobank."],"pmcid":["PMC9980259"],"funding_grant_id":["R35 HL135818","U01 HG008685","R03 HL154284","R01 HL153805","P30 AR070253"],"pubmed_authors":["Hassan SM","Cade BE","Karlson EW","Mullington JM","Redline S"],"additional_accession":[]},"is_claimable":false,"name":"Impact of Pulmonary and Sleep Disorders on COVID-19 Infection Severity in a Large Clinical Biobank.","description":"<h4>Rationale</h4>Multiple pulmonary, sleep, and other disorders are associated with the severity of Covid-19 infections but may or may not directly affect the etiology of acute Covid-19 infection. Identifying the relative importance of concurrent risk factors may prioritize respiratory disease outbreaks research.<h4>Objectives</h4>To identify associations of common preexisting pulmonary and sleep disease on acute Covid-19 infection severity, investigate the relative contributions of each disease and selected risk factors, identify sex-specific effects, and examine whether additional electronic health record (EHR) information would affect these associations.<h4>Methods</h4>45 pulmonary and 6 sleep diseases were examined in 37,020 patients with Covid-19. We analyzed three outcomes: death; a composite measure of mechanical ventilation and/or ICU admission; and inpatient admission. The relative contribution of pre-infection covariates including other diseases, laboratory tests, clinical procedures, and clinical note terms was calculated using LASSO. Each pulmonary/sleep disease model was then further adjusted for covariates.<h4>Measurements and main results</h4>37 pulmonary/sleep diseases were associated with at least one outcome at Bonferroni significance, 6 of which had increased relative risk in LASSO analyses. Multiple prospectively collected non-pulmonary/sleep diseases, EHR terms and laboratory results attenuated the associations between preexisting disease and Covid-19 infection severity. Adjustment for counts of prior \"blood urea nitrogen\" phrases in clinical notes attenuated the odds ratio point estimates of 12 pulmonary disease associations with death in women by ≥1.<h4>Conclusions</h4>Pulmonary diseases are commonly associated with Covid-19 infection severity. Associations are partially attenuated by prospectively-collected EHR data, which may aid in risk stratification and physiological studies.","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Feb","modification":"2025-04-04T21:55:06.15Z","creation":"2025-04-04T21:55:06.15Z"},"accession":"S-EPMC9980259","cross_references":{"pubmed":["36865276"],"doi":["10.1101/2023.02.19.23286148"]}}