{"doi":"10.1101/2020.07.03.20145581","title":"Prior diagnoses and medications as risk factors for COVID-19 in a Los Angeles Health System","abstract":"Summary With the continuing coronavirus disease 2019 (COVID-19) pandemic coupled with phased reopening, it is critical to identify risk factors associated with susceptibility and severity of disease in a diverse population to help shape government policies, guide clinical decision making, and prioritize future COVID-19 research. In this retrospective case-control study, we used de-identified electronic health records (EHR) from the University of California Los Angeles (UCLA) Health System between March 9 th , 2020 and June 14 th , 2020 to identify risk factors for COVID-19 susceptibility (severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) PCR test positive), inpatient admission, and severe outcomes (treatment in an intensive care unit or intubation). Of the 26,602 individuals tested by PCR for SARS-CoV-2, 992 were COVID-19 positive (3.7% of Tested), 220 were admitted in the hospital (22% of COVID-19 positive), and 77 had a severe outcome (35% of Inpatient). Consistent with previous studies, males and individuals older than 65 years old had increased risk of inpatient admission. Notably, individuals self-identifying as Hispanic or Latino constituted an increasing percentage of COVID-19 patients as disease severity escalated, comprising 24% of those testing positive, but 40% of those with a severe outcome, a disparity that remained after correcting for medical co-morbidities. Cardiovascular disease, hypertension, and renal disease were premorbid risk factors present before SARS-CoV-2 PCR testing associated with COVID-19 susceptibility. Less well-established risk factors for COVID-19 susceptibility included pre-existing dementia (odds ratio (OR) 5.2 [3.2-8.3], p=2.6 × 10 −10 ), mental health conditions (depression OR 2.1 [1.6-2.8], p=1.1 × 10 −6 ) and vitamin D deficiency (OR 1.8 [1.4-2.2], p=5.7 × 10 −6 ). Renal diseases including end-stage renal disease and anemia due to chronic renal disease were the predominant premorbid risk factors for COVID-19 inpatient admission. Other less established risk factors for COVID-19 inpatient admission included previous renal transplant (OR 9.7 [2.8-39], p=3.2×10 −4 ) and disorders of the immune system (OR 6.0 [2.3, 16], p=2.7×10 −4 ). Prior use of oral steroid medications was associated with decreased COVID-19 positive testing risk (OR 0.61 [0.45, 0.81], p=4.3×10 −4 ), but increased inpatient admission risk (OR 4.5 [2.3, 8.9], p=1.8×10 −5 ). We did not observe that prior use of angiotensin converting enzyme inhibitors or angiotensin receptor blockers increased the risk of testing positive for SARS-CoV-2, being admitted to the hospital, or having a severe outcome. This study involving direct EHR extraction identified known and less well-established demographics, and prior diagnoses and medications as risk factors for COVID-19 susceptibility and inpatient admission. Knowledge of these risk factors including marked ethnic disparities observed in disease severity should guide government policies, identify at-risk populations, inform clinical decision making, and prioritize future COVID-19 research.","journal":"medRxiv","year":2020,"id":118610,"datarank":2.401738533097667,"base_score":4.02535169073515,"endowment":4.02535169073515,"self_citation_contribution":0.6038027536102726,"citation_network_contribution":1.7979357794873942,"self_endowment_contribution":0.6038027536102726,"citer_contribution":1.7979357794873942,"corpus_percentile":null,"corpus_rank":null,"citation_count":55,"citer_count":55,"citers_with_citation_signal":42,"citers_with_endowment":42,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.945,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":551627,"name":"Yi Ding","orcid":"0000-0003-3595-2493","position":1,"is_corresponding":false},{"id":273433,"name":"Malika Freund","orcid":"0000-0002-3751-9274","position":2,"is_corresponding":false},{"id":273432,"name":"Ruth Johnson","orcid":"0000-0002-1929-0998","position":3,"is_corresponding":false},{"id":311855,"name":"Tommer Schwarz","orcid":"0000-0003-1777-3280","position":4,"is_corresponding":false},{"id":525628,"name":"Julie M. Yabu","orcid":"0000-0002-2819-4674","position":5,"is_corresponding":false},{"id":551628,"name":"Chad Hazlett","orcid":"0000-0003-1819-1928","position":6,"is_corresponding":false},{"id":308065,"name":"Jeffrey N. Chiang","orcid":"0000-0002-6843-1355","position":7,"is_corresponding":false},{"id":552917,"name":"Ami Wulf","orcid":null,"position":8,"is_corresponding":false},{"id":552918,"name":"UCLA Health Data Mart Working Group","orcid":null,"position":9,"is_corresponding":false},{"id":21398,"name":"Daniel H. Geschwind","orcid":"0000-0003-2896-3450","position":10,"is_corresponding":false},{"id":241305,"name":"Manish J. Butte","orcid":"0000-0002-4490-5595","position":11,"is_corresponding":false},{"id":731,"name":"Bogdan Paşaniuc","orcid":"0000-0002-0227-2056","position":12,"is_corresponding":false},{"id":281536,"name":"Timothy S. Chang","orcid":"0000-0002-9225-9874","position":0,"is_corresponding":true}],"reference_count":81,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:14:03.409507Z","pmid":"32637977","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}