Predictors at Admission of Mechanical Ventilation and Death in an Observational Cohort of Adults Hospitalized With Coronavirus Disease 2019
| Autor: | Nadine Oosmanally, Robyn Neblett Fanfair, Christine M Szablewski, Robert Jansen, Priti R. Patel, Julie Hollberg, Cherie Drenzek, Beau B. Bruce, Deron C. Burton, Pavithra Natarajan, Frank W. Brown, Brendan R Jackson, Timothy M. Uyeki, Melissa Tobin-D'Angelo, Sean D Browning, David J. Murphy, Juliana Almeida da Silva, Sapna Bamrah Morris, David W. Wright, Stephanie R. Bialek, Karen K. Wong, Alfonso C Hernandez-Romieu, James M. Blum, John Rossow, Benjamin Lefkove, William M SeweSll, Jessica Rogers-Brown, Jeremy A W Gold, Jack Owens |
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| Rok vydání: | 2020 |
| Předmět: |
Microbiology (medical)
medicine.medical_specialty medicine.medical_treatment Vital signs Disease 030204 cardiovascular system & hematology Coronary artery disease 03 medical and health sciences 0302 clinical medicine Risk Factors Internal medicine Major Article angiotensin receptor antagonists medicine Humans 030212 general & internal medicine Aged Retrospective Studies Mechanical ventilation SARS-CoV-2 business.industry Medical record COVID-19 Odds ratio Middle Aged medicine.disease Respiration Artificial mortality United States Confidence interval Hospitalization AcademicSubjects/MED00290 Infectious Diseases Cohort business |
| Zdroj: | Clinical Infectious Diseases Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America |
| ISSN: | 1537-6591 1058-4838 |
| Popis: | Background Coronavirus disease (COVID-19) can cause severe illness and death. Predictors of poor outcome collected on hospital admission may inform clinical and public health decisions. Methods We conducted a retrospective observational cohort investigation of 297 adults admitted to 8 academic and community hospitals in Georgia, United States, during March 2020. Using standardized medical record abstraction, we collected data on predictors including admission demographics, underlying medical conditions, outpatient antihypertensive medications, recorded symptoms, vital signs, radiographic findings, and laboratory values. We used random forest models to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for predictors of invasive mechanical ventilation (IMV) and death. Results Compared with age Conclusions After adjustment for patient and clinical characteristics, older age was the strongest predictor of death, exceeding comorbidities, abnormal vital signs, and laboratory test abnormalities. That coronary artery disease, but not chronic lung disease, was associated with death among hospitalized patients warrants further investigation, as do associations between certain antihypertensive medications and death. |
| Databáze: | OpenAIRE |
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