Predictors at Admission of Mechanical Ventilation and Death in an Observational Cohort of Adults Hospitalized With Coronavirus Disease 2019

Author:

Jackson Brendan R12,Gold Jeremy A W13,Natarajan Pavithra1,Rossow John123,Neblett Fanfair Robyn12,da Silva Juliana1,Wong Karen K12,Browning Sean D14,Bamrah Morris Sapna12,Rogers-Brown Jessica14,Hernandez-Romieu Alfonso C1235,Szablewski Christine M1236,Oosmanally Nadine6,Tobin-D’Angelo Melissa6,Drenzek Cherie6,Murphy David J5,Hollberg Julie5,Blum James M57,Jansen Robert8,Wright David W58,Sewell William M9,Owens Jack D9,Lefkove Benjamin10,Brown Frank W510,Burton Deron C12,Uyeki Timothy M12,Bialek Stephanie R12,Patel Priti R12,Bruce Beau B1

Affiliation:

1. COVID-19 Emergency Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

2. United States Public Health Service, Atlanta, GA, USA

3. Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

4. Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA

5. Emory University School of Medicine, Atlanta, Georgia, USA

6. Georgia Department of Public Health, Atlanta, Georgia, USA

7. Georgia Clinical and Translational Science Alliance, Atlanta, Georgia, USA

8. Grady Health System, Atlanta, Georgia, USA

9. Phoebe Putney Memorial Hospital, Albany, Georgia, USA

10. Emory Decatur Hospital, Decatur, Georgia, USA

Abstract

Abstract 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 <45 years, ages 65–74 years and ≥75 years were predictors of IMV (aORs, 3.12 [95% CI, 1.47–6.60] and 2.79 [95% CI, 1.23–6.33], respectively) and the strongest predictors for death (aORs, 12.92 [95% CI, 3.26–51.25] and 18.06 [95% CI, 4.43–73.63], respectively). Comorbidities associated with death (aORs, 2.4–3.8; P < .05) included end-stage renal disease, coronary artery disease, and neurologic disorders, but not pulmonary disease, immunocompromise, or hypertension. Prehospital use vs nonuse of angiotensin receptor blockers (aOR, 2.02 [95% CI, 1.03–3.96]) and dihydropyridine calcium channel blockers (aOR, 1.91 [95% CI, 1.03–3.55]) were associated with death. 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.

Funder

Centers for Disease Control and Prevention

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

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