3219 hospitalized patients with COVID-19 in Southeast Michigan: a retrospective case-cohort study
Methods
This study was conducted at an eight-hospital health system in Southeast Michigan. Southeast Michigan is the metro area of Detroit and is home to 4.5 million people, almost half of the population of the state of Michigan. Patients were included in the study if they tested positive for SARS-CoV-2 infection by nasopharyngeal PCR test and were admitted to one of the eight hospitals between 13 March 2020 and 29 April 2020. Data were collected retrospectively from the electronic health record (EHR) (Epic). Data collected included date of admission and discharge, patient demographics, home medications, common chronic medical conditions, inpatient medications received for the treatment of COVID-19, oxygen therapy, and status at the time of discharge from the hospital. Data were available for all patients during the study period. Patients who were still admitted at the end of the study period were not included in the data analysis.
Race and ethnicity were available by self-reported status in the EHR. While patients tend to live in suburban communities, while black patients tend to live in urban and poorer communities. Home medications of interest were assessed based on medication reconciliation by the attending physician at the time of admission. Inpatient medications of interest were obtained from the medication administration record. Chronic medical conditions assessed include diabetes mellitus, hypertension, heart failure, coronary artery disease, chronic kidney disease, obesity (body mass index ≥30), asthma, and chronic obstructive pulmonary disease. Documentation of these conditions in the medical history, problem list before admission, problem list during the admission or discharge diagnoses in the EHR was used to evaluate the presence of these conditions. Patients were grouped as living or deceased based on status at the time of discharge from the hospital.
To evaluate the change in risk of mortality during the study, three periods were created: pre-peak, peak, and post-peak hospital COVID-19 volume. These periods were from 13 March 2020 to 30 March 2020, from 31 March 2020 to 13 April 2020, and from 14 April 2020 to 29 April 2020. Peak was defined as the 2 weeks when the maximum number of patients were admitted to the hospital system with a diagnosis of COVID-19.
Results
A difference in the use of some treatment medications was noted in the pre-peak, peak, and post-peak periods. Specifically, hydroxychloroquine use decreased in the post-peak period but was still used in over 60% of patients. Similarly, azithromycin use decreased in the post-peak period to less than 35% compared with over 83% in the pre-peak and peak periods. A logistic regression model was used to estimate the OR of death when controlling for age, gender, race, current smoking, and chronic medical conditions. In this model, male patients had an increased odds of dying compared with female patients. The odds of dying were 1.04 for every increase in the year of age. There was no difference in mortality based on race. The presence of diabetes mellitus, heart failure, obesity, and chronic kidney disease resulted in increased odds of death, with chronic kidney disease having the highest effect. Hypertension, coronary artery disease, asthma, chronic obstructive pulmonary disease, and current smoking status were not associated with increased odds of dying.
