Characteristics and Risk Factors of Hospitalized and Nonhospitalized COVID-19 Patients, Atlanta, Georgia, USA, March-April 2020.

We compared the characteristics of hospitalized and nonhospitalized patients who had coronavirus disease in Atlanta, Georgia, USA. We found that risk for hospitalization increased with a patient's age and number of concurrent conditions. We also found a potential association between hospitalization and high hemoglobin A1c levels in persons with diabetes.

COVID-19 Clinical Phenotypes: Presentation and Temporal Progression of Disease in a Cohort of Hospitalized Adults in Georgia, United States.

BACKGROUND: The epidemiological features and outcomes of hospitalized adults with coronavirus disease 2019 (COVID-19) have been described; however, the temporal progression and medical complications of disease among hospitalized patients require further study. Detailed descriptions of the natural history of COVID-19 among hospitalized patients are paramount to optimize health care resource utilization, and the detection of different clinical phenotypes may allow tailored clinical management strategies. METHODS: This was a retrospective cohort study of 305 adult patients hospitalized with COVID-19 in 8 academic and community hospitals. Patient characteristics included demographics, comorbidities, medication use, medical complications, intensive care utilization, and longitudinal vital sign and laboratory test values. We examined laboratory and vital sign trends by mortality status and length of stay. To identify clinical phenotypes, we calculated Gower's dissimilarity matrix between each patient's clinical characteristics and clustered similar patients using the partitioning around medoids algorithm. RESULTS: One phenotype of 6 identified was characterized by high mortality (49%), older age, male sex, elevated inflammatory markers, high prevalence of cardiovascular disease, and shock. Patients with this severe phenotype had significantly elevated peak C-reactive protein creatinine, D-dimer, and white blood cell count and lower minimum lymphocyte count compared with other phenotypes (P < .01, all comparisons). CONCLUSIONS: Among a cohort of hospitalized adults, we identified a severe phenotype of COVID-19 based on the characteristics of its clinical course and poor prognosis. These findings need to be validated in other cohorts, as improved understanding of clinical phenotypes and risk factors for their development could help inform prognosis and tailored clinical management for COVID-19.

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

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.

Characteristics Associated with Hospitalization Among Patients with COVID-19 - Metropolitan Atlanta, Georgia, March-April 2020.

The first reported U.S. case of coronavirus disease 2019 (COVID-19) was detected in January 2020 (1). As of June 15, 2020, approximately 2 million cases and 115,000 COVID-19-associated deaths have been reported in the United States.* Reports of U.S. patients hospitalized with SARS-CoV-2 infection (the virus that causes COVID-19) describe high proportions of older, male, and black persons (2-4). Similarly, when comparing hospitalized patients with catchment area populations or nonhospitalized COVID-19 patients, high proportions have underlying conditions, including diabetes mellitus, hypertension, obesity, cardiovascular disease, chronic kidney disease, or chronic respiratory disease (3,4). For this report, data were abstracted from the medical records of 220 hospitalized and 311 nonhospitalized patients aged ≥18 years with laboratory-confirmed COVID-19 from six acute care hospitals and associated outpatient clinics in metropolitan Atlanta, Georgia. Multivariable analyses were performed to identify patient characteristics associated with hospitalization. The following characteristics were independently associated with hospitalization: age ≥65 years (adjusted odds ratio [aOR] = 3.4), black race (aOR = 3.2), having diabetes mellitus (aOR = 3.1), lack of insurance (aOR = 2.8), male sex (aOR = 2.4), smoking (aOR = 2.3), and obesity (aOR = 1.9). Infection with SARS-CoV-2 can lead to severe outcomes, including death, and measures to protect persons from infection, such as staying at home, social distancing (5), and awareness and management of underlying conditions should be emphasized for those at highest risk for hospitalization with COVID-19. Measures that prevent the spread of infection to others, such as wearing cloth face coverings (6), should be used whenever possible to protect groups at high risk. Potential barriers to the ability to adhere to these measures need to be addressed.

Characteristics and Clinical Outcomes of Adult Patients Hospitalized with COVID-19 - Georgia, March 2020.

SARS-CoV-2, the novel coronavirus that causes coronavirus disease 2019 (COVID-19), was first detected in the United States during January 2020 (1). Since then, >980,000 cases have been reported in the United States, including >55,000 associated deaths as of April 28, 2020 (2). Detailed data on demographic characteristics, underlying medical conditions, and clinical outcomes for persons hospitalized with COVID-19 are needed to inform prevention strategies and community-specific intervention messages. For this report, CDC, the Georgia Department of Public Health, and eight Georgia hospitals (seven in metropolitan Atlanta and one in southern Georgia) summarized medical record-abstracted data for hospitalized adult patients with laboratory-confirmed* COVID-19 who were admitted during March 2020. Among 305 hospitalized patients with COVID-19, 61.6% were aged <65 years, 50.5% were female, and 83.2% with known race/ethnicity were non-Hispanic black (black). Over a quarter of patients (26.2%) did not have conditions thought to put them at higher risk for severe disease, including being aged ≥65 years. The proportion of hospitalized patients who were black was higher than expected based on overall hospital admissions. In an adjusted time-to-event analysis, black patients were not more likely than were nonblack patients to receive invasive mechanical ventilation† (IMV) or to die during hospitalization (hazard ratio [HR] = 0.63; 95% confidence interval [CI] = 0.35-1.13). Given the overrepresentation of black patients within this hospitalized cohort, it is important for public health officials to ensure that prevention activities prioritize communities and racial/ethnic groups most affected by COVID-19. Clinicians and public officials should be aware that all adults, regardless of underlying conditions or age, are at risk for serious illness from COVID-19.

A retrospective study of the safety of intramuscular ziprasidone in agitated elderly patients.

OBJECTIVE: Authors evaluated the safety of intramuscular ziprasidone for use in acute agitation in an elderly population. METHOD: Medical records were reviewed retrospectively to identify consecutive patients who were admitted to our neuropsychiatry service with the presenting complaint of dementia (DSM-IV) with agitation and who were given intramuscular ziprasidone and then administered an electrocardiogram (ECG) (N = 23). Some patients also had a baseline ECG (N = 14). QTc intervals were recorded, and significance was defined as a QTc of > or =450 ms or a 10% prolongation from baseline. A paired-samples t test was performed to compare the baseline and postmedication QTc intervals. Confounding factors were examined, and cardiac events (torsades de pointes, cardiac arrest) were recorded. RESULTS: There was no significant difference in the QTc interval between the baseline and the post-ziprasidone values. One patient had a QTc greater than 500 ms and 25% over baseline, and therefore the medication was discontinued. The mean prolongation of the QTc interval was only 0.5 ms. There were no episodes of torsades de pointes. Other medications that the patients were taking did not appear to affect the QTc interval in an expected manner. CONCLUSION: Larger studies need to be done to evaluate the safety of intramuscular ziprasidone in agitated elderly patients, a population with an increased risk of QT prolongation and torsades de pointes because of their age, comorbid conditions, and concomitant use of multiple medications.