Factors Associated With Severe Illness in Patients Aged <21 Years Hospitalized for COVID-19

OBJECTIVES

To describe coronavirus disease 2019 (COVID-19)-related pediatric hospitalizations during a period of B.1.617.2 (Δ) variant predominance and to determine age-specific factors associated with severe illness.

METHODS

We abstracted data from medical charts to conduct a cross-sectional study of patients aged <21 years hospitalized at 6 United States children's hospitals from July to August 2021 for COVID-19 or with an incidental positive severe acute respiratory syndrome coronavirus 2 test. Among patients with COVID-19, we assessed factors associated with severe illness by calculating age-stratified prevalence ratios (PR). We defined severe illness as receiving high-flow nasal cannula, positive airway pressure, or invasive mechanical ventilation.

RESULTS

Of 947 hospitalized patients, 759 (80.1%) had COVID-19, of whom 287 (37.8%) had severe illness. Factors associated with severe illness included coinfection with respiratory syncytial virus (RSV) (PR 3.64) and bacteria (PR 1.88) in infants; RSV coinfection in patients aged 1 to 4 years (PR 1.96); and obesity in patients aged 5 to 11 (PR 2.20) and 12 to 17 years (PR 2.48). Having ≥2 underlying medical conditions was associated with severe illness in patients aged <1 (PR 1.82), 5 to 11 (PR 3.72), and 12 to 17 years (PR 3.19).

CONCLUSIONS

Among patients hospitalized for COVID-19, factors associated with severe illness included RSV coinfection in those aged <5 years, obesity in those aged 5 to 17 years, and other underlying conditions for all age groups <18 years. These findings can inform pediatric practice, risk communication, and prevention strategies, including vaccination against COVID-19.

High-Risk Injection-Related Practices Associated with anti-HCV Positivity among Young Adults Seeking Services in Three Small Cities in Wisconsin

BACKGROUND

Hepatitis C virus (HCV) infection has been increasing among people who inject drugs (PWID), younger than 30 years, and living in rural or suburban areas. We examined injection-related behaviors of young PWID to determine factors associated with HCV infection.

METHODS

From September 2013-May 2015, respondent-driven and snowball sampling were used in 3 suburban areas of Wisconsin to recruit PWID 18-29 years who reported injection drug use in the previous 12 months. Participants were tested for HCV antibody (anti-HCV) and reported injection-related behaviors/practices via self-administered computer-based survey. We calculated anti-HCV prevalence and assessed associated factors using multivariable logistic regression.

RESULTS

Forty-two percent (117/280) of participants were male, 83% (231/280) were white, and median age was 23 years. Overall HCV prevalence was 33%, but HCV prevalence among males was 39%. Adjusting for age, sex, race/ethnicity, education, relationship status, insurance status and income, anti-HCV positivity was associated with higher injection frequency (> 100 times in the past six months) (aOR = 3.07; 95% Confidence Interval (95% CI): 1.72-5.45), ever shared syringes (aOR = 5.15; 95% CI: 2.52-10.51), past week/last use receptive rinse water sharing (aOR = 1.88; 95% CI: 1.06-3.33), past week/last use receptive filter sharing (aOR = 3.25; 95% CI: 1.61-6.54), reusing syringes (aOR = 1.91, 95% CI: 1.08-3.37), history of overdose (aOR = 8.82; 95% CI: 2.26-3.95), and having ever injected another PWID (aOR = 8.82; 95%CI 3.94-19.76).

DISCUSSION

Anti-HCV positivity is associated with high-risk injection practices. Young PWID would benefit from access to evidence-based interventions that reduce their risk of infection, link those infected to HCV treatment, and provide education to reduce further transmission.

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 COVID-19

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 eight 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 (CI) 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 (aOR 3.12, CI 1.47–6.60; aOR 2.79, CI 1.23–6.33) and the strongest predictors for death (aOR 12.92, CI 3.26–51.25; aOR 18.06, CI 4.43–73.63). Comorbidities associated with death (aORs from 2.4 to 3.8, p <0.05) included end-stage renal disease, coronary artery disease, and neurologic disorders, but not pulmonary disease, immunocompromise, or hypertension. Pre-hospital use vs. non-use of angiotensin receptor blockers (aOR 2.02, CI 1.03–3.96) and dihydropyridine calcium channel blockers (aOR 1.91, 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.