Characteristics of Adults Aged 18–49 Years Without Underlying Conditions Hospitalized With Laboratory-Confirmed Coronavirus Disease 2019 in the United States: COVID-NET—March–August 2020

Owusu, Daniel; Kim, Lindsay; Whitaker, Michael; Piasecki, Alexandra M; Reingold, Arthur; Alden, Nisha; Maslar, Amber; Anderson, Evan J.; Ryan, Patricia; Kim, Sue; Como‐Sabetti, Kathryn; Hancock, Emily B.; Muse, Alison; Bennett, Nancy M.; Billing, Laurie M; Sutton, Melissa; Talbot, H. Keipp; Ortega, Jake; Brammer, Lynnette; Fry, Alicia M.; Hall, Aron J.; Garg, Shikha; Cummings, Charisse N; Holstein, Rachel; Kambhampati, Anita; Meador, Seth; Wortham, Jonathan M.; Chai, Shua J.; Kawasaki, Breanna; Yousey‐Hindes, Kimberly; Openo, Kyle P.; Monroe, Maya; Reeg, Libby; Lynfield, Ruth; Eisenberg, Nancy; Barney, Grant; Felsen, Christina B.; Shiltz, Jessica; West, Nicole; Schaffner, William; Price, Andrea

doi:10.1093/cid/ciaa1806

Cited by 18 publications

(20 citation statements)

References 8 publications

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“…The study population for this analysis included individuals who tested positive for SARS-CoV-2 by real-time reverse transcription-polymerase chain reaction (RT-PCR), from 26 January 2020 to 15 January 2021. The outcome of interest was hospitalization (as a measure of COVID-19 severity), defined as hospital admission in a BC acute care facility within 14 days after a positive SARS-CoV-2 test [7][8][9]. Patients residing in long term care facilities were excluded from the analyses as their transfer to hospitals was variable over time and across local regions.…”

Section: Study Populationmentioning

confidence: 99%

“…et al, 2016 [15]. 8 Assessed via "lymphoma", "metastatic cancer" and "solid tumor without metastasis" ICD-9/ICD-10 codes from groups 18, 19 and 20 of Elixhauser Comorbidity Score in DAD, MSP and NACRS records. 1 Assessed via "lymphoma", "metastatic cancer" and "solid tumor without metastasis" ICD-9/ICD-10 codes from groups 18, 19 and 20 of Elixhauser Comorbidity Score in DAD, MSP and NACRS records.…”

Section: Chronic Comorbidities As Risk Factorsmentioning

confidence: 99%

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Mental Health and Substance Use Associated with Hospitalization among People with COVID-19: A Population-Based Cohort Study

García

Wilton

Smolina

et al. 2021

Viruses

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This study identified factors associated with hospital admission among people with laboratory-diagnosed COVID-19 cases in British Columbia. The study used data from the BC COVID-19 Cohort, which integrates data on all COVID-19 cases with data on hospitalizations, medical visits, emergency room visits, prescription drugs, chronic conditions and deaths. The analysis included all laboratory-diagnosed COVID-19 cases in British Columbia to 15 January 2021. We evaluated factors associated with hospital admission using multivariable Poisson regression analysis with robust error variance. Of the 56,874 COVID-19 cases included in the analysis, 2298 were hospitalized. Factors associated with increased hospitalization risk were as follows: male sex (adjusted risk ratio (aRR) = 1.27; 95% CI = 1.17–1.37), older age (p-trend < 0.0001 across age groups increasing hospitalization risk with increasing age [aRR 30–39 years = 3.06; 95% CI = 2.32–4.03, to aRR 80+ years = 43.68; 95% CI = 33.41–57.10 compared to 20–29 years-old]), asthma (aRR = 1.15; 95% CI = 1.04–1.26), cancer (aRR = 1.19; 95% CI = 1.09–1.29), chronic kidney disease (aRR = 1.32; 95% CI = 1.19–1.47), diabetes (treated without insulin aRR = 1.13; 95% CI = 1.03–1.25, requiring insulin aRR = 5.05; 95% CI = 4.43–5.76), hypertension (aRR = 1.19; 95% CI = 1.08–1.31), injection drug use (aRR = 2.51; 95% CI = 2.14–2.95), intellectual and developmental disabilities (aRR = 1.67; 95% CI = 1.05–2.66), problematic alcohol use (aRR = 1.63; 95% CI = 1.43–1.85), immunosuppression (aRR = 1.29; 95% CI = 1.09–1.53), and schizophrenia and psychotic disorders (aRR = 1.49; 95% CI = 1.23–1.82). In an analysis restricted to women of reproductive age, pregnancy (aRR = 2.69; 95% CI = 1.42–5.07) was associated with increased risk of hospital admission. Older age, male sex, substance use, intellectual and developmental disability, chronic comorbidities, and pregnancy increase the risk of COVID-19-related hospitalization.

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Section: Study Populationmentioning

confidence: 99%

Section: Chronic Comorbidities As Risk Factorsmentioning

confidence: 99%

Mental Health and Substance Use Associated with Hospitalization among People with COVID-19: A Population-Based Cohort Study

García

Wilton

Smolina

et al. 2021

Viruses

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“…The majority of people infected with SARS-CoV-2 have mild symptoms [ 2 ], but an estimated 20% to 30% experience a severe illness that requires hospitalization [ 2 , 3 ]. COVID-19 hospitalizations are associated with substantial patient morbidity and mortality and considerable healthcare resource use and costs.…”

Section: Introductionmentioning

confidence: 99%

Real-world treatment patterns and clinical outcomes for inpatients with COVID-19 in the US from September 2020 to February 2021

et al. 2021

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The objective of this retrospective cohort study was to describe pre-treatment characteristics, treatment patterns, health resource use, and clinical outcomes among adults hospitalized with COVID-19 in the United States (US) who initiated common treatments for COVID-19. The Optum® COVID-19 electronic health records database was used to identify patients >18 years, diagnosed with COVID-19, who were admitted to an inpatient setting and received treatments of interest for COVID-19 between September 2020 and January 2021. Patients were stratified into cohorts based on index treatment use. Patient demographics, medical history, care setting, medical procedures, subsequent treatment use, patient disposition, clinical improvement, and outcomes were summarized descriptively. Among a total of 26,192 patients identified, the most prevalent treatments initiated were dexamethasone (35.4%) and dexamethasone + remdesivir (14.9%), and dexamethasone was the most common subsequent treatment. At day 14 post-index, <10% of patients received any treatments of interest. Mean (standard deviation [SD]) patient age was 65.6 (15.6) years, and the most prevalent comorbidities included hypertension (44.8%), obesity (35.4%), and diabetes (25.7%). At the end of follow-up, patients had a mean (SD) 8.1 (6.6) inpatient days and 1.4 (4.1) days with ICU care. Oxygen supplementation, non-invasive, or invasive ventilation was required by 4.5%, 3.0%, and 3.1% of patients, respectively. At the end of follow-up, 84.2% of patients had evidence of clinical improvement, 3.1% remained hospitalized, 83.8% were discharged, 4% died in hospital, and 9.1% died after discharge. Although the majority of patients were discharged alive, no treatments appeared to alleviate the inpatient morbidity and mortality associated with COVID-19. This highlights an unmet need for effective treatment options for patients hospitalized with COVID-19.

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“…During this unprecedented global pandemic, the return of students to campus has been heavily contemplated by colleges nationwide. While younger adults with COVID-19 and no other underlying health conditions are at a minor risk of severe health outcomes, colleges nationwide are making maximum efforts to halt the spread of the disease [ 8 ]. College campuses have implemented numerous COVID-19 prevention practices, including an increased testing capacity and requirements for mask-wearing and physical distancing.…”

Section: Introductionmentioning

confidence: 99%

Monitoring Beliefs and Physiological Measures Using Wearable Sensors and Smartphone Technology Among Students at Risk of COVID-19: Protocol for a mHealth Study

Cislo¹,

Clingan²,

Gilley³

et al. 2021

JMIR Res Protoc

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Background The COVID-19 pandemic has significantly impacted lives and greatly affected the mental health and public safety of an already vulnerable population—college students. Social distancing and isolation measures have presented challenges to students’ mental health. mHealth apps and wearable sensors may help monitor students at risk of COVID-19 and support their mental well-being. Objective This study aimed to monitor students at risk of COVID-19 by using a wearable sensor and a smartphone-based survey. Methods We conducted a prospective study on undergraduate and graduate students at a public university in the Midwest United States. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal smartphone devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints: at baseline, 1 month later, 2 months later, 3 months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population. Results This study enrolled 2158 college students between September 2020 and January 2021. Subjects are currently being followed-up for 1 academic year. Data collection and analysis are currently underway. Conclusions This study examined student health and well-being during the COVID-19 pandemic and assessed the feasibility of using a wearable sensor and a survey in a college student population, which may inform the role of our mHealth tools in assessing student health and well-being. Finally, using data derived from a wearable sensor, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data toward the development of a model for the early prediction and detection of COVID-19. Trial Registration ClinicalTrials.gov NCT04766788; https://clinicaltrials.gov/ct2/show/NCT04766788 International Registered Report Identifier (IRRID) DERR1-10.2196/29561

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Characteristics of Adults Aged 18–49 Years Without Underlying Conditions Hospitalized With Laboratory-Confirmed Coronavirus Disease 2019 in the United States: COVID-NET—March–August 2020

Cited by 18 publications

References 8 publications

Mental Health and Substance Use Associated with Hospitalization among People with COVID-19: A Population-Based Cohort Study

Mental Health and Substance Use Associated with Hospitalization among People with COVID-19: A Population-Based Cohort Study

Real-world treatment patterns and clinical outcomes for inpatients with COVID-19 in the US from September 2020 to February 2021

Monitoring Beliefs and Physiological Measures Using Wearable Sensors and Smartphone Technology Among Students at Risk of COVID-19: Protocol for a mHealth Study

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