Serum Sodium, Patient Symptoms, and Clinical Outcomes in Hospitalized Patients with COVID-19.

INTRODUCTION: Disorders of serum sodium (SNa) are common in hospitalized patients with COVID-19 and may reflect underlying disease severity. However, the association of SNa with patient-reported outcomes is not clear. METHODS: The Brigham and Women's Hospital COVID-19 Registry is a prospective cohort study of consecutively admitted adult patients with confirmed SARS-CoV-2 infection (n = 809). We examined the associations of SNa (continuous and tertiles) on admission with: (1) patient symptoms obtained from detailed chart review; and (2) in-hospital mortality, length of stay, and intensive care unit (ICU) admission using unadjusted and adjusted logistic regression models. Covariates included demographic data and comorbidities. RESULTS: Mean age was 60 years, 48% were male, and 35% had diabetes. The most frequent symptoms were cough (64%), fever (60%), and shortness of breath (56%). In adjusted models, higher SNa (per mmol/L) was associated with lower odds of GI symptoms (OR 0.96; 95% CI 0.92-0.99), higher odds of confusion (OR 1.08; 95% CI 1.04-1.13), in-hospital mortality (OR 1.06; 95% CI 1.02-1.11), and ICU admission (OR 1.09; 95% CI 1.05-1.13). The highest sodium tertile (compared with the middle tertile) showed similar associations, in addition to lower odds of either anosmia or ageusia (OR 0.30; 95% CI 0.12-0.74). CONCLUSION: In this prospective cohort study of hospitalized patients with COVID-19, hypernatremia was associated with higher odds of confusion and in-hospital mortality. These findings may aid providers in identifying high-risk patients who warrant closer attention, thereby furthering patient-centered approaches to care.

Feasibility and lessons learned on remote trial implementation from TestBoston, a fully remote, longitudinal, large-scale COVID-19 surveillance study.

Longitudinal clinical studies traditionally require in-person study visits which are well documented to pose barriers to participation and contribute challenges to enrolling representative samples. Remote trial models may reduce barriers to research engagement, improve retention, and reach a more representative cohort. As remote trials become more common following the COVID-19 pandemic, a critical evaluation of this approach is imperative to optimize this paradigm shift in research. The TestBoston study was launched to understand prevalence and risk factors for COVID-19 infection in the greater Boston area through a fully remote home-testing model. Participants (adults, within 45 miles of Boston, MA) were recruited remotely from patient registries at Brigham and Women's Hospital and the general public. Participants were provided with monthly and "on-demand" at-home SARS-CoV-2 RT-PCR and antibody testing using nasal swab and dried blood spot self-collection kits and electronic surveys to assess symptoms and risk factors for COVID-19 via an online dashboard. Between October 2020 and January 2021, we enrolled 10,289 participants reflective of Massachusetts census data. Mean age was 47 years (range 18-93), 5855 (56.9%) were assigned female sex at birth, 7181(69.8%) reported being White non-Hispanic, 952 (9.3%) Hispanic/Latinx, 925 (9.0%) Black, 889 (8.6%) Asian, and 342 (3.3%) other and/or more than one race. Lower initial enrollment among Black and Hispanic/Latinx individuals required an adaptive approach to recruitment, leveraging connections to the medical system, coupled with community partnerships to ensure a representative cohort. Longitudinal retention was higher among participants who were White non-Hispanic, older, working remotely, and with lower socioeconomic vulnerability. Implementation highlighted key differences in remote trial models as participants independently navigate study milestones, requiring a dedicated participant support team and robust technology platforms, to reduce barriers to enrollment, promote retention, and ensure scientific rigor and data quality. Remote clinical trial models offer tremendous potential to engage representative cohorts, scale biomedical research, and promote accessibility by reducing barriers common in traditional trial design. Barriers and burdens within remote trials may be experienced disproportionately across demographic groups. To maximize engagement and retention, researchers should prioritize intensive participant support, investment in technologic infrastructure and an adaptive approach to maximize engagement and retention.