Use of a Telemedicine Risk Assessment Tool to Predict the Risk of Hospitalization of 496 Outpatients With COVID-19: Retrospective Analysis.

BACKGROUND: Risk assessment of patients with acute COVID-19 in a telemedicine context is not well described. In settings of large numbers of patients, a risk assessment tool may guide resource allocation not only for patient care but also for maximum health care and public health benefit. OBJECTIVE: The goal of this study was to determine whether a COVID-19 telemedicine risk assessment tool accurately predicts hospitalizations. METHODS: We conducted a retrospective study of a COVID-19 telemedicine home monitoring program serving health care workers and the community in Atlanta, Georgia, with enrollment from March 24 to May 26, 2020; the final call range was from March 27 to June 19, 2020. All patients were assessed by medical providers using an institutional COVID-19 risk assessment tool designating patients as Tier 1 (low risk for hospitalization), Tier 2 (intermediate risk for hospitalization), or Tier 3 (high risk for hospitalization). Patients were followed with regular telephone calls to an endpoint of improvement or hospitalization. Using survival analysis by Cox regression with days to hospitalization as the metric, we analyzed the performance of the risk tiers and explored individual patient factors associated with risk of hospitalization. RESULTS: Providers using the risk assessment rubric assigned 496 outpatients to tiers: Tier 1, 237 out of 496 (47.8%); Tier 2, 185 out of 496 (37.3%); and Tier 3, 74 out of 496 (14.9%). Subsequent hospitalizations numbered 3 out of 237 (1.3%) for Tier 1, 15 out of 185 (8.1%) for Tier 2, and 17 out of 74 (23%) for Tier 3. From a Cox regression model with age of 60 years or older, gender, and reported obesity as covariates, the adjusted hazard ratios for hospitalization using Tier 1 as reference were 3.74 (95% CI 1.06-13.27; P=.04) for Tier 2 and 10.87 (95% CI 3.09-38.27; P<.001) for Tier 3. CONCLUSIONS: A telemedicine risk assessment tool prospectively applied to an outpatient population with COVID-19 identified populations with low, intermediate, and high risk of hospitalization.

Associations between remote patient monitoring programme responsiveness and clinical outcomes for patients with COVID-19.

OBJECTIVE: To assess whether engagement in a COVID-19 remote patient monitoring (RPM) programme or telemedicine programme improves patient outcomes. METHODS: This is a retrospective cohort study analysing patient responsiveness to our RPM survey or telemedicine visits and outcomes during the COVID-19 pandemic. Daily text message surveys and telemedicine consultations were offered to all patients who tested positive for SARS-CoV-2 at our institutional screening centres. Survey respondents with alarm responses were contacted by a nurse. We assessed the relationship between virtual engagement (telemedicine or RPM survey response) and clinical outcomes using multivariable logistic regression. RESULTS: Between 10 July 2020 and 2 January 2021, 6822 patients tested positive, with 1230 (18%) responding to at least one survey. Compared with non-responders, responders were younger (49 vs 53 years) and more likely to be white (40% vs 33%) and female (65% vs 55%) and had fewer comorbidities. After adjustment, individuals who engaged virtually were less likely to experience an emergency department visit, hospital admission or intensive care unit-level care. CONCLUSION: Telemedicine and RPM programme engagement (vs no engagement) were associated with better outcomes, but this was likely due to differences in groups at baseline rather than the efficacy of our intervention alone.

Postacute Sequelae of SARS-CoV-2 Infection and Impact on Quality of Life 1-6 Months After Illness and Association With Initial Symptom Severity.

BACKGROUND: Individuals with coronavirus disease 2019 (COVID-19) may have persistent symptoms following their acute illness. The prevalence and predictors of these symptoms, termed postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; PASC), have not been fully described. METHODS: Participants discharged from an outpatient telemedicine program for COVID-19 were emailed a survey (1-6 months after discharge) about ongoing symptoms, acute illness severity, and quality of life. Standardized telemedicine notes from acute illness were used for covariates (comorbidities and provider-assessed symptom severity). Bivariate and multivariable analyses were performed to assess predictors of persistent symptoms. RESULTS: Two hundred ninety patients completed the survey, of whom 115 (39.7%) reported persistent symptoms including fatigue (n = 59, 20.3%), dyspnea on exertion (n = 41, 14.1%), and mental fog (n = 39, 13.5%), among others. The proportion of persistent symptoms did not differ based on duration since illness (<90 days: n = 32, 37.2%; vs >90 days: n = 80, 40.4%; P = .61). Predictors of persistent symptoms included provider-assessed moderate-severe illness (adjusted odds ratio [aOR], 3.24; 95% CI, 1.75-6.02), female sex (aOR, 1.99; 95% CI, 0.98-4.04; >90 days out: aOR, 2.24; 95% CI, 1.01-4.95), and middle age (aOR, 2.08; 95% CI, 1.07-4.03). Common symptoms associated with reports of worse physical health included weakness, fatigue, myalgias, and mental fog. CONCLUSIONS: Symptoms following acute COVID-19 are common and may be predicted by factors during the acute phase of illness. Fatigue and neuropsychiatric symptoms figured prominently. Select symptoms seem to be particularly associated with perceptions of physical health following COVID-19 and warrant specific attention on future studies of PASC.

Longitudinal analysis shows durable and broad immune memory after SARS-CoV-2 infection with persisting antibody responses and memory B and T cells.

Ending the COVID-19 pandemic will require long-lived immunity to SARS-CoV-2. Here, we evaluate 254 COVID-19 patients longitudinally up to 8 months and find durable broad-based immune responses. SARS-CoV-2 spike binding and neutralizing antibodies exhibit a bi-phasic decay with an extended half-life of >200 days suggesting the generation of longer-lived plasma cells. SARS-CoV-2 infection also boosts antibody titers to SARS-CoV-1 and common betacoronaviruses. In addition, spike-specific IgG+ memory B cells persist, which bodes well for a rapid antibody response upon virus re-exposure or vaccination. Virus-specific CD4+ and CD8+ T cells are polyfunctional and maintained with an estimated half-life of 200 days. Interestingly, CD4+ T cell responses equally target several SARS-CoV-2 proteins, whereas the CD8+ T cell responses preferentially target the nucleoprotein, highlighting the potential importance of including the nucleoprotein in future vaccines. Taken together, these results suggest that broad and effective immunity may persist long-term in recovered COVID-19 patients.

One-Stop Serum Assay Identifies COVID-19 Disease Severity and Vaccination Responses.

SARS-CoV-2 has caused over 100,000,000 cases and almost 2,500,000 deaths globally. Comprehensive assessment of the multifaceted antiviral Ab response is critical for diagnosis, differentiation of severity, and characterization of long-term immunity, especially as COVID-19 vaccines become available. Severe disease is associated with early, massive plasmablast responses. We developed a multiplex immunoassay from serum/plasma of acutely infected and convalescent COVID-19 patients and prepandemic and postpandemic healthy adults. We measured IgA, IgG, and/or IgM against SARS-CoV-2 nucleocapsid (N), spike domain 1 (S1), S1-receptor binding domain (RBD) and S1-N-terminal domain. For diagnosis, the combined [IgA + IgG + IgM] or IgG levels measured for N, S1, and S1-RBD yielded area under the curve values ≥0.90. Virus-specific Ig levels were higher in patients with severe/critical compared with mild/moderate infections. A strong prozone effect was observed in sera from severe/critical patients-a possible source of underestimated Ab concentrations in previous studies. Mild/moderate patients displayed a slower rise and lower peak in anti-N and anti-S1 IgG levels compared with severe/critical patients, but anti-RBD IgG and neutralization responses reached similar levels at 2-4 mo after symptom onset. Measurement of the Ab responses in sera from 18 COVID-19-vaccinated patients revealed specific responses for the S1-RBD Ag and none against the N protein. This highly sensitive, SARS-CoV-2-specific, multiplex immunoassay measures the magnitude, complexity, and kinetics of the Ab response and can distinguish serum Ab responses from natural SARS-CoV-2 infections (mild or severe) and mRNA COVID-19 vaccines.

A Survey of Provider-Reported Use and Perceived Effectiveness of Medications for Symptom Management in Telemedicine and Outpatient Visits for Mild COVID-19.

INTRODUCTION: Many patients with mild coronavirus disease 2019 (COVID-19) have symptoms requiring acute and follow-up care. The aims of this study were to assess (1) provider-reported use of medications and their perceived effectiveness and (2) degree of difficulty managing specific symptoms at episodic COVID-19 care sites and in a longitudinal monitoring program. METHODS: We sent an online survey to physicians, advanced practice providers, and registered nurses redeployed to COVID-19 care sites at an academic medical center from March to May 2020. We asked about the use of medications and perceived effectiveness of medications to treat symptoms of COVID-19 and the perceived challenge of symptom management. Comparison was made by provider type (episodic or longitudinal site of care). RESULTS: Responses from 64 providers were included. The most frequently used medications were acetaminophen (87.1% of respondents), benzonatate (83.9%), and albuterol metered dose inhalers (MDI) (80.6%). Therapies for lower respiratory tract symptoms were reported as more commonly used by longitudinal follow-up providers compared to episodic providers including guaifenesin (90.6% vs 60.0%, p = 0.007), benzonatate (93.8% vs 73.3%, p = 0.04), nebulized albuterol for patients with asthma (75.0% vs 43.3%, p = 0.019), and albuterol MDIs for patients without asthma (90.6% vs 66.7%, p = 0.029). Medications found to have the highest perceived efficacy by respondents using the therapy (> 80% reporting "very efficacious") included albuterol, acetaminophen for fever, non-sedating antihistamines, nasal steroid spray, and non-steroidal anti-inflammatory drugs (NSAIDs) for myalgia, arthralgia, or headache. Lower respiratory symptoms and anxiety were rated as the most challenging symptoms to manage. CONCLUSIONS: Providers reported that clinical care of mild COVID-19 with medications in common use for other respiratory infections is effective, both at episodic care and longitudinal sites of care, but that specific symptoms are still challenging to manage.

Infection- and vaccine-induced antibody binding and neutralization of the B.1.351 SARS-CoV-2 variant.

The emergence of SARS-CoV-2 variants with mutations in the spike protein is raising concerns about the efficacy of infection- or vaccine-induced antibodies. We compared antibody binding and live virus neutralization of sera from naturally infected and Moderna-vaccinated individuals against two SARS-CoV-2 variants: B.1 containing the spike mutation D614G and the emerging B.1.351 variant containing additional spike mutations and deletions. Sera from acutely infected and convalescent COVID-19 patients exhibited a 3-fold reduction in binding antibody titers to the B.1.351 variant receptor-binding domain of the spike protein and a 3.5-fold reduction in neutralizing antibody titers against SARS-CoV-2 B.1.351 variant compared to the B.1 variant. Similar results were seen with sera from Moderna-vaccinated individuals. Despite reduced antibody titers against the B.1.351 variant, sera from infected and vaccinated individuals containing polyclonal antibodies to the spike protein could still neutralize SARS-CoV-2 B.1.351, suggesting that protective humoral immunity may be retained against this variant.

Description of symptom course in a telemedicine monitoring clinic for acute symptomatic COVID-19: a retrospective cohort study.

OBJECTIVE: Describe the disease course in a cohort of outpatients with COVID-19 and evaluate factors predicting duration of symptoms. DESIGN: Retrospective cohort study. SETTING: Telemedicine clinic at a large medical system in Atlanta, Georgia. PARTICIPANTS: 337 patients with acute COVID-19. Exclusion criteria included intake visit more than 10 days after symptom onset and hospitalisation prior to intake visit. MAIN OUTCOME MEASURES: Symptom duration in days. RESULTS: Common symptoms at intake visit are upper respiratory (73% cough, 55% loss of smell or taste, 57% sinus congestion, 32% sore throat) and systemic (66% headache, 64% body aches, 53% chills, 30% dizziness, 36% fever). Day of symptom onset was earliest for systemic and upper respiratory symptoms (median onset day 1 for both), followed by lower respiratory symptoms (day 3, 95% CI 2 to 4), with later onset of gastrointestinal symptoms (day 4, 95% CI 3 to 5), when present. Cough had the longest duration when present with median 17 days (95% CI 15 to 21), with 42% not resolved at final visit. Loss of smell or taste had the second longest duration with 14 days (95% CI 12 to 17), with 38% not resolved at final visit. Initial symptom severity is a significant predictor of symptom duration (p<0.01 for multiple symptoms). CONCLUSIONS: COVID-19 illness in outpatients follows a pattern of progression from systemic symptoms to lower respiratory symptoms and persistent symptoms are common across categories. Initial symptom severity is a significant predictor of disease duration for most considered symptoms.

Prolonged Symptoms After COVID-19 Infection in Outpatients.

We review 127 encounters for polymerase chain reaction-confirmed coronavirus disease 2019 (COVID-19) infection at a multidisciplinary outpatient clinic. We describe the symptomatology, time course, exam, and radiographic findings in this population. Patients with COVID-19 can experience persistent symptoms, primarily respiratory in nature, which can be severe enough to warrant hospitalization.

Discharge characteristics and care transitions of hospitalized patients with COVID-19.

Little is known about the follow-up healthcare needs of patients hospitalized with coronavirus disease 2019 (COVID-19) after hospital discharge. Due to the unique circumstances of providing transitional care in a pandemic, post-discharge providers must adapt to specific needs and limitations identified for the care of COVID-19 patients. In this study, we conducted a retrospective chart review of all hospitalized COVID-19 patients discharged from an Emory Healthcare Hospital in Atlanta, GA from March 26 to April 21, 2020 to characterize their post-discharge care plans. A total of 310 patients were included in the study (median age 58, range: 23-99; 51.0% female; 69.0% African American). The most common presenting comorbidities were hypertension (200, 64.5%), obesity (BMI≥30) (138, 44.5%), and diabetes mellitus (112, 36.1%). The median length of hospitalization was 5 days (range: 0-33). Sixty-seven patients (21.6%) were admitted to the intensive care unit and 42 patients (13.5%) received invasive mechanical ventilation. The most common complications recorded at discharge were electrolyte abnormalities (124, 40.0%), acute kidney injury (86, 27.7%) and sepsis (55, 17.7%). The majority of patients were discharged directly home (281, 90.6%). Seventy-five patients (24.2%) required any home service including home health and home oxygen therapy. The most common follow-up need was an appointment with a primary care provider (258, 83.2%). Twenty-four patients (7.7%) had one or more visit to an ED after discharge and 16 patients (5.2%) were readmitted. To our knowledge, this is the first large study to report on post-discharge medical care for COVID-19 patients.

Characterization of Prolonged COVID-19 Symptoms in an Outpatient Telemedicine Clinic.

We identified patients with coronavirus disease 2019 in a telemedicine clinic who requested ongoing follow-up calls 6 weeks after symptom onset. In this group, respiratory symptoms are the most common complaints, asthma and lung disease are frequent comorbidities, and patients often have not returned to work or usual activity.

Non-hospitalized Adults with COVID-19 Differ Noticeably from Hospitalized Adults in Their Demographic, Clinical, and Social Characteristics.

The characteristics of patients with coronavirus disease 2019 (COVID-19) have primarily been described in hospitalized adults. Characterization of COVID-19 in ambulatory care is needed for a better understanding of its evolving epidemiology. Our aim is to provide a description of the demographics, comorbidities, clinical presentation, and social factors in confirmed SARS-CoV-2-positive non-hospitalized adults. We conducted a retrospective medical record review of 208 confirmed SARS-CoV-2-positive patients treated in a COVID-19 virtual outpatient management clinic established in an academic health system in Georgia. The mean age was 47.8 (range 21-88) and 69.2% were female. By race/ethnicity, 49.5% were non-Hispanic African American, 25.5% other/unknown, 22.6% non-Hispanic white, and 2.4% Hispanic. Nearly 70% had at least one preexisting medical condition. The most common presenting symptoms were cough (75.5%), loss of smell or taste (63%), headache (62%), and body aches (54.3%). Physician or advanced practice provider assessed symptom severity ranged from 51.9% mild, 30.3% moderate, and 1.4% severe. Only eight reported limitations to home care (3.8%), 55.3% had a caregiver available, and 93.3% reported initiating self-isolation. Care needs were met for 83.2%. Our results suggest the demographic and clinical characteristics of COVID-19 illness in non-hospitalized adults differ considerably from hospitalized patients and warrant greater awareness of risk among younger and healthier individuals and consideration of testing and recommending self-isolation for a wider spectrum of clinical symptoms by clinicians. Social factors may also influence the efficacy of preventive strategies and allocation of resources toward the SARS-CoV-2 pandemic.