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Risk for Non–AIDS-Defining and AIDS-Defining Cancer of Early Versus Delayed Initiation of Antiretroviral Therapy: A Multinational Prospective Cohort Study: Annals of Internal Medicine: Vol 174, No 6
Background: Immediate initiation of antiretroviral therapy (ART) regardless of CD4 cell count reduces risk for AIDS and non–AIDS-related events in asymptomatic, HIV-positive persons and is the standard of care. However, most HIV-positive persons initiate ART when their CD4 count decreases below 500 × 109 cells/L. Consequences of delayed ART on risk for non–AIDS-defining and AIDS-defining cancer, one of the most common reasons for death in HIV, are unclear. Objective: To estimate the long-term risk difference for cancer with the immediate ART strategy. Design: Multinational prospective cohort study. Setting: The D:A:D (Data collection on Adverse events of anti-HIV Drugs) study, which included HIV-positive persons from Europe, Australia, and the United States. Participants: 8318 HIV-positive persons with at least 1 measurement each of CD4 cell count and viral load while ART-naive (study period, 2006 to 2016). Measurements: The parametric g-formula was used, with adjustment for baseline and time-dependent confounders (CD4 cell count and viral load), to assess the 10-year risk for non–AIDS-defining and AIDS-defining cancer of immediate versus deferred (at CD4 counts <350 and <500 × 109 cells/L) ART initiation strategies. Results: During 64 021 person-years of follow-up, 231 cases of non–AIDS-defining cancer and 272 of AIDS-defining cancer occurred among HIV-positive persons with a median age of 36 years (interquartile range, 29 to 43 years). With immediate ART, the 10-year risk for non–AIDS-defining cancer was 2.97% (95% CI, 2.37% to 3.50%) and that for AIDS-defining cancer was 2.50% (CI, 2.37% to 3.38%). Compared with immediate ART initiation, the 10-year absolute risk differences when deferring ART to CD4 counts less than 500 × 109 cells/L and less than 350 × 109 cells/L were 0.12 percentage point (CI, −0.01 to 0.26 percentage point) and 0.29 percentage point (CI, −0.03 to 0.73 percentage point), respectively, for non–AIDS-defining cancer and 0.32 percentage point (CI, 0.21 to 0.44 percentage point) and 1.00 percentage point (CI, 0.67 to 1.44 percentage points), respectively, for AIDS-defining cancer. Limitation: Potential residual confounding due to observational study design. Conclusion: In this young cohort, effects of immediate ART on 10-year risk for cancer were small, and further supportive data are needed for non–AIDS-defining cancer. Primary Funding Source: Highly Active Antiretroviral Therapy Oversight Committee.
Surviving COVID-19 After Hospital Discharge: Symptom, Functional, and Adverse Outcomes of Home Health Recipients
Background: Little is known about recovery from coronavirus disease 2019 (COVID-19) after hospital discharge. Objective: To describe the home health recovery of patients with COVID-19 and risk factors associated with rehospitalization or death. Design: Retrospective observational cohort. Setting: New York City. Participants: 1409 patients with COVID-19 admitted to home health care (HHC) between 1 April and 15 June 2020 after hospitalization. Measurements: Covariates and outcomes were obtained from the mandated OASIS (Outcome and Assessment Information Set). Cox proportional hazards models were used to estimate the hazard ratio (HR) of risk factors associated with rehospitalization or death. Results: After an average of 32 days in HHC, 94% of patients were discharged and most achieved statistically significant improvements in symptoms and function. Activity-of-daily-living dependencies decreased from an average of 6 (95% CI, 5.9 to 6.1) to 1.2 (CI, 1.1 to 1.3). Risk for rehospitalization or death was higher for male patients (HR, 1.45 [CI, 1.04 to 2.03]); White patients (HR, 1.74 [CI, 1.22 to 2.47]); and patients with heart failure (HR, 2.12 [CI, 1.41 to 3.19]), diabetes with complications (HR, 1.71 [CI, 1.17 to 2.52]), 2 or more emergency department visits in the past 6 months (HR, 1.78 [CI, 1.21 to 2.62]), pain daily or all the time (HR, 1.46 [CI, 1.05 to 2.05]), cognitive impairment (HR, 1.49 [CI, 1.04 to 2.13]), or functional dependencies (HR, 1.09 [CI, 1.00 to 1.20]). Eleven patients (1%) died, 137 (10%) were rehospitalized, and 23 (2%) remain on service. Limitations: Care was provided by 1 home health agency. Information on rehospitalization and death after HHC discharge is not available. Conclusion: Symptom burden and functional dependence were common at the time of HHC admission but improved for most patients. Comorbid conditions of heart failure and diabetes, as well as characteristics present at admission, identified patients at greatest risk for an adverse event. Primary Funding Source: No direct funding.
Treatment Patterns and Clinical Outcomes After the Introduction of the Medicare Sepsis Performance Measure (SEP-1)
Background: Medicare requires that hospitals report on their adherence to the Severe Sepsis and Septic Shock Early Management Bundle (SEP-1). Objective: To evaluate the effect of SEP-1 on treatment patterns and patient outcomes. Design: Longitudinal study of hospitals using repeated cross-sectional cohorts of patients. Setting: 11 hospitals within an integrated health system. Patients: 54 225 encounters between January 2013 and December 2017 for adults with sepsis who were hospitalized through the emergency department. Intervention: Onset of the SEP-1 reporting requirement in October 2015. Measurements: Changes in SEP-1–targeted processes, including antibiotic administration, lactate measurement, and fluid administration at 3 hours from sepsis onset; repeated lactate and vasopressor administration for hypotension within 6 hours of sepsis onset; and sepsis outcomes, including risk-adjusted intensive care unit (ICU) admission, in-hospital mortality, and home discharge among survivors. Results: Two years after its implementation, SEP-1 was associated with variable changes in process measures, with the greatest effect being an increase in lactate measurement within 3 hours of sepsis onset (absolute increase, 23.7 percentage points [95% CI, 20.7 to 26.7 percentage points]; P < 0.001). There were small increases in antibiotic administration (absolute increase, 4.7 percentage points [CI, 1.9 to 7.6 percentage points]; P = 0.001) and fluid administration of 30 mL/kg of body weight within 3 hours of sepsis onset (absolute increase, 3.4 percentage points [CI, 1.5 to 5.2 percentage points]; P < 0.001). There was no change in vasopressor administration. There was a small increase in ICU admissions (absolute increase, 2.0 percentage points [CI, 0 to 4.0 percentage points]; P = 0.055) and no changes in mortality (absolute change, 0.1 percentage points [CI, −0.9 to 1.1 percentage points]; P = 0.87) or discharge to home. Limitation: Data are from a single health system. Conclusion: Implementation of the SEP-1 mandatory reporting program was associated with variable changes in process measures, without improvements in clinical outcomes. Revising the measure may optimize its future effect. Primary Funding Source: Agency for Healthcare Research and Quality.
Effect of Timing of and Adherence to Social Distancing Measures on COVID-19 Burden in the United States: A Simulation Modeling Approach: Annals of Internal Medicine: Vol 174, No 1
Background: Across the United States, various social distancing measures were implemented to control the spread of coronavirus disease 2019 (COVID-19). However, the effectiveness of such measures for specific regions with varying population demographic characteristics and different levels of adherence to social distancing is uncertain. Objective: To determine the effect of social distancing measures in unique regions. Design: An agent-based simulation model. Setting: Agent-based model applied to Dane County, Wisconsin; the Milwaukee metropolitan (metro) area; and New York City (NYC). Patients: Synthetic population at different ages. Intervention: Different times for implementing and easing social distancing measures at different levels of adherence. Measurements: The model represented the social network and interactions among persons in a region, considering population demographic characteristics, limited testing availability, “imported” infections, asymptomatic disease transmission, and age-specific adherence to social distancing measures. The primary outcome was the total number of confirmed COVID-19 cases. Results: The timing of and adherence to social distancing had a major effect on COVID-19 occurrence. In NYC, implementing social distancing measures 1 week earlier would have reduced the total number of confirmed cases from 203 261 to 41 366 as of 31 May 2020, whereas a 1-week delay could have increased the number of confirmed cases to 1 407 600. A delay in implementation had a differential effect on the number of cases in the Milwaukee metro area versus Dane County, indicating that the effect of social distancing measures varies even within the same state. Limitation: The effect of weather conditions on transmission dynamics was not considered. Conclusion: The timing of implementing and easing social distancing measures has major effects on the number of COVID-19 cases. Primary Funding Source: National Institute of Allergy and Infectious Diseases.
Insights From Rapid Deployment of a “Virtual Hospital” as Standard Care During the COVID-19 Pandemic
Background: Pandemics disrupt traditional health care operations by overwhelming system resource capacity but also create opportunities for care innovation. Objective: To describe the development and rapid deployment of a virtual hospital program, Atrium Health hospital at home (AH-HaH), within a large health care system. Design: Prospective case series. Setting: Atrium Health, a large integrated health care organization in the southeastern United States. Patients: 1477 patients diagnosed with coronavirus disease 2019 (COVID-19) from 23 March to 7 May 2020 who received care via AH-HaH. Intervention: A virtual hospital model providing proactive home monitoring and hospital-level care through a virtual observation unit (VOU) and a virtual acute care unit (VACU) in the home setting for eligible patients with COVID-19. Measurements: Patient demographic characteristics, comorbid conditions, treatments administered (intravenous fluids, antibiotics, supplemental oxygen, and respiratory medications), transfer to inpatient care, and hospital outcomes (length of stay, intensive care unit [ICU] admission, mechanical ventilation, and death) were collected from electronic health record data. Results: 1477 patients received care in either the AH-HaH VOU or VACU or both settings, with a median length of stay of 11 days. Of these, 1293 (88%) patients received care in the VOU only, with 40 (3%) requiring inpatient hospitalization. Of these 40 patients, 16 (40%) spent time in the ICU, 7 (18%) required ventilator support, and 2 (5%) died during their hospital admission. In total, 184 (12%) patients were ever admitted to the VACU, during which 21 patients (11%) required intravenous fluids, 16 (9%) received antibiotics, 40 (22%) required respiratory inhaler or nebulizer treatments, 41 (22%) used supplemental oxygen, and 24 (13%) were admitted as an inpatient to a conventional hospital. Of these 24 patients, 10 (42%) required ICU admission, 1 (3%) required a ventilator, and none died during their hospital admission. Limitation: Generalizability is limited to patients with a working telephone and the ability to comply with the monitoring protocols. Conclusion: Virtual hospital programs have the potential to provide health systems with additional inpatient capacity during the COVID-19 pandemic and beyond. Primary Funding Source: Atrium Health.
How to Safely Reopen Colleges and Universities During COVID-19: Experiences From Taiwan
Reopening colleges and universities during the coronavirus disease 2019 (COVID-19) pandemic poses a special challenge worldwide. Taiwan is one of the few countries where schools are functioning normally. To secure the safety of students and staff, the Ministry of Education in Taiwan established general guidelines for college campuses. The guidelines delineated creation of a task force at each university; school-based risk screening based on travel history, occupation, contacts, and clusters; measures on self-management of health and quarantine; general hygiene measures (including wearing masks indoors); principles on ventilation and sanitization; regulations on school assemblies; a process for reporting suspected cases; and policies on school closing and make-up classes. It also announced that a class should be suspended if 1 student or staff member in it tested positive and that a school should be closed for 14 days if it had 2 or more confirmed cases. As of 18 June 2020, there have been 7 confirmed cases in 6 Taiwanese universities since the start of the pandemic. One university was temporarily closed, adopted virtual classes, and quickly reopened after 14 days of contact tracing and quarantine of possible contacts. Taiwan's experience suggests that, under certain circumstances, safely reopening colleges and universities this fall may be feasible with a combination of strategies that include containment (access control with contact tracing and quarantine) and mitigation (hygiene, sanitation, ventilation, and social distancing) practices.