Cross-Cutting Lessons Learned During the COVID-19 Pandemic-the Walter Reed Army Institute of Research Experience.

INTRODUCTION: At the start of the coronavirus disease 2019 (COVID-19) pandemic, Walter Reed Army Institute of Research (WRAIR) mobilized to rapidly conduct medical research to detect, prevent, and treat the disease in order to minimize the impact of the pandemic on the health and readiness of U.S. Forces. WRAIR's major efforts included the development of the Department of Defense (DoD) COVID-19 vaccine candidate, researching novel drug therapies and monoclonal antibodies, refining and scaling-up diagnostic capabilities, evaluating the impact of viral diversity, assessing the behavioral health of Soldiers, supporting U.S. DoD operational forces overseas, and providing myriad assistance to allied nations. WRAIR personnel have also filled key roles within the whole of government response to the pandemic. WRAIR had to overcome major pandemic-related operational challenges in order to quickly execute a multimillion-dollar portfolio of COVID-19 research. Consequently, the organization learned lessons that could benefit other leaders of medical research organizations preparing for the next pandemic. MATERIALS AND METHODS: We identified lessons learned using a qualitative thematic analysis of 76 observation/recommendation pairs from across the organization. These lessons learned were organized under the Army's four pillars of readiness (staffing, training, equipping, and leadership development). To this framework, we added organizing and leading to best capture our experiences within the context of pandemic response. RESULTS: The major lessons learned for organizing were: (1) the pandemic created a need to rapidly pivot to new scientific priorities; (2) necessary health and safety precautions disrupted the flow of normal science and put programs at risk of missing milestones; (3) relationships with partners and allies facilitated medical diplomacy and advancement of U.S. national military and economic goals; and (4) a successful response required interoperability within and across multiple organizations. For equipping: (1) existing infrastructure lacked sufficient capacity and technical capability to allow immediate countermeasure development; (2) critical supply chains were strained; and (3) critical information system function and capacity were suddenly insufficient under maximum remote work. For staffing and training: (1) successful telework required rapid shifts in management, engagement, and accountability methods; and (2) organizational policies and processes had to adapt quickly to support remote staffing. For leading and leadership development (1) engaged, hopeful, and empathetic leadership made a difference; and (2) the workforce benefitted from concerted leadership communication that created a shared understanding of shifting priorities as well as new processes and procedures. CONCLUSIONS: An effective pandemic response requires comprehensive institutional preparedness that facilitates flexibility and surge capacity. The single most important action leaders of medical research organizations can take to prepare for the next pandemic is to develop a quick-reaction force that would activate under prespecified criteria to manage reprioritization of all science and support activities to address pandemic response priorities at the velocity of relevance.

Supervised Machine Learning Approach to Identify Early Predictors of Poor Outcome in Patients with COVID-19 Presenting to a Large Quaternary Care Hospital in New York City.

BACKGROUND: The progression of clinical manifestations in patients with coronavirus disease 2019 (COVID-19) highlights the need to account for symptom duration at the time of hospital presentation in decision-making algorithms. METHODS: We performed a nested case-control analysis of 4103 adult patients with COVID-19 and at least 28 days of follow-up who presented to a New York City medical center. Multivariable logistic regression and classification and regression tree (CART) analysis were used to identify predictors of poor outcome. RESULTS: Patients presenting to the hospital earlier in their disease course were older, had more comorbidities, and a greater proportion decompensated (<4 days, 41%; 4-8 days, 31%; >8 days, 26%). The first recorded oxygen delivery method was the most important predictor of decompensation overall in CART analysis. In patients with symptoms for <4, 4-8, and >8 days, requiring at least non-rebreather, age ≥ 63 years, and neutrophil/lymphocyte ratio ≥ 5.1; requiring at least non-rebreather, IL-6 ≥ 24.7 pg/mL, and D-dimer ≥ 2.4 µg/mL; and IL-6 ≥ 64.3 pg/mL, requiring non-rebreather, and CRP ≥ 152.5 mg/mL in predictive models were independently associated with poor outcome, respectively. CONCLUSION: Symptom duration in tandem with initial clinical and laboratory markers can be used to identify patients with COVID-19 at increased risk for poor outcomes.

Clinical Characteristics and Outcomes in People Living With Human Immunodeficiency Virus Hospitalized for Coronavirus Disease 2019.

We describe the characteristics of 31 people living with human immunodeficiency virus hospitalized for severe acute respiratory syndrome coronavirus 2 infection. All patients were on antiretroviral therapy and virologically suppressed at the time of admission. Clinical course and outcomes were similar to those reported in other hospitalized cohorts.

Pretest Symptom Duration and Cycle Threshold Values for Severe Acute Respiratory Syndrome Coronavirus 2 Reverse-Transcription Polymerase Chain Reaction Predict Coronavirus Disease 2019 Mortality.

BACKGROUND: The relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and patient symptom duration in both in- and outpatients, and the impact of these factors on patient outcomes, are currently unknown. Understanding these associations is important to clinicians caring for patients with coronavirus disease 2019 (COVID-19). METHODS: We conducted an observational study between March 10 and May 30, 2020 at a large quaternary academic medical center in New York City. Patient characteristics, laboratory values, and clinical outcomes were abstracted from the electronic medical records. Of all patients tested for SARS-CoV-2 during this time (N = 16 384), there were 5467 patients with positive tests, 4254 of which had available cycle threshold (Ct) values and were included in further analysis. Univariable and multivariable logistic regression models were used to test associations between Ct values, duration of symptoms before testing, patient characteristics, and mortality. The primary outcome is defined as death or discharge to hospice. RESULTS: Lower Ct values at diagnosis (ie, higher viral load) were associated with significantly higher mortality among both in- and outpatients. It is interesting to note that patients with a shorter time since the onset of symptoms to testing had a worse prognosis, with those presenting less than 3 days from symptom onset having 2-fold increased odds of death. After adjusting for time since symptom onset and other clinical covariates, Ct values remained a strong predictor of mortality. CONCLUSIONS: Severe acute respiratory syndrome coronavirus 2 reverse-transcription polymerase chain reaction Ct value and duration of symptoms are strongly associated with mortality. These 2 factors add useful information for clinicians to risk stratify patients presenting with COVID-19.

HIV-1 Infection Does Not Change Disease Course or Inflammatory Pattern of SARS-CoV-2-Infected Patients Presenting at a Large Urban Medical Center in New York City.

BACKGROUND: The clinical impact of coronavirus disease 2019 (COVID-19) among people with HIV (PWH) remains unclear. In this retrospective cohort study of COVID-19, we compared clinical outcomes and laboratory parameters among PWH and controls. METHODS: Sixty-eight PWH diagnosed with COVID-19 were matched 1:4 to patients without known HIV diagnosis, drawn from a study population of all patients who were diagnosed with COVID-19 at an academic urban hospital. The primary outcome was death/discharge to hospice within 30 days of hospital presentation. RESULTS: PWH were more likely to be admitted from the emergency department than patients without HIV (91% vs 71%; P = .001). We observed no statistically significant difference between admitted PWH and patients without HIV in terms of 30-day mortality rate (19% vs 13%, respectively) or mechanical ventilation rate (18% vs 20%, respectively). PWH had higher erythrocyte sedimentation rates than controls on admission but did not differ in other inflammatory marker levels or nasopharyngeal/oropharyngeal severe acute respiratory syndrome coronavirus 2 viral load estimated by reverse transcriptase polymerase chain reaction cycle thresholds. CONCLUSIONS: HIV infection status was associated with a higher admission rate; however, among hospitalized patients, PWH did not differ from HIV-uninfected controls by rate of mechanical ventilation or death/discharge to hospice.