Characteristics and outcomes of COVID-19 patients in New York City's public hospital system.

BACKGROUND: New York City (NYC) bore the greatest burden of COVID-19 in the United States early in the pandemic. In this case series, we describe characteristics and outcomes of racially and ethnically diverse patients tested for and hospitalized with COVID-19 in New York City's public hospital system. METHODS: We reviewed the electronic health records of all patients who received a SARS-CoV-2 test between March 5 and April 9, 2020, with follow up through April 16, 2020. The primary outcomes were a positive test, hospitalization, and death. Demographics and comorbidities were also assessed. RESULTS: 22254 patients were tested for SARS-CoV-2. 13442 (61%) were positive; among those, the median age was 52.7 years (interquartile range [IQR] 39.5-64.5), 7481 (56%) were male, 3518 (26%) were Black, and 4593 (34%) were Hispanic. Nearly half (4669, 46%) had at least one chronic disease (27% diabetes, 30% hypertension, and 21% cardiovascular disease). Of those testing positive, 6248 (46%) were hospitalized. The median age was 61.6 years (IQR 49.7-72.9); 3851 (62%) were male, 1950 (31%) were Black, and 2102 (34%) were Hispanic. More than half (3269, 53%) had at least one chronic disease (33% diabetes, 37% hypertension, 24% cardiovascular disease, 11% chronic kidney disease). 1724 (28%) hospitalized patients died. The median age was 71.0 years (IQR 60.0, 80.9); 1087 (63%) were male, 506 (29%) were Black, and 528 (31%) were Hispanic. Chronic diseases were common (35% diabetes, 37% hypertension, 28% cardiovascular disease, 15% chronic kidney disease). Male sex, older age, diabetes, cardiac history, and chronic kidney disease were significantly associated with testing positive, hospitalization, and death. Racial/ethnic disparities were observed across all outcomes. CONCLUSIONS AND RELEVANCE: This is the largest and most racially/ethnically diverse case series of patients tested and hospitalized for COVID-19 in New York City to date. Our findings highlight disparities in outcomes that can inform prevention and testing recommendations.

Rapid prediction of in-hospital mortality among adults with COVID-19 disease.

BACKGROUND: We developed a simple tool to estimate the probability of dying from acute COVID-19 illness only with readily available assessments at initial admission. METHODS: This retrospective study included 13,190 racially and ethnically diverse adults admitted to one of the New York City Health + Hospitals (NYC H+H) system for COVID-19 illness between March 1 and June 30, 2020. Demographic characteristics, simple vital signs and routine clinical laboratory tests were collected from the electronic medical records. A clinical prediction model to estimate the risk of dying during the hospitalization were developed. RESULTS: Mean age (interquartile range) was 58 (45-72) years; 5421 (41%) were women, 5258 were Latinx (40%), 3805 Black (29%), 1168 White (9%), and 2959 Other (22%). During hospitalization, 2,875 were (22%) died. Using separate test and validation samples, machine learning (Gradient Boosted Decision Trees) identified eight variables-oxygen saturation, respiratory rate, systolic and diastolic blood pressures, pulse rate, blood urea nitrogen level, age and creatinine-that predicted mortality, with an area under the ROC curve (AUC) of 94%. A score based on these variables classified 5,677 (46%) as low risk (a score of 0) who had 0.8% (95% confidence interval, 0.5-1.0%) risk of dying, and 674 (5.4%) as high-risk (score ≥ 12 points) who had a 97.6% (96.5-98.8%) risk of dying; the remainder had intermediate risks. A risk calculator is available online at https://danielevanslab.shinyapps.io/Covid_mortality/. CONCLUSIONS: In a diverse population of hospitalized patients with COVID-19 illness, a clinical prediction model using a few readily available vital signs reflecting the severity of disease may precisely predict in-hospital mortality in diverse populations and can rapidly assist decisions to prioritize admissions and intensive care.

Detection and Genetic Characterization of Community-Based SARS-CoV-2 Infections - New York City, March 2020.

To limit introduction of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), the United States restricted travel from China on February 2, 2020, and from Europe on March 13. To determine whether local transmission of SARS-CoV-2 could be detected, the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) conducted deidentified sentinel surveillance at six NYC hospital emergency departments (EDs) during March 1-20. On March 8, while testing availability for SARS-CoV-2 was still limited, DOHMH announced sustained community transmission of SARS-CoV-2 (1). At this time, twenty-six NYC residents had confirmed COVID-19, and ED visits for influenza-like illness* increased, despite decreased influenza virus circulation.† The following week, on March 15, when only seven of the 56 (13%) patients with known exposure histories had exposure outside of NYC, the level of community SARS-CoV-2 transmission status was elevated from sustained community transmission to widespread community transmission (2). Through sentinel surveillance during March 1-20, DOHMH collected 544 specimens from patients with influenza-like symptoms (ILS)§ who had negative test results for influenza and, in some instances, other respiratory pathogens.¶ All 544 specimens were tested for SARS-CoV-2 at CDC; 36 (6.6%) tested positive. Using genetic sequencing, CDC determined that the sequences of most SARS-CoV-2-positive specimens resembled those circulating in Europe, suggesting probable introductions of SARS-CoV-2 from Europe, from other U.S. locations, and local introductions from within New York. These findings demonstrate that partnering with health care facilities and developing the systems needed for rapid implementation of sentinel surveillance, coupled with capacity for genetic sequencing before an outbreak, can help inform timely containment and mitigation strategies.

Current advances in transfusion medicine 2020: A critical review of selected topics by the AABB Clinical Transfusion Medicine Committee.

BACKGROUND: The AABB Clinical Transfusion Medicine Committee (CTMC) compiles an annual synopsis of the published literature covering important developments in the field of transfusion medicine (TM), which has been made available as a manuscript published in Transfusion since 2018. METHODS: CTMC committee members reviewed original manuscripts including TM-related topics published electronically (ahead) or in print from December 2019 to December 2020. The selection of topics and manuscripts was discussed at committee meetings and chosen based on relevance and originality. Next, committee members worked in pairs to create a synopsis of each topic, which was then reviewed by two additional committee members. The first and senior authors of this manuscript assembled the final manuscript. Although this synopsis is extensive, it is not exhaustive, and some papers may have been excluded or missed. RESULTS: The following topics are included: COVID-19 effects on the blood supply and regulatory landscape, COVID convalescent plasma, adult transfusion practices, whole blood, molecular immunohematology, pediatric TM, cellular therapy, and apheresis medicine. CONCLUSIONS: This synopsis provides easy access to relevant topics and may be useful as an educational tool.