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JAMA Health Forum ; 1(12): e201450, 2020 Dec 01.
Article in English | MEDLINE | ID: covidwho-2059093
Int J Infect Dis ; 104: 34-40, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-997023


BACKGROUND: The use of hydroxychloroquine (HCQ), with or without concurrent administration of azithromycin (AZM), for treatment of COVID-19 has received considerable attention. The purpose of this study was to determine whether HCQ administration is associated with improved mortality in COVID-19 patients. METHODS: We conducted a retrospective analysis of data collected during the care process for COVID-19 positive patients discharged from facilities affiliated with a large healthcare system in the United States as of April 27, 2020. Patients were categorized by treatment with HCQ (in addition to standard supportive therapy) or receipt of supportive therapy with no HCQ. Patient outcomes were evaluated for in-hospital mortality. Patient demographics and clinical characteristics were accounted for through a multivariable regression analysis. RESULTS: A total of 1669 patients were evaluated (no HCQ, n = 696; HCQ, n = 973). When adjusting for patient characteristics, receipt of AZM, and severity of disease at admission, there was no beneficial effect of receipt of HCQ on the risk of death. In this population, there was an 81% increase in the risk of mortality among patients who received HCQ at any time during their hospital stay versus no HCQ exposure (OR: 1.81, 95% CI: 1.20-2.77, p = 0.01). CONCLUSIONS: In this retrospective analysis, we found that there was no benefit of administration of HCQ on mortality in COVID-19 patients. These results support recent changes to clinical trials that discourage the use of HCQ in COVID-19 patients.

COVID-19 Drug Treatment , Hydroxychloroquine/therapeutic use , SARS-CoV-2 , Adolescent , Adult , Aged , Aged, 80 and over , Azithromycin/administration & dosage , COVID-19/mortality , Female , Hospital Mortality , Humans , Hydroxychloroquine/administration & dosage , Male , Middle Aged , Retrospective Studies , Young Adult
Infect Control Hosp Epidemiol ; 42(4): 399-405, 2021 04.
Article in English | MEDLINE | ID: covidwho-806030


OBJECTIVE: To determine risk factors for mortality among COVID-19 patients admitted to a system of community hospitals in the United States. DESIGN: Retrospective analysis of patient data collected from the routine care of COVID-19 patients. SETTING: System of >180 acute-care facilities in the United States. PARTICIPANTS: All admitted patients with positive identification of COVID-19 and a documented discharge as of May 12, 2020. METHODS: Determination of demographic characteristics, vital signs at admission, patient comorbidities and recorded discharge disposition in this population to construct a logistic regression estimating the odds of mortality, particular for those patients characterized as not being critically ill at admission. RESULTS: In total, 6,180 COVID-19+ patients were identified as of May 12, 2020. Most COVID-19+ patients (4,808, 77.8%) were admitted directly to a medical-surgical unit with no documented critical care or mechanical ventilation within 8 hours of admission. After adjusting for demographic characteristics, comorbidities, and vital signs at admission in this subgroup, the largest driver of the odds of mortality was patient age (OR, 1.07; 95% CI, 1.06-1.08; P < .001). Decreased oxygen saturation at admission was associated with increased odds of mortality (OR, 1.09; 95% CI, 1.06-1.12; P < .001) as was diabetes (OR, 1.57; 95% CI, 1.21-2.03; P < .001). CONCLUSIONS: The identification of factors observable at admission that are associated with mortality in COVID-19 patients who are initially admitted to non-critical care units may help care providers, hospital epidemiologists, and hospital safety experts better plan for the care of these patients.

COVID-19/pathology , Vital Signs , Age Factors , Aged , Aged, 80 and over , COVID-19/mortality , Female , Humans , Logistic Models , Male , Middle Aged , Oxygen/blood , Patient Admission/statistics & numerical data , Retrospective Studies , Risk Factors , United States/epidemiology