ABSTRACT
BACKGROUND: Recombinant monoclonal antibody therapies have been utilized under emergency use authorization (EUA) for the prevention of clinical decompensation in high-risk COVID-19 positive patients for up to 10 days from symptom onset. The purpose of this study was to determine the impact of the timing of the monoclonal antibody, bamlanivimab, on clinical outcomes in high-risk COVID-19 positive patients. METHODS: This was an IRB-approved, retrospective evaluation of adult patients who received bamlanivimab per EUA criteria in the emergency department (ED). Patients were dichotomized into two groups- 3 days of symptoms or less (early) versus 4 to 10 days (late). The primary outcome was hospitalization for COVID-related illness at 28 days (or treatment failure). Secondary outcomes were COVID-related ED visits at 28 days, hospital and intensive care unit (ICU) length of stay (LOS), and in-hospital mortality at 28 days. RESULTS: A total of 839 patients were included in the analysis. There was no difference observed in COVID-related hospitalization rates within 28 days between the early and late bamlanivimab administration groups (7.5% vs. 8.2%, p = 0.71). There was no difference in COVID-related ED visits within 28 days with 13% of patients returning to the ED. CONCLUSIONS: In conclusion, there were no differences in the rates of hospitalization at 28 days when bamlanivimab was administered in the first 3 days of illness versus days 4 to 10. Future prospective studies are warranted to expand upon the characteristics of patients that may or may not benefit from monoclonal antibody therapy.
Subject(s)
Antibodies, Monoclonal, Humanized/administration & dosage , Antibodies, Neutralizing/administration & dosage , Antiviral Agents/administration & dosage , COVID-19 Drug Treatment , Patient Readmission , Adolescent , Adult , Age Factors , Aged , Body Mass Index , COVID-19/diagnosis , COVID-19/mortality , Drug Administration Schedule , Emergency Service, Hospital , Female , Hospital Mortality , Humans , Length of Stay , Male , Middle Aged , Retrospective Studies , Risk Factors , Treatment Outcome , Young AdultABSTRACT
OBJECTIVE: Historically, double data entry (DDE) has been considered the criterion standard for minimizing data entry errors. However, previous studies considered data entry alternatives through the limited lens of data accuracy. This study supplies information regarding data accuracy, operational efficiency, and cost for DDE and Optical Mark Recognition (OMR) for processing the Consumer Assessment of Healthcare Providers and Systems 5.0 survey. METHODS: To assess data accuracy, we compared error rates for DDE and OMR by dividing the number of surveys that were arbitrated by the total number of surveys processed for each method. To assess operational efficiency, we tallied the cost of data entry for DDE and OMR after survey receipt. Costs were calculated on the basis of personnel, depreciation for capital equipment, and costs of noncapital equipment. RESULTS: The cost savings attributed to this method were negated by the operational efficiency of OMR. There was a statistical significance between rates of arbitration between DDE and OMR; however, this statistical significance did not create a practical significance. CONCLUSIONS: The potential benefits of DDE in terms of data accuracy did not outweigh the operational efficiency and thereby financial savings of OMR.
Subject(s)
Data Accuracy , Data Collection/methods , Data Collection/standards , Efficiency, Organizational , Data Collection/economics , Data Collection/instrumentation , Humans , Patient Satisfaction , Surveys and QuestionnairesABSTRACT
Longitudinal cohort studies normally identify and adjudicate incident events detected during follow-up by retrieving medical records. There are several reasons why the adjudication process may not be successfully completed for a suspected event including the inability to retrieve medical records from hospitals and an insufficient time between the suspected event and data analysis. These "incomplete adjudications" are normally assumed not to be events, an approach which may be associated with loss of precision and introduction of bias. In this article, the authors evaluate the use of multiple imputation methods designed to include incomplete adjudications in analysis. Using data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study, 2008-2009, they demonstrate that this approach may increase precision and reduce bias in estimates of the relations between risk factors and incident events.
