Utility of COVID-19 antigen testing in the emergency department.

BACKGROUND: The BinaxNOW coronavirus disease 2019 (COVID-19) Ag Card test (Abbott Diagnostics Scarborough, Inc.) is a lateral flow immunochromatographic point-of-care test for the qualitative detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid protein antigen. It provides results from nasal swabs in 15 minutes. Our purpose was to determine its sensitivity and specificity for a COVID-19 diagnosis. METHODS: Eligible patients had symptoms of COVID-19 or suspected exposure. After consent, 2 nasal swabs were collected; 1 was tested using the Abbott RealTime SARS-CoV-2 (ie, the gold standard polymerase chain reaction test) and the second run on the BinaxNOW point of care platform by emergency department staff. RESULTS: From July 20 to October 28, 2020, 767 patients were enrolled, of which 735 had evaluable samples. Their mean (SD) age was 46.8 (16.6) years, and 422 (57.4%) were women. A total of 623 (84.8%) patients had COVID-19 symptoms, most commonly shortness of breath (n = 404; 55.0%), cough (n = 314; 42.7%), and fever (n = 253; 34.4%). Although 460 (62.6%) had symptoms ≤7 days, the mean (SD) time since symptom onset was 8.1 (14.0) days. Positive tests occurred in 173 (23.5%) and 141 (19.2%) with the gold standard versus BinaxNOW test, respectively. Those with symptoms >2 weeks had a positive test rate roughly half of those with earlier presentations. In patients with symptoms ≤7 days, the sensitivity, specificity, and negative and positive predictive values for the BinaxNOW test were 84.6%, 98.5%, 94.9%, and 95.2%, respectively. CONCLUSIONS: The BinaxNOW point-of-care test has good sensitivity and excellent specificity for the detection of COVID-19. We recommend using the BinasNOW for patients with symptoms up to 2 weeks.

The status of patient portal use among Emergency Department patients experiencing houselessness: A large-scale single-center observational study.

OBJECTIVE: Patient portal (PP) use has rapidly increased in recent years. However, the PP use status among houseless patients is largely unknown. We aim to determine 1) the PP use status among Emergency Department (ED) patients experiencing houselessness, and 2) whether PP use is linked to the increase in patient clinic visits. METHODS: This is a single-center retrospective observational study. From March 1, 2019, to February 28, 2021, houseless patients who presented at ED were included. Their PP use status, including passive PP use (log-on only PP) and effective PP use (use PP of functions) was compared between houseless and non-houseless patients. The number of clinic visits was also compared between these two groups. Lastly, a multivariate logistic regression was analyzed to determine the association between houseless status and PP use. RESULTS: We included a total of 236,684 patients, 13% of whom (30,956) were houseless at time of their encounter. Fewer houseless patients had effective PP use in comparison to non-houseless patients (7.3% versus 11.6%, p < 0.001). In addition, a higher number of clinic visits were found among houseless patients who had effective PP use than those without (18 versus 3, p < 0.001). The adjusted odds ratio of houseless status associated with PP use was 0.48 (95% CI 0.46-0.49, p < 0.001). CONCLUSIONS: Houselessness is a potential risk factor preventing patient portal use. In addition, using patient portals could potentially increase clinic visits among the houseless patient population.

Validation of a simplified comorbidity evaluation predicting clinical outcomes among patients with coronavirus disease 2019 - A multicenter retrospective observation study.

OBJECTIVES: We compared and validated the performance accuracy of simplified comorbidity evaluation compared to the Charlson Comorbidity Index (CCI) predicting COVID-19 severity. In addition, we also determined whether risk prediction of COVID-19 severity changed during different COVID-19 pandemic outbreaks. METHODS: We enrolled all patients whose SARS-CoV-2 PCR tests were performed at six different hospital Emergency Departments in 2020. Patients were divided into three groups based on the various COVID-19 outbreaks in the US (first wave: March-May 2020, second wave: June-September 2020, and third wave: October-December 2020). A simplified comorbidity evaluation was used as an independent risk factor to predict clinical outcomes using multivariate logistic regressions. RESULTS: A total of 22,248 patients were included, for which 7023 (32%) patients tested COVID-19 positive. Higher percentages of COVID-19 patients with more than three chronic conditions had worse clinical outcomes (i.e., hospital and intensive care unit admissions, receiving invasive mechanical ventilations, and in-hospital mortality) during all three COVID-19 outbreak waves. CONCLUSIONS: This simplified comorbidity evaluation was validated to be associated with COVID clinical outcomes. Such evaluation did not perform worse when compared with CCI to predict in-hospital mortality.

A Simplified Comorbidity Evaluation Predicting Clinical Outcomes Among Patients With Coronavirus Disease 2019.

BACKGROUND: Patients with coronavirus disease 2019 (COVID-19) have shown a range of clinical outcomes. Previous studies have reported that patient comorbidities are predictive of worse clinical outcomes, especially when patients have multiple chronic diseases. We aim to: 1) derive a simplified comorbidity evaluation and determine its accuracy of predicting clinical outcomes (i.e., hospital admission, intensive care unit (ICU) admission, ventilation, and in-hospital mortality); and 2) determine its performance accuracy in comparison to well-established comorbidity indexes. METHODS: This was a single-center retrospective observational study. We enrolled all emergency department (ED) patients with COVID-19 from March 1, 2020, to December 31, 2020. A simplified comorbidity evaluation (COVID-related high-risk chronic condition (CCC)) was derived to predict different clinical outcomes using multivariate logistic regressions. In addition, chronic diseases included in the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) were scored, and its accuracy of predicting COVID-19 clinical outcomes was also compared with the CCC. RESULTS: Data were retrieved from 90,549 ED patient visits during the study period, among which 3,864 patients were COVID-19 positive. Forty-seven point nine percent (1,851/3,864) were admitted to the hospital, 9.4% (364) patients were admitted to the ICU, 6.2% (238) received invasive mechanical ventilation, and 4.6% (177) patients died in the hospital. The CCC evaluation correlated well with the four studied clinical outcomes. The adjusted odds ratios of predicting in-hospital death from CCC was 2.84 (95% confidence interval (CI): 1.81 - 4.45, P < 0.001). C-statistics of CCC predicting in-hospital all-cause mortality was 0.73 (0.69 - 0.76), similar to those of the CCI's (0.72) and ECI's (0.71, P = 0.0513). CONCLUSIONS: CCC can accurately predict clinical outcomes among patients with COVID-19. Its performance accuracies for such predictions are not inferior to those of the CCI or ECI's.