Accurate point-of-care serology tests for COVID-19.

BACKGROUND: As COVID-19 vaccines become available, screening individuals for prior COVID-19 infection and vaccine response in point-of-care (POC) settings has renewed interest. We prospectively screened at-risk individuals for SARS-CoV-2 spike and nucleocapsid protein antibodies in a POC setting to determine if it was a feasible method to identify antibody from prior infection. METHODS: Three EUA-approved lateral flow antibody assays were performed on POC finger-stick blood and compared with serum and a CLIA nucleocapsid antibody immunoassay. Variables including antibody class, time since PCR, and the assay antigen used were evaluated. RESULTS: 512 subjects enrolled, of which 104 had a COVID-19 history and positive PCR. Only three PCR-positive subjects required hospitalization, with one requiring mechanical ventilation. The POC results correlated well with the immunoassay (93-97% sensitivity) and using serum did not improve the sensitivity or specificity. CONCLUSIONS: Finger-stick, POC COVID-19 antibody testing was highly effective in identifying antibody resulting from prior infections in mildly symptomatic subjects. Using high-complexity serum immunoassays did not improve the screening outcome. Almost all individuals with COVID-19 infection produced detectable antibodies to the virus. POC antibody testing is useful as a screen for prior COVID-19 infection, and should be useful in assessing vaccine response.

Postmarket Surveillance of Point-of-Care Glucose Meters through Analysis of Electronic Medical Records.

BACKGROUND: The electronic medical record (EMR) holds a promising source of data for active postmarket surveillance of diagnostic accuracy, particularly for point-of-care (POC) devices. Through a comparison with prospective bedside and laboratory accuracy studies, we demonstrate the validity of active surveillance via an EMR data mining method [Data Mining EMRs to Evaluate Coincident Testing (DETECT)], comparing POC glucose results to near-in-time central laboratory glucose results. METHODS: The Roche ACCU-CHEK Inform II(®) POC glucose meter was evaluated in a laboratory validation study (n = 73), a prospective bedside intensive care unit (ICU) study (n = 124), and with DETECT (n = 852-27 503). For DETECT, the EMR was queried for POC and central laboratory glucose results with filtering based on of bedside collection timestamps, central laboratory time delays, patient location, time period, absence of repeat testing, and presence of peripheral lines. RESULTS: DETECT and the bedside ICU study produced similar estimates of average bias (4.5 vs 5.0 mg/dL) and relative random error (6.3% vs 5.6%), with overlapping CIs. For glucose <100 mg/dL, the laboratory validation study estimated a lower relative random error of 3.6%. POC average bias correlated with central laboratory turnaround times, consistent with 4.8 mg · dL(-1) · h(-1) glycolysis. After glycolysis adjustment, average bias was estimated by the bedside ICU study at -0.4 mg/dL (CI, -1.6 to 0.9) and DETECT at -0.7 (CI, -1.3 to 0.2), and percentage POC results occurring outside Clinical Laboratory Standards Institute quality goals were 2.4% and 4.8%, respectively. CONCLUSIONS: This study validates DETECT for estimating POC glucose meter accuracy compared with a prospective bedside ICU study and establishes it as a reliable postmarket surveillance methodology.