Analytic characteristics of three Bayer contour blood glucose monitoring systems in neonates.

Hypoglycemia in infants is common, is difficult to recognize, and may lead to permanent neurologic impairment. Low glucose concentrations and high hematocrits in newborns pose significant analytic challenges for whole blood glucose meters. Three Bayer glucose monitoring systems were evaluated using 211 blood samples from 162 neonates (age range 5 hours to 29 days, median age 3 days). Hematocrit and whole blood glucose were determined in heparinized whole blood, and plasma glucose was determined using the Roche Cobas 6000. Accuracy was evaluated against plasma concentrations using ISO 15197:2013 and CLSI POCT 12-A3 criteria. Glucose imprecision on the Cobas system was 1.8-2.6% (CV) from 26-610 mg/dL. Imprecision across all meter systems was 2.8% (CV) at 130 mg/dL. Glucose concentrations, hematocrit, and total bilirubin ranged from 20-150 mg/dL, 18 -75%, and 0.5-19.6 mg/dL, respectively. Linear regression analysis of whole blood versus plasma for the 3 combined systems yielded an average slope of 1.06 and correlation coefficient greater than 0.980. Bias between the Contour and Cobas was not significantly correlated with hematocrit. Greater than 99% of meter results were within 15 mg/dL and 20% of plasma results at glucose concentrations ≤ 75 and > 75 mg/dL, respectively. Of meter results, 97% were within 12.5 mg/dL of plasma results at concentrations ≤ 100 mg/dL, while 96% of meter results were within 12.5% of plasma at concentrations > 100 mg/dL. The Bayer CONTOUR Blood Glucose Monitoring Systems exceed ISO 15197:2013 and CLSI criteria in neonatal blood samples.

Point-of-care breath test for biomarkers of active pulmonary tuberculosis.

RATIONALE: Volatile organic compounds (VOCs) in breath provide biomarkers of tuberculosis (TB) because Mycobacterium tuberculosis manufactures VOC metabolites that are detectable in the breath of infected patients. OBJECTIVES: We evaluated breath VOC biomarkers in subjects with active pulmonary TB, using an internet-linked rapid point-of-care breath test. METHODS: 279 subjects were studied at four centers in three countries, Philippines, UK, and India, and data was analyzed from 251 (130 active pulmonary TB, 121 controls). A point-of-care system collected and concentrated breath and air VOCs, and analyzed them with automated thermal desorption, gas chromatography, and surface acoustic wave detection. A breath test was completed in 6 min. Chromatograms were converted to a series of Kovats Index (KI) windows, and biomarkers of active pulmonary TB were identified by Monte Carlo analysis of KI window alveolar gradients (abundance in breath minus abundance in room air). MEASUREMENTS AND MAIN RESULTS: Multiple Monte Carlo simulations identified eight KI windows as biomarkers with better than random performance. Four KI windows corresponded with KI values of VOCs previously identified as biomarkers of pulmonary TB and metabolic products of M. tuberculosis, principally derivatives of naphthalene, benzene and alkanes. A multivariate predictive algorithm identified active pulmonary TB with 80% accuracy (area under curve of receiver operating characteristic curve), sensitivity=71.2%, and specificity = 72%. Accuracy increased to 84% in age-matched subgroups. In a population with 5% prevalence, the breath test would identify active pulmonary TB with 98% negative predictive value and 13% positive predictive value. CONCLUSIONS: A six-minute point-of-care breath test for volatile biomarkers accurately identified subjects with active pulmonary TB.