Validation of the Hospital for Sick Children Algorithm for Discriminating Bacteremia From Contaminants in Children With a Preliminary Positive Blood Culture.

STUDY OBJECTIVE: Children with positive blood cultures obtained in the emergency department (ED) prompt urgent actions due to the risk of bacteremia. This study aimed to validate the Hospital for Sick Children algorithm used for discriminating bacteremia from contaminants and identified variables associated with bacteremia in children with positive blood cultures. METHODS: We conducted a retrospective cohort study of all children with positive blood cultures from a tertiary care, pediatric ED between 2018 and 2022. A 2-step standardized approach defined true bacteremia as the primary outcome based on 1) the bacteria involved and 2) the clinical outcome assessed by 2 reviewers. We evaluated multiple independent variables. We used multiple logistic regression to analyze the association between independent variables and outcome. RESULTS: Among the 375,428 ED visits, 574 participants were identified, including 286 (49.8%; 95% confidence interval [CI] 45.8% to 53.9%) with bacteremia and 288 (50.2%; 95% CI 46.1% to 54.3%) with contaminants. The algorithm identified 364 children (63.4%) at high risk of bacteremia, 178 (31.0%) at medium risk, and 32 (5.6%) at low risk. The corresponding bacteremia proportions were 62%, 34%, and 0%, respectively, for a sensitivity of 100% and a specificity of 11%. Suspicion of osteoarticular infection (aOR=43.6; 95% CI 16.2 to 118), presence of internal hardware (aOR=24.9; 95% CI 7.2 to 83.5), and presence of Gram-negative bacteria or Gram-positive cocci in chains/pairs (aOR=21.7; 95% CI 11.7 to 40.3) were the most significant predictors of true bacteremia. CONCLUSION: The Hospital for Sick Children algorithm exhibits 100% sensitivity to detect children with bacteremia but demonstrated low specificity at 11%. We identified predictors to discriminate contaminants from bacteremia.

SARS-CoV-2 immunoassays in a predominantly vaccinated population: Performances and qualitative agreements obtained with two analytical approaches and four immunoassays.

BACKGROUND AND OBJECTIVES: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurveys are typically analysed by applying a fixed threshold for seropositivity ('conventional approach'). However, this approach underestimates the seroprevalence of anti-nucleocapsid (N) in vaccinated individuals-who often exhibit a difficult-to-detect anti-N response. This limitation is compounded by delays between the onset of infection and sample collection. To address this issue, we compared the performance of four immunoassays using a new analytical approach ('ratio-based approach'), which determines seropositivity based on an increase in anti-N levels. MATERIALS AND METHODS: Two groups of plasma donors and four immunoassays (Elecsys total anti-N, VITROS total anti-N, Architect anti-N Immunoglobulin G (IgG) and in-house total anti-N) were evaluated. First-group donors (N = 145) had one positive SARS-CoV-2 polymerase chain reaction (PCR) test result and had made two plasma donations, including one before and one after the PCR test (median = 27 days post-PCR). Second-group donors (N = 100) had made two plasma donations early in the Omicron wave. RESULTS: Among first-group donors (97.9% vaccinated), sensitivity estimates ranged from 60.0% to 89.0% with the conventional approach, compared with 94.5% to 98.6% with the ratio-based approach. Among second-group donors, Fleiss's κ ranged from 0.56 to 0.83 with the conventional approach, compared with 0.90 to 1.00 with the ratio-based approach. CONCLUSION: With the conventional approach, the sensitivity of four immunoassays-measured in a predominantly vaccinated population based on samples collected ~1 month after a positive test result-fell below regulatory agencies requirement of ≥95%. The ratio-based approach significantly improved the sensitivities and qualitative agreement among immunoassays, to the point where all would meet this requirement.