Objective To determine whether updating a diagnostic prediction model by adding a combination assay (tumour necrosis factor-related apoptosis-inducing ligand, interferon γinduced protein-10 and C reactive protein (CRP)) can accurately identify children with pneumonia or other serious bacterial infections (SBIs). Design Observational double-blind diagnostic study. Setting Two hospitals in Israel and four hospitals in the Netherlands. Patients 591 children, aged 1-60 months, presenting with lower respiratory tract infections or fever without source. 96 of them had SBIs. The original Feverkidstool, a polytomous logistic regression model including clinical variables and CRP, was recalibrated and thereafter updated by using the assay. Main outco...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
Timely antibiotic treatment improves the outcome of patients with bacterial infections, but antibiot...
textabstractObjective: To derive, cross validate, and externally validate a clinical prediction mode...
__Objective__ To determine whether updating a diagnostic prediction model by adding a combination as...
Objective: To externally validate and update the Feverkids tool clinical prediction model for differ...
BACKGROUND: A physician is frequently unable to distinguish bacterial from viral infections. ImmunoX...
BACKGROUND: A physician is frequently unable to distinguish bacterial from viral infections. ImmunoX...
\ua9 2023 Author(s). Published by BMJ.Objective: To externally validate and update the Feverkids too...
OBJECTIVE To externally validate and update the Feverkids tool clinical prediction model for diff...
OBJECTIVE To externally validate and update the Feverkids tool clinical prediction model for diff...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
Background: There is a need to better distinguish viral infections from antibiotic-requiring bacteri...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
Timely antibiotic treatment improves the outcome of patients with bacterial infections, but antibiot...
textabstractObjective: To derive, cross validate, and externally validate a clinical prediction mode...
__Objective__ To determine whether updating a diagnostic prediction model by adding a combination as...
Objective: To externally validate and update the Feverkids tool clinical prediction model for differ...
BACKGROUND: A physician is frequently unable to distinguish bacterial from viral infections. ImmunoX...
BACKGROUND: A physician is frequently unable to distinguish bacterial from viral infections. ImmunoX...
\ua9 2023 Author(s). Published by BMJ.Objective: To externally validate and update the Feverkids too...
OBJECTIVE To externally validate and update the Feverkids tool clinical prediction model for diff...
OBJECTIVE To externally validate and update the Feverkids tool clinical prediction model for diff...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
Background: There is a need to better distinguish viral infections from antibiotic-requiring bacteri...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
International audienceThe diagnosis of serious bacterial infection (SBI) in young febrile children r...
Timely antibiotic treatment improves the outcome of patients with bacterial infections, but antibiot...
textabstractObjective: To derive, cross validate, and externally validate a clinical prediction mode...