Περίληψη:
Background: The limited diagnostic accuracy of biomarkers in children at
risk of a serious bacterial infection (SBI) might be due to the
imperfect reference standard of SBI. We aimed to evaluate the diagnostic
performance of a new classification algorithm for biomarker discovery in
children at risk of SBI.
Methods: We used data from five previously published, prospective
observational biomarker discovery studies, which included patients aged
0-<16 years: the Alder Hey emergency department (n = 1,120), Alder Hey
pediatric intensive care unit (n = 355), Erasmus emergency department (n
= 1,993), Maasstad emergency department (n = 714) and St. Mary’s
hospital (n = 200) cohorts. Biomarkers including procalcitonin (PCT) (4
cohorts), neutrophil gelatinase-associated lipocalin-2 (NGAL) (3
cohorts) and resistin (2 cohorts) were compared for their ability to
classify patients according to current standards (dichotomous
classification of SBI vs. non-SBI), vs. a proposed PERFORM
classification algorithm that assign patients to one of eleven
categories. These categories were based on clinical phenotype, test
outcomes and C-reactive protein level and accounted for the uncertainty
of final diagnosis in many febrile children. The success of the
biomarkers was measured by the Area under the receiver operating Curves
(AUCs) when they were used individually or in combination.
Results: Using the new PERFORM classification system, patients with
clinically confident bacterial diagnosis (”definite bacterial”
category) had significantly higher levels of PCT, NGAL and resistin
compared with those with a clinically confident viral diagnosis
(”definite viral” category). Patients with diagnostic uncertainty
had biomarker concentrations that varied across the spectrum. AUCs were
higher for classification of “definite bacterial” vs. “definite
viral” following the PERFORM algorithm than using the “SBI” vs.
“non-SBI” classification; summary AUC for PCT was 0.77 (95% CI
0.72-0.82) vs. 0.70 (95% CI 0.65-0.75); for NGAL this was 0.80 (95% CI
0.69-0.91) vs. 0.70 (95% CI 0.58-0.81); for resistin this was 0.68
(95% CI 0.61-0.75) vs. 0.64 (0.58-0.69) The three biomarkers combined
had summary AUC of 0.83 (0.77-0.89) for “definite bacterial” vs.
“definite viral” infections and 0.71 (0.67-0.74) for “SBI” vs.
“non-SBI.”
Conclusion: Biomarkers of bacterial infection were strongly associated
with the diagnostic categories using the PERFORM classification system
in five independent cohorts. Our proposed algorithm provides a novel
framework for phenotyping children with suspected or confirmed infection
for future biomarker studies.
Συγγραφείς:
Nijman, Ruud G.
Oostenbrink, Rianne
Moll, Henriette A. and
Casals-Pascual, Climent
von Both, Ulrich
Cunnington, Aubrey and
De, Tisham
Eleftheriou, Irini
Emonts, Marieke
Fink, Colin
and van der Flier, Michiel
de Groot, Ronald
Kaforou, Myrsini and
Kohlmaier, Benno
Kuijpers, Taco W.
Lim, Emma
Maconochie, Ian
K.
Paulus, Stephane
Martinon-Torres, Federico
Pokorn, Marko
and Romaine, Sam T.
Calle, Irene Rivero
Schlapbach, Luregn J.
and Smit, Frank J.
Tsolia, Maria
Usuf, Effua
Wright,
Victoria J.
Yeung, Shunmay
Zavadska, Dace
Zenz, Werner and
Levin, Michael
Herberg, Jethro A.
Carrol, Enitan D.
PERFORM
Consortium Personalized Ri
