Osteoperiostitis in children: proposal for a diagnostic algorithm.

Chronic non-bacterial osteomyelitis Classification tree Differential diagnosis Goldbloom syndrome Osteomyelitis Periostitis

Journal

European journal of pediatrics
ISSN: 1432-1076
Titre abrégé: Eur J Pediatr
Pays: Germany
ID NLM: 7603873

Informations de publication

Date de publication:
Oct 2021
Historique:
received: 29 01 2021
accepted: 29 03 2021
revised: 16 03 2021
pubmed: 9 4 2021
medline: 14 9 2021
entrez: 8 4 2021
Statut: ppublish

Résumé

Juvenile osteoperiostites (JOP) are a group of inflammatory bone diseases whose differential diagnosis is often difficult. The main conditions are acute osteomyelitis (AOM), chronic non-bacterial osteomyelitis (CNO) and the Goldbloom syndrome (GS). The study was aimed to develop an algorithm to enable an early diagnosis of JOP. Clinical records of patients with AOM, CNO and GS, followed at our Center over the past 10 years, were reviewed. Twelve additional patients with GS were selected from PubMed/MEDLINE literature search. Data collected included demographics, clinical manifestations, laboratory and instrumental investigations at disease onset. The association between categorical variables was investigated, and the segmentation of patients with different diagnoses was analyzed through a classification tree model (CTREE package) in order to build up a diagnostic algorithm. Ninety-two patients (33 CNO, 44 AOM, 15 GS) entered the study. Among 30 variables considered at onset, nine (age at onset, fever, weight loss, symmetry, focality, functional limitation, anemia, elevated ESR, CRP) resulted statistically significant in differentiating the three clinical entities from each other and were chosen to build up a decisional tree. Three variables, symmetry of bone involvement, presence of fever and age at disease onset, resulted significant to discriminate each of the three diseases from the others. The performance of the diagnostic algorithm was validated by comparing the diagnoses provided by the model with the real diagnoses and showed 85.9% accuracy.Conclusion: We propose a diagnostic algorithm, based on simple clinical data, which can help guide a prompt and appropriate diagnosis of JOP. What is Known: • Juvenile osteoperiostitis (JOP) are a group of inflammatory bone diseases followed by various pediatric specialists. • The distinction between these conditions is not easy as clinical and laboratory features often overlap. What is New: • We propose a diagnostic algorithm, based on clinical data of real patients, with high degree accuracy. • This instrument can help guide the prompt and appropriate diagnosis of JOP.

Identifiants

pubmed: 33830308
doi: 10.1007/s00431-021-04058-3
pii: 10.1007/s00431-021-04058-3
pmc: PMC8429375
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

3229-3235

Informations de copyright

© 2021. The Author(s).

Références

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Auteurs

Francesco Zulian (F)

Rheumatology Unit, Department of Woman's and Child's Health, University of Padova, Via Giustiniani 3, 35128, Padua, Italy. francescozulian58@gmail.com.

Elena Marigo (E)

Rheumatology Unit, Department of Woman's and Child's Health, University of Padova, Via Giustiniani 3, 35128, Padua, Italy.

Francesca Ardenti-Morini (F)

Pediatric Unit, Sant'Eugenio Hospital, Rome, Italy.

Fabio Vittadello (F)

Explora-Research and Statistical Analysis, Vigodarzere, Padua, Italy.

Monica Zuliani (M)

Department of Medicine-DIMED, Radiology Institute, University of Padova, Padua, Italy.

Chiara Giraudo (C)

Department of Medicine-DIMED, Radiology Institute, University of Padova, Padua, Italy.

Alessandra Meneghel (A)

Rheumatology Unit, Department of Woman's and Child's Health, University of Padova, Via Giustiniani 3, 35128, Padua, Italy.

Giorgia Martini (G)

Rheumatology Unit, Department of Woman's and Child's Health, University of Padova, Via Giustiniani 3, 35128, Padua, Italy.

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