Development of a multicentre cohort study to understand the role of MRI and ultrasound in the diagnosis of acute haematogenous bone and joint infection in children (the PIC Bone study)

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Nogaro, M-C, Hartshorn, S, Brady, M, Offiah, A, Faust, S, Firth, G, Ma, J, Dhiman, P, O'Mahoney, J, Davies, L et al (show 7 more authors) , Spowart, C, Moscrop, A, Young, B ORCID: 0000-0001-6041-9901, Tudur-Smith, C ORCID: 0000-0003-3051-1445, Collins, G, Perry, DC ORCID: 0000-0001-8420-8252 and Theologis, T (2025) Development of a multicentre cohort study to understand the role of MRI and ultrasound in the diagnosis of acute haematogenous bone and joint infection in children (the PIC Bone study) BONE & JOINT OPEN, 6 (6). pp. 677-684. ISSN 2633-1462, 2633-1462

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Abstract

Aims Bone and joint infections (BJI) in children are rare but can be serious. Differentiating BJI from other conditions with similar symptoms is critical. Advanced imaging (ultrasound scans (USS) and MRI) is often required to confirm the diagnosis. The differing merits of imaging type and regional variation in access to advanced imaging can lead to diagnostic uncertainty and treatment variation. The aim of this study is to evaluate the diagnostic accuracy of MRI and USS for the investigation of BJI in children, and develop and validate prediction models to aid the diagnosis of BJI in children. A nested qualitative sub-study will explore acceptability of the imaging to children, parents, and health practitioners. Methods A multicentre retrospective cohort of children (aged < 16 years) with suspected diagnosis of BJI will be used to estimate the diagnostic accuracy of the two imaging methods and develop the prediction models. The models will be evaluated in a second cohort of prospectively recruited children. Diagnostic test accuracy will be estimated overall, and separately for children aged under and over five years. The prediction models will be fit using logistic regression, with candidate predictors chosen based on clinical plausibility and from a review of the literature. Continuous predictors will be examined for non-linearity with confirmed BJI using fractional polynomials. Multiple imputation will be used to replace missing values. Internal validation will be carried out using bootstrapping. Model performance will be assessed with discrimination and calibration.

Item Type:	Article
Uncontrolled Keywords:	32 Biomedical and Clinical Sciences, 3202 Clinical Sciences, Biomedical Imaging, Bioengineering, Pediatric Research Initiative, Clinical Research, 4.2 Evaluation of markers and technologies
Divisions:	Faculty of Health & Life Sciences Faculty of Health & Life Sciences > Inst. Life Courses & Medical Sciences Faculty of Health & Life Sciences > Inst. Population Health
Depositing User:	Symplectic Admin
Date Deposited:	11 Jun 2025 09:29
Last Modified:	10 Aug 2026 23:13
DOI:	10.1302/2633-1462.66.BJO-2024-0277
Open Access URL:	https://pubmed.ncbi.nlm.nih.gov/40490248/
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3193190
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