Application of bone metabolic parameters in the diagnosis of growing pains.

J Clin Lab Anal

Department of Clinical Laboratory, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center For Child Health, Hangzhou, China.

Published: February 2022

Objective: The present study aimed to assess the diagnostic significance of serum bone metabolic parameters in children with growing pains (GPs).

Methods: All patients diagnosed with GP and healthy controls matched with age and gender were recruited at the outpatient clinic of Children's Hospital at Zhejiang University School of Medicine from August 2016 to August 2021. In all subjects, serum levels of calcium (Ca), phosphorus (P), procollagen type-I N-terminal (PINP), parathormone (PTH), 25-hydroxyvitamin D (25-(OH)D), osteocalcin (OC), N-terminal cross-linked telopeptides of type-I collagen (CTX), and tartrate-resistant acid phosphatase type 5b (TRACP5b) were investigated. The univariate analysis, multivariate logistic regression analysis, and receiver operating characteristic (ROC) curve were used to identify the bone metabolic parameters factors for diagnosing GP.

Results: We enrolled 386 children with GP and 399 healthy controls in present study. The mean age of GP group was 5.319 years, and, primarily, the subjects were preschool-age children. The gender ratio (male-to-female) was 1.27 in GP group. After adjusting for age and gender, we identified that the serum levels of Ca (p < 0.001, OR: 25.039), P (p = 0.018, OR: 2.681), PINP (p < 0.001, OR: 1.002), and PTH (p = 0.036, OR: 0.988) were independent diagnostic factors associated with GP. Area under curve (AUC) of the ROC curves was in the order: PINP (0.612) > Ca (0.599) > P (0.583) > PTH (0.541). A combination of independent diagnostic factors and multivariable logistic regression analysis provided a refined logistic regression model to improve the diagnostic potential, of which the AUC had reached 0.655.

Conclusions: Serum levels of Ca, P, PINP, and PTH could be independent diagnostic factors associated with GP. The logistic model was significantly superior to bone metabolic parameters for diagnosing GP.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842154PMC
http://dx.doi.org/10.1002/jcla.24184DOI Listing

Publication Analysis

Top Keywords

bone metabolic
16
metabolic parameters
16
serum levels
12
logistic regression
12
growing pains
8
healthy controls
8
age gender
8
regression analysis
8
independent diagnostic
8
diagnostic factors
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!