Characterization of Primary IGF-1 Deficiency in a Cohort of Canadian Children with Short Stature Using a Novel Algorithm Tailored to Electronic Medical Records

TL;DR

A new algorithm was developed to identify children with short stature who may have a rare growth disorder, but few cases were confirmed in a Canadian study.

Contribution

A novel EMR algorithm was developed to detect potential cases of SPIGFD in children with short stature.

Findings

The algorithm identified 30 children (0.6%) with potential SPIGFD from 4863 children with short stature.

Chart reviews confirmed that none of the identified children had SPIGFD.

Abstract

(1) Background: Severe primary insulin-like growth factor-I deficiency (SPIGFD) is a rare disorder causing short stature in children due to low insulin-like growth factor 1 (IGF-1) levels. Given the sparsity of reported cases of SPIGFD worldwide, the condition may be underdiagnosed, potentially preventing affected children from receiving therapy with recombinant human IGF-1 (rhIGF-1). Our objective was to determine the prevalence of SPIGFD among children with short stature at a large pediatric tertiary care center through the use of a novel electronic medical record (EMR) algorithm. (2) Methods: We queried our EMR using an algorithm that detected all children seen at our center between 1 November 2013 and 31 August 2021 with short stature and low IGF-1. We then conducted chart reviews, applying established diagnostic criteria for those identified with potential SPIGFD. (3) Results: From a cohort of 4863 children with short stature, our algorithm identified 30 (0.6%) patients with potential SPIGFD. Using chart reviews, we determined that none of these patients had SPIGFD. (4) Conclusions: Our algorithm can be used in other EMRs to identify which patients are likely to have SPIGFD and thus benefit from treatment with rhIGF-1. This model can be replicated for other rare diseases.

Figures