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Characterization of Primary IGF-1 Deficiency in a Cohort of Canadian Children with Short Stature Using a Novel Algorithm Tailored to Electronic Medical Records.
Haridas, Rinila; Baxter, Carly; Dover, Saunya; Goldbloom, Ellen B; Terekhov, Ivan; Robinson, Marie-Eve.
Affiliation
  • Haridas R; Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada.
  • Baxter C; Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada.
  • Dover S; Division of Endocrinology & Metabolism, Children's Hospital of Eastern Ontario, Ottawa, ON K1H 8L1, Canada.
  • Goldbloom EB; Department of Pediatrics, Faculty of Medicine, University of Ottawa, Ottawa, ON K1H 8L1, Canada.
  • Terekhov I; Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada.
  • Robinson ME; Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada.
Children (Basel) ; 11(6)2024 Jun 14.
Article in En | MEDLINE | ID: mdl-38929306
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Children (Basel) Year: 2024 Document type: Article Affiliation country: Canada

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Children (Basel) Year: 2024 Document type: Article Affiliation country: Canada