Algorithm helps detect undiagnosed adult growth hormone deficiency
Researchers have developed an algorithm that has the potential to improve the detection of adult growth hormone deficiency (AGHD), an often underdiagnosed disease associated with increased morbidity and mortality, according to a study.
By identifying appropriate patients that warrant further diagnostic testing and treatment, the algorithm may help save costs.
Data were used to categorize 135 million adults in the US into groups according to the likelihood of having AGHD. Overall, 0.5% of people were categorized into groups with high likelihood, 6.0%, with moderate likelihood, and 93.6% with low likelihood. The proportions of females were 59.3%, 71.6%, and 50.4%, respectively.
People with high and moderate likelihood were older (aged >50 years) than those in the low-likelihood group.
In the high-likelihood group, only 2.2% of people had been treated with GH therapy as adults.
Those with a higher likelihood of having AGHD had a higher incidence of comorbidities than the low-likelihood group. Comorbidities included malignant neoplastic disease, malignant breast tumor, hyperlipidemia, hypertensive disorder, osteoarthritis, and heart disease.
Yuen KCJ, Birkegard AC, Blevins LS, et al. Development of a Novel Algorithm to Identify People with High Likelihood of Adult Growth Hormone Deficiency in a US Healthcare Claims Database. Int J Endocrinol. 2022;2022:7853786. doi: 10.1155/2022/7853786. PMID: 35761982; PMCID: PMC9233577.