LEARNING POINTS: There is a broad range of differential diagnosis for acromegaloid features such as acromegaly, pseudoacromegaly with severe insulin resistance, Marfan's syndrome, McCune-Albright and a rare condition called pachydermoperiostosis.Once a patient is suspected to have acromegaly, the first step is biochemical testing to confirm the clinical diagnosis, followed by radiologic testing to determine the cause of the excess growth hormone (GH) secretion. The cause is a somatotroph adenoma of the pituitary in over 95 percent of cases.The first step is measurement of a serum insulin-like growth factor 1 (IGF1). A normal serum IGF1 concentration is strong evidence that the patient does not have acromegaly.If the serum IGF1 concentration is high (or equivocal), serum GH should be measured after oral glucose administration. Inadequate suppression of GH after a glucose load confirms the diagnosis of acromegaly.Once the presence of excess GH secretion is confirmed, the next step is pituitary magnetic resonance imaging (MRI).Atypical presentation warrants revision of the diagnosis. This patient presented with clubbing with no gigantism, which is expected in adolescent acromegalics as the growth spurt and epiphyseal plate closure have not taken place yet.
OBJECTIVE: Our objective was to create a framework that can guide future implementation and research on the use of eHealth tools to support patients with growth disorders who require growth hormone therapy.
METHODS: A total of 12 pediatric endocrinologists with experience in eHealth, from a wide geographical distribution, participated in a series of online discussions. We summarized the discussions of 3 workshops, conducted during 2020, on the use of eHealth in the management of growth disorders, which were structured to provide insights on existing challenges, opportunities, and solutions for the implementation of eHealth tools across the patient journey, from referral to the end of pediatric therapy.
RESULTS: A total of 815 responses were collected from 2 questionnaire-based activities covering referral and diagnosis of growth disorders, and subsequent growth hormone therapy stages of the patient pathway, relating to physicians, nurses, and patients, parents, or caregivers. We mapped the feedback from those discussions into a framework that we developed as a guide to integration of eHealth tools across the patient journey. Responses focused on improved clinical management, such as growth monitoring and automation of referral for early detection of growth disorders, which could trigger rapid evaluation and diagnosis. Patient support included the use of eHealth for enhanced patient and caregiver communication, better access to educational opportunities, and enhanced medical and psychological support during growth hormone therapy management. Given the potential availability of patient data from connected devices, artificial intelligence can be used to predict adherence and personalize patient support. Providing evidence to demonstrate the value and utility of eHealth tools will ensure that these tools are widely accepted, trusted, and used in clinical practice, but implementation issues (eg, adaptation to specific clinical settings) must be addressed.
CONCLUSIONS: The use of eHealth in growth hormone therapy has major potential to improve the management of growth disorders along the patient journey. Combining objective clinical information and patient adherence data is vital in supporting decision-making and the development of new eHealth tools. Involvement of clinicians and patients in the process of integrating such technologies into clinical practice is essential for implementation and developing evidence that eHealth tools can provide value across the patient pathway.
RESEARCH DESIGN AND METHODS: Forty sarcopenic women were divided into an experimental group (EX = 30) and a control group (C = 10). The EX-group was further divided into Maintenance Training 1 (MT1 = 10), Maintenance Training 2 (MT2 = 10), and Detraining (DT = 10). The participants underwent 8 weeks of resistance training, consisting of hypertrophy and strength cycles. Following this, the EX-group had a 4-week period with no exercise or a reduced training volume. Measurements were taken at three time points.
RESULTS: After 8 weeks, the EX-group showed significant improvements in Insulin Like Growth Factor-1 (IGF-1), Myostatin (MSTN), Follistatin (Fstn), Growth Hormone (GH) and Cortisol (Cort) compared to the control group. During the volume reduction period, there were no significant differences between MT1 and MT2 groups, but both groups saw increases in IGF-1, Fstn, GH, and decreases in MSTN and Cort compared to the DT group.
CONCLUSIONS: These findings suggest that performing at least one training session per week with the HIIRT protocol is crucial for maintaining hormonal adaptations in sarcopenic older women.
MATERIALS AND METHODS: This was a longitudinal study of eight IGHD subjects (2 males, 6 females) with a mean age of 11.1 ± 0.8 years and age-matched control groups. The pituitary gland, basal ganglia and limbic structures volumes were obtained using 3T MRI voxel-based morphology. The left-hand bone age was assessed using the Tanner-Whitehouse method. Follow-up imaging was performed after an average of 1.8 ± 0.4 years on rhGH.
RESULTS: Subjects with IGHD had a smaller mean volume of the pituitary gland, right thalamus, hippocampus, and amygdala than the controls. After rhGH therapy, these volumes normalized to the age-matched controls. Corpus callosum of IGHD subjects had a larger mean volume than the controls and did not show much volume changes in response to rhGH therapy. There were changes towards normalization of bone age deficit of IGHD in response to rhGH therapy.
CONCLUSION: The pituitary gland, hippocampus, and amygdala volumes in IGHD subjects were smaller than age-matched controls and showed the most response to rhGH therapy. Semi-automated volumetric assessment of pituitary gland, hippocampus, and amygdala using MRI may provide an objective assessment of response to rhGH therapy.