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Sökning: WFRF:(Koledova E.)

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1.
  • Stevens, A., et al. (författare)
  • Gene expression signatures predict response to therapy with growth hormone
  • 2021
  • Ingår i: Pharmacogenomics Journal. - : Springer Science and Business Media LLC. - 1470-269X .- 1473-1150. ; 21, s. 594-607
  • Tidskriftsartikel (refereegranskat)abstract
    • Recombinant human growth hormone (r-hGH) is used as a therapeutic agent for disorders of growth including growth hormone deficiency (GHD) and Turner syndrome (TS). Treatment is costly and current methods to model response are inexact. GHD (n = 71) and TS patients (n = 43) were recruited to study response to r-hGH over 5 years. Analysis was performed using 1219 genetic markers and baseline (pre-treatment) blood transcriptome. Random forest was used to determine predictive value of transcriptomic data associated with growth response. No genetic marker passed the stringency criteria for prediction. However, we identified an identical set of genes in both GHD and TS whose expression could be used to classify therapeutic response to r-hGH with a high accuracy (AUC > 0.9). Combining transcriptomic markers with clinical phenotype was shown to significantly reduce predictive error. This work could be translated into a single genomic test linked to a prediction algorithm to improve clinical management. Trial registration numbers: NCT00256126 and NCT00699855.
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2.
  • Dimitri, P., et al. (författare)
  • An eHealth Framework for Managing Pediatric Growth Disorders and Growth Hormone Therapy
  • 2021
  • Ingår i: Journal of Medical Internet Research. - : JMIR Publications Inc.. - 1438-8871. ; 23:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The use of technology to support health and health care has grown rapidly in the last decade across all ages and medical specialties. Newly developed eHealth tools are being implemented in long-term management of growth failure in children, a low prevalence pediatric endocrine disorder. 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.
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3.
  • Savage, MO, et al. (författare)
  • Early Detection, Referral, Investigation, and Diagnosis of Children with Growth Disorders
  • 2016
  • Ingår i: Hormone research in paediatrics. - : S. Karger AG. - 1663-2826 .- 1663-2818. ; 85:5, s. 325-332
  • Tidskriftsartikel (refereegranskat)abstract
    • Early diagnosis is a key objective in clinical medicine, and early detection of pathological short stature has tangible benefits for growth prognosis and the well-being of the child. Despite late diagnosis being common in growth disorders, programmes of height screening in primary care are not universal in developed countries and may be random or non-existent. A notable exception is automated growth monitoring in Finland, where an algorithm to detect abnormal growth is integrated into children's electronic health records, resulting in increased diagnoses of pathological short stature. Evidence-based anthropometric criteria for referral of short stature to secondary or tertiary care are now published, due largely to excellent studies in the Netherlands. Following referral of the short child, the protocol for laboratory investigations remains somewhat controversial because in healthy children their diagnostic yield can be too low for cost-effectiveness. However, outside of tertiary academic paediatric endocrinology centres, baseline screening tests are considered worthwhile and may speed up diagnosis and treatment. Finally, auxological cut-offs cannot replace good clinical practice, and the understanding that early and effective management depends on commitment to a diagnosis and individualisation of therapy in the short child cannot be overemphasised.
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