Molecular genetics and metabolism · 2024
Continuous glucose monitoring metrics in people with liver glycogen storage disease and idiopathic ketotic hypoglycemia: A single-center, retrospective, observational study.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Overduin Ruben J, Venema Annieke, Lubout Charlotte M A, Fokkert-Wilts Marieke J, De Boer Foekje, Schreuder Andrea B, Rossi Alessandro, Derks Terry G J
Аннотация
BACKGROUND: Cohort data on continuous glucose monitoring (CGM) metrics are scarce for liver glycogen storage diseases (GSDs) and idiopathic ketotic hypoglycemia (IKH). The aim of this study was to retrospectively describe CGM metrics for people with liver GSDs and IKH.
PATIENTS AND METHODS: CGM metrics (descriptive, glycemic variation and glycemic control parameters) were calculated for 47 liver GSD and 14 IKH patients, categorized in cohorts by disease subtype, age and treatment status, and compared to published age-matched CGM metrics from healthy individuals. Glycemic control was assessed as time-in-range (TIR; ≥3.9 - ≤7.8 and ≥3.9 - ≤10.0 mmol/L), time-below-range (TBR; <3.0 mmol/L and ≥3.0 - ≤3.9 mmol/L), and time-above-range (TAR; >7.8 and >10.0 mmol/L).
RESULTS: Despite all patients receiving dietary treatment, GSD cohorts displayed significantly different CGM metrics compared to healthy individuals. Decreased TIR together with increased TAR were noted in GSD I, GSD III, and GSD XI (Fanconi-Bickel syndrome) cohorts (all p < 0.05). In addition, all GSD I cohorts showed increased TBR (all p < 0.05). In GSD IV an increased TBR (p < 0.05) and decreased TAR were noted (p < 0.05). In GSD IX only increased TAR was observed (p < 0.05). IKH patient cohorts, both with and without treatment, presented CGM metrics similar to healthy individuals.
CONCLUSION: Despite dietary treatment, most liver GSD cohorts do not achieve CGM metrics comparable to healthy individuals. International recommendations on the use of CGM and clinical targets for CGM metrics in liver GSD patients are warranted, both for patient care and clinical trials.
PATIENTS AND METHODS: CGM metrics (descriptive, glycemic variation and glycemic control parameters) were calculated for 47 liver GSD and 14 IKH patients, categorized in cohorts by disease subtype, age and treatment status, and compared to published age-matched CGM metrics from healthy individuals. Glycemic control was assessed as time-in-range (TIR; ≥3.9 - ≤7.8 and ≥3.9 - ≤10.0 mmol/L), time-below-range (TBR; <3.0 mmol/L and ≥3.0 - ≤3.9 mmol/L), and time-above-range (TAR; >7.8 and >10.0 mmol/L).
RESULTS: Despite all patients receiving dietary treatment, GSD cohorts displayed significantly different CGM metrics compared to healthy individuals. Decreased TIR together with increased TAR were noted in GSD I, GSD III, and GSD XI (Fanconi-Bickel syndrome) cohorts (all p < 0.05). In addition, all GSD I cohorts showed increased TBR (all p < 0.05). In GSD IV an increased TBR (p < 0.05) and decreased TAR were noted (p < 0.05). In GSD IX only increased TAR was observed (p < 0.05). IKH patient cohorts, both with and without treatment, presented CGM metrics similar to healthy individuals.
CONCLUSION: Despite dietary treatment, most liver GSD cohorts do not achieve CGM metrics comparable to healthy individuals. International recommendations on the use of CGM and clinical targets for CGM metrics in liver GSD patients are warranted, both for patient care and clinical trials.