Neonatal diabetes mellitus and congenital diaphragmatic hernia: coincidence or concurrent etiology?

<p>Abstract</p> <p>Neonatal diabetes mellitus (NDM) is a rare metabolic disorder, affecting approximately 1 in 500,000 live births. The management of NDM is challenging, as the benefits of controlling hyperglycemia must be balanced with the risks of iatrogenic hypoglycemia. NDM occurs in both permanent and transient forms, which have been genetically and phenotypically well characterized. Herein, we present the previously unreported combination of transient NDM (TNDM) and congenital diaphragmatic hernia (CDH). In addition to reviewing the management and genetics of NDM we discuss the potential for overlapping genetic or embryologic abnormalities to explain the concurrence of CDH and NDM.</p

Breath Analysis in Children with Ketogenic Glycogen Storage Diseases

(1) Background: The treatment goal of ketogenic glycogen storage diseases (GSDs) is appropriate control of hypoglycemia and other disturbances such as dyslipidemia. Monitoring and treatment of ketosis are known to improve outcomes. We used breath analysis to identify volatile organic compounds (VOCs) that correlate with serum ketones in order to provide a non-invasive method of monitoring ketosis. (2) Methods: Consecutive children with ketogenic GSDs were recruited from a single center during routine admission to monitor serum glucose and ketone levels. Five breath samples were collected from every patient at the same time of blood draws. SIFT-mass spectrometry was used to analyze breath samples. Univariate linear mixed-effects regression models for 22 known VOCs and either serum ketones or glucose were performed. (3) Results: Our cohort included 20 patients aged 5–15 years with a mean BMI of 20 kg/m2 (72% tile). Most patients had GSD type 0 (35%), while 25% had type IX. VOCs that showed a significant correlation with serum ketone levels included acetone (p p p = 0.0001), 3-methylhexane (p = 0.0047), and carbon disulfide (p = 0.0499). No correlation was found between serum glucose and any VOC. (4) Conclusions: Breath analysis is a promising noninvasive tool that can be used to predict ketone serum levels in patients with GSD

Breath Analysis in Children with Ketogenic Glycogen Storage Diseases

(1) Background: The treatment goal of ketogenic glycogen storage diseases (GSDs) is appropriate control of hypoglycemia and other disturbances such as dyslipidemia. Monitoring and treatment of ketosis are known to improve outcomes. We used breath analysis to identify volatile organic compounds (VOCs) that correlate with serum ketones in order to provide a non-invasive method of monitoring ketosis. (2) Methods: Consecutive children with ketogenic GSDs were recruited from a single center during routine admission to monitor serum glucose and ketone levels. Five breath samples were collected from every patient at the same time of blood draws. SIFT-mass spectrometry was used to analyze breath samples. Univariate linear mixed-effects regression models for 22 known VOCs and either serum ketones or glucose were performed. (3) Results: Our cohort included 20 patients aged 5&ndash;15 years with a mean BMI of 20 kg/m2 (72% tile). Most patients had GSD type 0 (35%), while 25% had type IX. VOCs that showed a significant correlation with serum ketone levels included acetone (p &lt; 0.0001), trimethylamine (p &lt; 0.0001), pentane (p = 0.0001), 3-methylhexane (p = 0.0047), and carbon disulfide (p = 0.0499). No correlation was found between serum glucose and any VOC. (4) Conclusions: Breath analysis is a promising noninvasive tool that can be used to predict ketone serum levels in patients with GSD