Reversibility of Hyperglycemic States in Children with Obesity-Diagnostic Pitfalls in the Assessment of Glucose Metabolism in Children and Adolescents with Obesity.

Objective: Disorders of glucose metabolism in children with obesity are less common than in adults. There is also evidence that they may be transient. The aim of this study was to determine the prevalence of impaired fasting glucose (IFG), impaired glucose tolerance (IGT), type 2 diabetes mellitus (DM2) and its reversibility in pediatric patients with obesity and to define the factors determining the reversibility of prediabetes or progression to diabetes. Methods: Retrospective analysis included 573 patients with obesity (mean BMI Z-score 4.4, 316 girls at mean age 13.5 years old, range 2.9-17.11, all Caucasians). Results: The normal results of OGTT were present in 90.8 % (n=520) and prediabetes in 9.2% (n=53) (IFG 17%, IGT 88.7%, DM 0%) subjects. Among those who underwent OGTT twice, impaired glucose regulation was present in 9.3% subjects (n=5) (IFG 40%, IGT 80%, DM 0%) at baseline and in 14.8% subject (n=8) (IFG 25%, IGT 50%, DM 25%) at follow-up after lifestyle modification only. After 12-36 months of follow up, in the previous presence of IGT, 60% reverted to NGT, 20% persisted as IFG and 20% as IGT and no one progressed to DM. The risk factors for progression of glucose metabolism disorders were increase of BMI Z-score, and higher insulin levels, and HOMA-IR. Conclusions: IFG and IGT are common in pediatric patients with obesity, while the progression to DM2 is a rare condition. Disorders of glucose metabolism disorders have reversible character. Every change of BMI Z-score has a significant impact on changes of glucose levels.

Generation of 20 human induced pluripotent stem cell lines from patients with focal segmental glomerulosclerosis (FSGS).

Focal segmental glomerulosclerosis (FSGS) is a major cause of familial nephrotic syndrome. We generated 20 induced pluripotent stem cell lines from patients diagnosed with FSGS. The iPSC lines include 8 female and 12 male lines and cover a donor age range from 31 to 78. The lines were generated from peripheral blood mononuclear cells by integration-free reprogramming using Sendai virus vectors. Cell lines were fully characterized regarding their pluripotency and differentiation potential, and quality controlled for karyotypic integrity, identity and clearance of reprogramming vectors. The generated cell lines represent a valuable tool for disease modelling and drug development for FSGS.

Co-medication and potential drug interactions among patients with epilepsy.

PURPOSE: This study aimed to analyze the extent of co-medication and to assess potential interactions between antiepileptic drugs (AEDs) and other drugs among patients with epilepsy. METHODS: We studied 663 consecutive patients with epilepsy seen in tertiary outpatient clinic. Data on epilepsy and current treatment with AED(s) were collected from structured interview and medical records. Other medications used regularly were classified according to the Anatomical Therapeutic Chemical classification system. Possible drug interactions between AEDs and other drugs were analyzed with the use of IBM Micromedex® database. RESULTS: Studied sample included 395 women; 54.5% of subjects were on monotherapy. Enzyme-inducing AED(s) were used by 127 patients (19.2%). Among 265 patients who used medications other than AEDs (40.0% of all subjects), potential major and moderate interactions between AEDs and other drugs were found in 80 patients (30.1%). Most prevalent major interactions included: ethinylestradiol/estradiol - valproate/oxcarbazepine/carbamazepine, sertraline-carbamazepine, and simvastatin-carbamazepine. A total number of currently used medications (OR = 1.26 [1.07-1.48] per one additional medication; p = 0.005) and the use of enzyme-inducing AEDs (OR = 2.78 [1.51-5.12]; p < 0.001) were independent predictors of interactions between AEDs and other drugs. CONCLUSIONS: Co-medication is common (40%) among patients with epilepsy. Potential major or moderate interactions between AED(s) and other drugs are noted in 30.1% of patients exposed to at least one medication other than AED (12.1% of the entire cohort). The risk of potential interactions increases with the number of medications used chronically and with the use of hepatic enzyme-inducing AEDs.