Despite the widespread diffusion of continuous glucose monitoring (CGM) systems, which includes both real-time CGM (rtCGM) and intermittently scanned CGM (isCGM), an effective application of CGM technology in clinical practice is still limited. The study aimed to investigate the relationship between isCGM-derived glycemic metrics and glycated hemoglobin (HbA1c), identifying overall CGM targets and exploring the inter-subject variability.

A group of 27 children and adolescents with type 1 diabetes under multiple daily injection insulin-therapy was enrolled. All participants used the isCGM Abbott's FreeStyle Libre system on average for eight months, and clinical data were collected from the Advanced Intelligent Distant-Glucose Monitoring platform. Starting from each HbA1c exam date, windows of past 30, 60, and 90days were considered to compute several CGM metrics. The relationships between HbA1c and each metric were explored through linear mixed models, adopting an HbA1c target of 7%.

Time in Range and Time in Target Range show a negative relationship with HbA1c (R

0.88) whereas Time Above Range and Time Severely Above Range show a positive relationship (R
0.75). Focusing on Time in Range in 30-day windows, random effect represented by the patient's specific intercept reveals a high variability compared to the overall population intercept.

This study confirms the relationship between several CGM metrics and HbA1c; it also highlights the importance of an individualized interpretation of the CGM data.
This study confirms the relationship between several CGM metrics and HbA1c; it also highlights the importance of an individualized interpretation of the CGM data.
Childhood obesity is a public health concern worldwide, with rates continuing to rise, despite preventive measures. Lifestyle modification remains the mainstay in the treatment of patients with excessive weight, but unfortunately, this is not always successful. Options for medical management of obesity in the paediatric population are limited.

Seven adolescents (all girls, mean age 14.9 years) with a body mass index (BMI) above 98th percentile and serious complications secondary to obesity were offered an intense weight management programme. The participants were reviewed by a multidisciplinary team every two weeks for advice and support, and treated with daily subcutaneous injections of liraglutide (dose range 1.2-3.0mg). Scores for anxiety and depression were evaluated using the Revised Child Anxiety and Depression Scale.

The results showed a significant weight loss over the three months with an average reduction of 5.4kg (4.2%; 95% CI 1.93-8.78; p=0.0087). The mean drop in BMI was 2.1kg/m
, which is statistically significant (95% CI 0.973-3.199; p=0.0037). Resolution of complications (raised intracranial pressure and steatohepatitis) was noted following weight loss. Anxiety and depressive symptoms improved over the three-month intervention course, especially features of separation anxiety disorder. Liraglutide was well tolerated by all patients.

Liraglutide medication, alongside a dedicated multidisciplinary team guided lifestyle therapy, is effective and safe in the treatment for excessive weight in adolescents, leading to the reversal of the complications related to obesity and improvement in the psychological symptoms.
Liraglutide medication, alongside a dedicated multidisciplinary team guided lifestyle therapy, is effective and safe in the treatment for excessive weight in adolescents, leading to the reversal of the complications related to obesity and improvement in the psychological symptoms.
Congenital idiopathic growth hormone deficiency (GHD) is associated with various MRI abnormalities, including sellar and extrasellar abnormalities. However, it remains contentious whether MRI brain findings could provide an additional avenue for precisely predicting the differentiation of GHD based on severity and type isolated GHD or multiple pituitary hormone deficiencies (MPHD). This study aimed to ascertain the abnormality that is the best predictor of severity and type of GHD amongst the different MRI findings.

We conducted an analytical cross-sectional study, including 100 subjects diagnosed with idiopathic GHD. Patients were grouped into severe GHD, partial GHD, and MPHD and into groups based on the presence of pituitary hypoplasia, extrasellar brain abnormalities (EBA), and presence of ectopic posterior pituitary or pituitary stalk abnormalities (EPP/PSA) or both.

Sixty six percentage of subjects had isolated GHD, 34% had MPHD, 71% had severe GHD, and 29% had partial GHD. Pituitary hypoplasia was the most common finding, observed in 53% of patients, while 23% had EBA, and 25% had EPP/PSA. Pituitary hypoplasia was observed to be the best predictor of severity of GHD with an odds ratio (OR) of 10.8, followed by EPP/PSA (OR=2.8), and EBA was the weakest predictor (OR=1.8). Pituitary hypoplasia was the only finding to predict MPHD (OR=9.2) significantly. On ROC analysis, a Pituitary height SDS of-2.03 had the best detection threshold for both severe GHD and MPHD.

We observed Pituitary hypoplasia to be not only the most frequent MRI abnormality but also the best predictor of severe GHD and MPHD amongst various sellar and extrasellar abnormalities.
We observed Pituitary hypoplasia to be not only the most frequent MRI abnormality but also the best predictor of severe GHD and MPHD amongst various sellar and extrasellar abnormalities.
We validated a continuous cardiometabolic risk (CMR) measure among adolescents.

Five metabolic syndrome (MetS) components including waist circumference, triglycerides, high-density lipoprotein cholesterol, fasting blood glucose, and mean arterial pressure were assessed in a national cohort of U.S. adolescents (n=560; 16.5±0.5y/o at baseline) in 10th grade (2010, Wave 1 (W1)), and follow-up assessments four (W4) and seven (W7) years later. Separately by wave, linear regressions were fitted to each MetS component controlling for age, sex, and race/ethnicity, and yielded standardized residuals (Z-scores). Wave-specific component Z-scores were summed to obtain composite CMR Z-scores. Four- and seven-year CMR change (CMR-diff W1-W4 and W1-W7). MAP4K inhibitor and average CMR risk (CMR-avg; (W1+W4)/2 and (W1+W7)/2) were calculated using the CMR Z-scores. W7 MetS was determined using adult criteria. Student's t-test and receiver operating characteristic (ROC) curve were conducted.

Participants meeting the adult criteria for MetS at W7 (74 of 416, 17.MAP4K inhibitor