Metabolic trajectories of diabetic ketoacidosis onset described by breath analysis.

Purpose: This feasibility study aimed to investigate the use of exhaled breath analysis to capture and quantify relative changes of metabolites during resolution of acute diabetic ketoacidosis under insulin and rehydration therapy. Methods: Breath analysis was conducted on 30 patients of which 5 with DKA. They inflated Nalophan bags, and their metabolic content was subsequently interrogated by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). Results: SESI-HRMS analysis showed that acetone, pyruvate, and acetoacetate, which are well known to be altered in DKA, were readily detectable in breath of participants with DKA. In addition, a total of 665 mass spectral features were found to significantly correlate with base excess and prompt metabolic trajectories toward an in-control state as they progress toward homeostasis. Conclusion: This study provides proof-of-principle for using exhaled breath analysis in a real ICU setting for DKA monitoring. This non-invasive new technology provides new insights and a more comprehensive overview of the effect of insulin and rehydration during DKA treatment.

Clinically practical pharmacometrics computer model to evaluate and personalize pharmacotherapy in pediatric rare diseases: application to Graves' disease.

Objectives: Graves' disease (GD) with onset in childhood or adolescence is a rare disease (ORPHA:525731). Current pharmacotherapeutic approaches use antithyroid drugs, such as carbimazole, as monotherapy or in combination with thyroxine hormone substitutes, such as levothyroxine, as block-and-replace therapy to normalize thyroid function and improve patients' quality of life. However, in the context of fluctuating disease activity, especially during puberty, a considerable proportion of pediatric patients with GD is suffering from thyroid hormone concentrations outside the therapeutic reference ranges. Our main goal was to develop a clinically practical pharmacometrics computer model that characterizes and predicts individual disease activity in children with various severity of GD under pharmacotherapy. Methods: Retrospectively collected clinical data from children and adolescents with GD under up to two years of treatment at four different pediatric hospitals in Switzerland were analyzed. Development of the pharmacometrics computer model is based on the non-linear mixed effects approach accounting for inter-individual variability and incorporating individual patient characteristics. Disease severity groups were defined based on free thyroxine (FT4) measurements at diagnosis. Results: Data from 44 children with GD (75% female, median age 11 years, 62% receiving monotherapy) were analyzed. FT4 measurements were collected in 13, 15, and 16 pediatric patients with mild, moderate, or severe GD, with a median FT4 at diagnosis of 59.9 pmol/l (IQR 48.4, 76.8), and a total of 494 FT4 measurements during a median follow-up of 1.89 years (IQR 1.69, 1.97). We observed no notable difference between severity groups in terms of patient characteristics, daily carbimazole starting doses, and patient years. The final pharmacometrics computer model was developed based on FT4 measurements and on carbimazole or on carbimazole and levothyroxine doses involving two clinically relevant covariate effects: age at diagnosis and disease severity. Discussion: We present a tailored pharmacometrics computer model that is able to describe individual FT4 dynamics under both, carbimazole monotherapy and carbimazole/levothyroxine block-and-replace therapy accounting for inter-individual disease progression and treatment response in children and adolescents with GD. Such clinically practical and predictive computer model has the potential to facilitate and enhance personalized pharmacotherapy in pediatric GD, reducing over- and underdosing and avoiding negative short- and long-term consequences. Prospective randomized validation trials are warranted to further validate and fine-tune computer-supported personalized dosing in pediatric GD and other rare pediatric diseases.

New model of glucose-insulin regulation characterizes effects of physical activity and facilitates personalized treatment evaluation in children and adults with type 1 diabetes.

Accurate treatment adjustment to physical activity (PA) remains a challenging problem in type 1 diabetes (T1D) management. Exercise-driven effects on glucose metabolism depend strongly on duration and intensity of the activity, and are highly variable between patients. In-silico evaluation can support the development of improved treatment strategies, and can facilitate personalized treatment optimization. This requires models of the glucose-insulin system that capture relevant exercise-related processes. We developed a model of glucose-insulin regulation that describes changes in glucose metabolism for aerobic moderate- to high-intensity PA of short and prolonged duration. In particular, we incorporated the insulin-independent increase in glucose uptake and production, including glycogen depletion, and the prolonged rise in insulin sensitivity. The model further includes meal absorption and insulin kinetics, allowing simulation of everyday scenarios. The model accurately predicts glucose dynamics for varying PA scenarios in a range of independent validation data sets, and full-day simulations with PA of different timing, duration and intensity agree with clinical observations. We personalized the model on data from a multi-day free-living study of children with T1D by adjusting a small number of model parameters to each child. To assess the use of the personalized models for individual treatment evaluation, we compared subject-specific treatment options for PA management in replay simulations of the recorded data with altered meal, insulin and PA inputs.

Computing optimal drug dosing with OptiDose: implementation in NONMEM.

Determining a drug dosing recommendation with a PKPD model can be a laborious and complex task. Recently, an optimal dosing algorithm (OptiDose) was developed to compute the optimal doses for any pharmacometrics/PKPD model for a given dosing scenario. In the present work, we reformulate the underlying optimal control problem and elaborate how to solve it with standard commands in the software NONMEM. To demonstrate the potential of the OptiDose implementation in NONMEM, four relevant but substantially different optimal dosing tasks are solved. In addition, the impact of different dosing scenarios as well as the choice of the therapeutic goal on the computed optimal doses are discussed.

Semimechanistic modeling of copeptin and aldosterone kinetics and dynamics in response to rehydration treatment for diabetic ketoacidosis in children.

Diabetic ketoacidosis (DKA), a frequent complication of type 1 diabetes (T1D), is characterized by hyperosmolar hypovolemia. The response of water-regulating hormones arginine vasopressin (AVP; antidiuretic hormone) and aldosterone to DKA treatment in children is not well understood, although they may have potential as future diagnostic, prognostic, and/or treatment monitoring markers in diabetic patients. We aimed to characterize the dynamics of the response in copeptin (marker for AVP) and aldosterone secretion to rehydration treatment in pediatric patients with DKA. Data originated from a prospective, observational, multicenter study including 28 pediatric T1D patients treated for DKA (median age, 11.5 years; weight, 35 kg). Serial measurements of hormone levels were obtained during 72 h following rehydration start. Semimechanistic pharmacometric modeling was used to analyze the kinetic/dynamic relationship of copeptin and aldosterone secretion in response to the correction of hyperosmolality and hypovolemia, respectively. Modeling revealed different sensitivities for osmolality-dependent copeptin secretion during the first 72 h of rehydration, possibly explained by an osmotic shift introduced by hypovolemia. Response in aldosterone secretion to the correction of hypovolemia seemed to be delayed, which was well described by an extra upstream turnover compartment, possibly representing chronic upregulation of aldosterone synthase (cytochrome P450 11B2). In conclusion, semimechanistic modeling provided novel physiological insights in hormonal water regulation in pediatric patients during DKA treatment, providing rationale to further evaluate the potential of monitoring copeptin, but not aldosterone due to its delayed response, for future optimization of rehydration treatment to reduce the risk of acute complications such as cerebral edema.

Trends and outcomes of children, adolescents, and adults hospitalized with inherited metabolic disorders: A population-based cohort study.

Inherited metabolic disorders (IMDs) comprise a heterogeneous class of genetic disorders characterized by impaired biochemical functions in metabolism. However, incidences and outcomes of patients hospitalized with IMDs are largely unknown. We conducted a population-based cohort study using nationwide in-hospital claims data in Switzerland from 2012 to 2020. We assessed incidence rates of hospitalizations and hospital-associated outcomes, stratified in five age groups (0-9, 10-19, 20-39, 40-59, and 60-90 years) and three types of IMDs (peptide, amine and amino acid metabolism disorders [AD], carbohydrate metabolism disorders [CD], fatty acid, and ketone body metabolism disorders [FD]). A total of 7293 hospitalizations with IMD were identified, of which 3638 had AD, 3153 CD, and 502 FD. Incidence rates for hospitalizations per 100 000 person-years were highest under the age of 10 years across all types of IMDs (8.69 for AD, 5.73 for CD, 3.71 for FD) and decreased thereafter. In patients with AD and CD, hospitalization rates increased again in adults aged 60-90 years (7.28 for AD, 7.25 for CD), while they remained low in patients with FD (0.31). Compared to inpatients without IMD, adult IMD patients had a higher burden of hospital-associated adverse outcomes including an increased risk of in-hospital mortality, intensive care unit admission, mechanical ventilation, and longer length of hospital or intensive care unit stay. Incremental risk of 30-day, 1-year, and 2-year hospital readmission was highest among children and adolescents with IMD.

Endocrine Disorders in Children with Brain Tumors: At Diagnosis, after Surgery, Radiotherapy and Chemotherapy.

INTRODUCTION: Brain tumors are the second most frequent type of all pediatric malignancies. Depending on their localization, patients with brain tumors may present neurological or ophthalmological symptoms, but also weight anomalies and endocrine disorders ranging from growth hormone deficiency, anomalies of puberty, diabetes insipidus to panhypopituitarism. Immediately at diagnosis, all patients with brain tumors require a complete assessment of the hypothalamic-pituitary function in order to address eventual endocrine disorders. Moreover, children and adolescents undergoing brain surgery must receive peri- and postoperative hydrocortisone stress therapy. Post-operative disorders of water homeostasis are frequent, ranging from transient diabetes insipidus, as well as syndrome of inappropriate antidiuretic hormone secretion to persistent diabetes insipidus. Late endocrine disorders may result from surgery near or within the hypothalamic-pituitary region. Pituitary deficits are frequent after radiotherapy, especially growth hormone deficiency. Thyroid nodules or secondary thyroid cancers may arise years after radiotherapy. Gonadal dysfunction is frequent after chemotherapy especially with alkylating agents. CONCLUSION: Early detection and treatment of specific endocrine disorders at diagnosis, perioperatively, and during long-term follow-up result in improved general and metabolic health and quality of life.

Machine learning-based algorithm as an innovative approach for the differentiation between diabetes insipidus and primary polydipsia in clinical practice.

Objective: Differentiation between central diabetes insipidus (cDI) and primary polydipsia (PP) remains challenging in clinical practice. Although the hypertonic saline infusion test led to high diagnostic accuracy, it is a laborious test requiring close monitoring of plasma sodium levels. As such, we leverage machine learning (ML) to facilitate differential diagnosis of cDI. Design: We analyzed data of 59 patients with cDI and 81 patients with PP from a prospective multicenter study evaluating the hypertonic saline test as new test approach to diagnose cDI. Our primary outcome was the diagnostic accuracy of the ML-based algorithm in differentiating cDI from PP patients. Methods: The data set used included 56 clinical, biochemical, and radiological covariates. We identified a set of five covariates which were crucial for differentiating cDI from PP patients utilizing standard ML methods. We developed ML-based algorithms on the data and validated them with an unseen test data set. Results: Urine osmolality, plasma sodium and glucose, known transsphenoidal surgery, or anterior pituitary deficiencies were selected as input parameters for the basic ML-based algorithm. Testing it on an unseen test data set resulted in a high area under the curve (AUC) score of 0.87. A further improvement of the ML-based algorithm was reached with the addition of MRI characteristics and the results of the hypertonic saline infusion test (AUC: 0.93 and 0.98, respectively). Conclusion: The developed ML-based algorithm facilitated differentiation between cDI and PP patients with high accuracy even if only clinical information and laboratory data were available, thereby possibly avoiding cumbersome clinical tests in the future.

Lifetime risk and health-care burden of diabetic ketoacidosis: A population-based study.

Objective: Diabetic ketoacidosis (DKA) is a life-threatening complication of both type 1 and type 2 diabetes. We aimed to assess population-based rates, trends and outcomes of patients with DKA. Design and methods: This is a nationwide cohort study using hospital discharge claims data from 2010 to 2018 in Switzerland. Incidence rates and in-hospital outcomes of DKA were analyzed throughout lifetime for children (0-9 years), adolescents (10-19 years), and adults (20-29, 30-59, and 60-90 years). Analyses were stratified for type of diabetes mellitus and sex. Results: In total, 5,544 hospitalizations with DKA were identified, of whom 3,847 were seen in patients with type 1 diabetes and 1,697 in type 2 diabetes. Incidence rates of DKA among patients with type 1 diabetes were highest during adolescence with 17.67 (girls) and 13.87 (boys) events per 100,000 person-years (incidence rate difference [IRD]: -3.80 [95% CI, -5.59 to -2.02]) and decreased with age in both sexes thereafter. Incidence rates of DKA in patients with type 2 diabetes were low up to an age of 40 years and rose to 5.26 (females) and 6.82 (males) per 100,000 person-years in adults aged 60-90 years. Diabetic ketoacidosis was associated with relevant health-care burden independent of age, sex, or type of diabetes. The population-based incidence rate of DKA increased over time from 7.22 per 100,000 person-years in 2010 to 9.49 per 100,000 person-years in 2018. Conclusions: In type 1 diabetes highest incidence rates of DKA hospitalizations were observed among adolescent females. In comparison, in patients with type 2 diabetes the risk for DKA steadily increased with age with higher rates in adult males. Over the 9 year study period, incidence rates of DKA were increasing irrespective of type of diabetes. DKA was associated with a high burden of disease reflected by high rates of intensive care unit admission, prolonged hospital stay and high mortality rates, especially in elderly.

Fear of hypoglycemia and quality of life in young people with type 1 diabetes and their parents in the era of sensor glucose monitoring.

Introduction: It is crucial to understand psychosocial outcomes in children and adolescents with type 1 diabetes (T1D) and their families to provide optimal family-centered care. Hence, the aim of this study was to explore psychosocial outcomes in young people with T1D and their parents using currently available glucose monitoring devices in a real-life clinic setting. Methods: Children and adolescents aged 2-18 years with T1D for more than 6 months and their parents were recruited into a cross-sectional study to complete the Hypoglycemia Fear Survey (HFS) and the Pediatric Quality of Life Inventory (PedsQL) Generic Score Scales, Diabetes Module and Family Impact Module. Demographics and diabetes-specific parameters were obtained from medicals records. Results: Fifty-nine children and adolescents (mean age 15.1 ± 3.0 years) and 49 parents of children (mean age of children 12.5± 3.3 years) of which 44 were child-parent dyads completed the questionnaires. Parents had a higher mean (SD) FOH total and worry subscore than children, total score was 37.9 (14.6) vs. 32.2 (11.9), p = 0.047 and worry subscore was 17.8 (10.4) vs. 12.8 (9.0), p = 0.01. Furthermore, lower parental diabetes-specific QoL score was observed in parents, 78.8 (12.2) vs. 82.7 (10.3), p=0.02. No difference in FOH and QoL between real-time continuous glucose monitoring (rtCGM) and intermittently scanned glucose monitoring (isCGM) users and users of devices with and without alerts was observed. In isCGM users (n=36 completing the child questionnaires, n=33 completing parent questionnaires), higher parental FOH and lower parental diabetes-specific QoL correlated with higher scanning frequency, r = 0.399, p = 0.021, and r = -0.464, p = 0.007 respectively. No significant correlation was documented between scanning frequency and child questionnaire scores. Conclusions: Parents are more likely to perceive higher levels of psychosocial burden related to their child's diabetes than children and adolescents with T1D, especially parents of younger children. This highlights the need for family-based education and treatment resources to support parents in diabetes management in addition to rapidly advancing diabetes technology. In isCGM users, higher parental FOH and lower parent-perceived QoL correlated with a higher scanning frequency, indicating the potential impact of glucose monitoring modality on psychosocial outcomes or vice versa.

Caregiver burden, and parents' perception of disease severity determine health-related quality of life in paediatric patients with intoxication-type inborn errors of metabolism.

Background: Living with a non-acute (phenylketonuria) or acute (e.g. urea cycle disorders, organic acidurias) intoxication-type inborn error of metabolism (IT-IEM) can have a substantial impact on health-related quality of life (HrQoL) of paediatric patients and their families. Parents take primary responsibility for treatment monitoring and experience worry and fear about their child's health status. Quantitative evidence on parental psychological factors which may influence the HrQoL of patients with IT-IEM are sparse to non-existent. Methods: In this multicenter survey study 50 parents of IT-IEM patients (ages 5-19) assessed the severity of their child's disease, reported on caregiver burden, and proxy-rated their child's HrQoL. Additionally, 35 patient self-reports on HrQoL were obtained (n = 16 female patients, n = 19 male patients). Multiple linear regressions were conducted to examine the predictive power of child age, sex, medical diagnosis type (acute / non-acute), parental perceived disease severity and caregiver burden on patients' HrQoL. Mediation analyses were used to investigate the relation of caregiver burden and parental ratings of disease severity with patients' HrQoL. Results: Significant regression models for self-reported [F(5,34) = 10.752, p < .001, R 2 adj.. = 0.59] and parent proxy reported HrQoL [F(5,49) = 20.513, p < .001, R 2 adj.. = 0.67] emerged. High caregiver burden and perceived disease severity predicted significantly lower patient self- and proxy-reported HrQoL while type of diagnosis (acute versus non-acute) did not. Female sex predicted significantly lower self-reported HrQoL. High caregiver burden was the mediating factor between high perceived severity of the child's disease and lower proxy- by parent rated HrQoL. Conclusion: Detecting elevated burden of care and providing support for parents seems crucial to prevent adverse consequences for their children's HrQoL. Intervention studies are needed, to assess which support programs are most efficient.

Glucagon-stimulated copeptin measurements in the differential diagnosis of diabetes insipidus: a double-blind, randomized, placebo-controlled study.

Background: The differential diagnosis of diabetes insipidus is challenging. The most reliable approaches are copeptin measurements after hypertonic saline infusion or arginine, which is a known growth hormone secretagogue but has recently also been shown to stimulate the neurohypophysis. Similar to arginine, glucagon stimulates growth hormone release, but its effect on the neurohypophysis is poorly studied. Design: Double-blind, randomized, placebo-controlled trial including 22 healthy participants, 10 patients with central diabetes insipidus, and 10 patients with primary polydipsia at the University Hospital Basel, Switzerland. Methods: Each participant underwent the glucagon test (s.c. injection of 1 mg glucagon) and placebo test. The primary objective was to determine whether glucagon stimulates copeptin and to explore whether the copeptin response differentiates between diabetes insipidus and primary polydipsia. Copeptin levels were measured at baseline, 30, 60, 90, 120, 150, and 180 min after injection. Results: In healthy participants, glucagon stimulated copeptin with a median increase of 7.56 (2.38; 28.03) pmol/L, while placebo had no effect (0.10 pmol/L (-0.70; 0.68); P < 0.001). In patients with diabetes insipidus, copeptin showed no relevant increase upon glucagon, with an increase of 0.55 (0.21; 1.65) pmol/L, whereas copeptin was stimulated in patients with primary polydipsia with an increase of 15.70 (5.99; 24.39) pmol/L. Using a copeptin cut-off level of 4.6pmol/L had a sensitivity of 100% (95% CI: 100-100) and a specificity of 90% (95% CI: 70-100) to discriminate between diabetes insipidus and primary polydipsia. Conclusion: Glucagon stimulates the neurohypophysis, and glucagon-stimulated copeptin has the potential for a safe, novel, and precise test in the differential diagnosis of diabetes insipidus.

The kinetic profiles of copeptin and mid regional proadrenomedullin (MR-proADM) in pediatric lower respiratory tract infections.

BACKGROUND: Kinetics of copeptin and mid regional proadrenomedullin (MR-proADM) during febrile pediatric lower respiratory tract infections (LRTI) are unknown. We aimed to analyze kinetic profiles of copeptin and MR-proADM and the impact of clinical and laboratory factors on those biomarkers. METHODS: This is a retrospective post-hoc analysis of a randomized controlled trial, evaluating procalcitonin guidance for antibiotic treatment of LRTI (ProPAED-study). In 175 pediatric patients presenting to the emergency department plasma copeptin and MR-proADM concentrations were determined on day 1, 3, and 5. Their association with clinical characteristics and other inflammatory biomarkers were tested by non-linear mixed effect modelling. RESULTS: Median copeptin and MR-proADM values were elevated on day 1 and decreased during on day 3 and 5 (-26%; -34%, respectively). The initial concentrations of MR-proADM at inclusion were higher in patients receiving antibiotics intravenously compared to oral administration (difference 0.62 pmol/L, 95%CI 0.44;1.42, p<0.001). Intensive care unit (ICU) admission was associated with a daily increase of MR-proADM (increase/day 1.03 pmol/L, 95%CI 0.43;1.50, p<0.001). Positive blood culture in patients with antibiotic treatment and negative results on nasopharyngeal aspirates, or negative blood culture were associated with a decreasing MR-proADM (decrease/day -0.85 pmol/L, 95%CI -0.45;-1.44), p<0.001). CONCLUSION: Elevated MR-proADM and increases thereof were associated with ICU admission suggesting the potential as a prognostic factor for severe pediatric LRTI. MR-proADM might only bear limited value for decision making on stopping antibiotics due to its slow decrease. Copeptin had no added value in our setting.

OptiDose: Computing the Individualized Optimal Drug Dosing Regimen Using Optimal Control.

Providing the optimal dosing strategy of a drug for an individual patient is an important task in pharmaceutical sciences and daily clinical application. We developed and validated an optimal dosing algorithm (OptiDose) that computes the optimal individualized dosing regimen for pharmacokinetic-pharmacodynamic models in substantially different scenarios with various routes of administration by solving an optimal control problem. The aim is to compute a control that brings the underlying system as closely as possible to a desired reference function by minimizing a cost functional. In pharmacokinetic-pharmacodynamic modeling, the controls are the administered doses and the reference function can be the disease progression. Drug administration at certain time points provides a finite number of discrete controls, the drug doses, determining the drug concentration and its effect on the disease progression. Consequently, rewriting the cost functional gives a finite-dimensional optimal control problem depending only on the doses. Adjoint techniques allow to compute the gradient of the cost functional efficiently. This admits to solve the optimal control problem with robust algorithms such as quasi-Newton methods from finite-dimensional optimization. OptiDose is applied to three relevant but substantially different pharmacokinetic-pharmacodynamic examples.

Simulation-Based Evaluation of Treatment Adjustment to Exercise in Type 1 Diabetes.

Regular exercise is beneficial and recommended for people with type 1 diabetes, but increased glucose demand and changes in insulin sensitivity require treatment adjustments to prevent exercise-induced hypoglycemia. Several different adjustment strategies based on insulin bolus reductions and additional carbohydrate intake have been proposed, but large inter- and intraindividual variability and studies using different exercise duration, intensity, and timing impede a direct comparison of their effects. In this study, we use a mathematical model of the glucoregulatory system and implement published guidelines and strategies in-silico to provide a direct comparison on a single 'typical' person on a standard day with three meals. We augment this day by a broad range of exercise scenarios combining different intensity and duration of the exercise session, and different timing with respect to adjacent meals. We compare the resulting blood glucose trajectories and use summary measures to evaluate the time-in-range and risk scores for hypo- and hyperglycemic events for each simulation scenario, and to determine factors that impede prevention of hypoglycemia events. Our simulations suggest that the considered strategies and guidelines successfully minimize the risk for acute hypoglycemia. At the same time, all adjustments substantially increase the risk of late-onset hypoglycemia compared to no adjustment in many cases. We also find that timing between exercise and meals and additional carbohydrate intake during exercise can lead to non-intuitive behavior due to superposition of meal- and exercise-related glucose dynamics. Increased insulin sensitivity appears as a major driver of non-acute hypoglycemic events. Overall, our results indicate that further treatment adjustment might be required both immediately following exercise and up to several hours later, but that the intricate interplay between different dynamics makes it difficult to provide generic recommendations. However, our simulation scenarios extend substantially beyond the original scope of each model component and proper model validation is warranted before applying our in-silico results in a clinical setting.

Autonomic cardiac regulation during spontaneous nocturnal hypoglycemia in children with type 1 diabetes.

BACKGROUND: Hypoglycemia is the most common complication in insulin treated diabetes. Though mostly mild, it can be fatal in rare cases: It is hypothesized that hypoglycemia related QTc prolongation contributes to cardiac arrhythmia. OBJECTIVE: To evaluate influence of nocturnal hypoglycemia on QTc and heart rate variability (HRV) in children with T1D. METHODS: Children and adolescents with T1D for at least 6 months participated in an observational study using continuous glucose monitoring (CGM) and Holter electrocardiogram for five consecutive nights. Mean QTc was calculated for episodes of nocturnal hypoglycemia (<3.7 mmol/L) and compared to periods of the same duration preceding hypoglycemia. HRV (RMSSD, low and high frequency power LF and HF) was analyzed for different 15 min intervals: before hypoglycemia, onset of hypoglycemia, before/after nadir, end of hypoglycemia and after hypoglycemia. RESULTS: Mean QTc during hypoglycemia was significantly longer compared to euglycemia (412 ± 15 vs. 405 ± 18 ms, p = 0.005). HRV changed significantly: RMSSD (from 88 ± 57 to 73 ± 43 ms) and HF (from 54 ± 17 to 47 ± 17nu) decreased from before hypoglycemia to after nadir, while heart rate (from 69 ± 9 to 72 ± 12 bpm) and LF (from 44 ± 17 to 52 ± 21 nu) increased (p = 0.04). CONCLUSION: A QTc lengthening effect of nocturnal hypoglycemia in children with T1D was documented. HRV changes occurred even before detection of nocturnal hypoglycemia by CGM, which may be useful for hypoglycemia prediction.

Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study.

Modeling of retrospectively collected multi-center data of a rare disease in pediatrics is challenging because laboratory data can stem from several decades measured with different assays. Here we present a retrospective pharmacometrics (PMX) based data analysis of the rare disease congenital hypothyroidism (CH) in newborns and infants. Our overall aim is to develop a model that can be applied to optimize dosing in this pediatric patient population since suboptimal treatment of CH during the first 2 years of life is associated with a reduced intelligence quotient between 10 and 14 years. The first goal is to describe a retrospectively collected dataset consisting of 61 newborns and infants with CH up to 2 years of age. Overall, 505 measurements of free thyroxine (FT4) and 510 measurements of thyrotropin or thyroid-stimulating hormone were available from patients receiving substitution treatment with levothyroxine (LT4). The second goal is to introduce a scale/location-scale normalization method to merge available FT4 measurements since 34 different postnatal age- and assay-specific laboratory reference ranges were applied. This method takes into account the change of the distribution of FT4 values over time, i.e. a transformation from right-skewed towards normality during LT4 treatment. The third goal is to develop a practical and useful PMX model for LT4 treatment to characterize FT4 measurements, which is applicable within a clinical setting. In summary, a time-dependent normalization method and a practical PMX model are presented. Since there is no on-going or planned development of new pharmacological approaches for CH, PMX based modeling and simulation can be leveraged to personalize dosing with the goal to enhance longer-term neurological outcome in children with the rare disease CH.

Co-therapy with S-adenosylmethionine and nicotinamide riboside improves t-cell survival and function in Arts Syndrome (PRPS1 deficiency).

Arts syndrome or phosphoribosyl-pyrophosphate-synthetase-1 (PRPS1) deficiency is caused by loss-of-function mutations in the PRPS1 gene (Xq22.3). PRPS1 is an initial and essential step for the synthesis of the nucleotides of purines, pyrimidines, and nicotinamide. Classically, affected males present with sensorineural hearing loss, optic atrophy, muscular hypotonia, developmental impairment, and recurrent severe respiratory infections early in life. Treatment of a 3-year old boy with S-adenosylmethionine (SAM) replenished erythrocyte purine nucleotides of adenosine and guanosine, while SAM and nicotinamide riboside co-therapy further improved his clinical phenotype as well as T-cell survival and function.

Congenital Hypothyroidism: A 2020-2021 Consensus Guidelines Update-An ENDO-European Reference Network Initiative Endorsed by the European Society for Pediatric Endocrinology and the European Society for Endocrinology.

Background: An ENDO-European Reference Network (ERN) initiative was launched that was endorsed by the European Society for Pediatric Endocrinology and the European Society for Endocrinology with 22 participants from the ENDO-ERN and the two societies. The aim was to update the practice guidelines for the diagnosis and management of congenital hypothyroidism (CH). A systematic literature search was conducted to identify key articles on neonatal screening, diagnosis, and management of primary and central CH. The evidence-based guidelines were graded with the Grading of Recommendations, Assessment, Development and Evaluation system, describing both the strength of recommendations and the quality of evidence. In the absence of sufficient evidence, conclusions were based on expert opinion. Summary: The recommendations include the various neonatal screening approaches for CH as well as the etiology (also genetics), diagnostics, treatment, and prognosis of both primary and central CH. When CH is diagnosed, the expert panel recommends the immediate start of correctly dosed levothyroxine treatment and frequent follow-up including laboratory testing to keep thyroid hormone levels in their target ranges, timely assessment of the need to continue treatment, attention for neurodevelopment and neurosensory functions, and, if necessary, consulting other health professionals, and education of the child and family about CH. Harmonization of diagnostics, treatment, and follow-up will optimize patient outcomes. Lastly, all individuals with CH are entitled to a well-planned transition of care from pediatrics to adult medicine. Conclusions: This consensus guidelines update should be used to further optimize detection, diagnosis, treatment, and follow-up of children with all forms of CH in the light of the most recent evidence. It should be helpful in convincing health authorities of the benefits of neonatal screening for CH. Further epidemiological and experimental studies are needed to understand the increased incidence of this condition.

Copeptin Kinetics and Its Relationship to Osmolality During Rehydration for Diabetic Ketoacidosis in Children.

CONTEXT: Copeptin is a surrogate marker for arginine vasopressin (AVP) release in response to hyperosmolal stimuli such as diabetic ketoacidosis (DKA). OBJECTIVE: The objective of this work is to characterize kinetics of copeptin and osmolality, and their dynamic relationship during rehydration and insulin therapy in children with type 1 diabetes (T1D) and DKA. DESIGN AND SETTING: A prospective, observational, multicenter study was conducted. PATIENTS AND INTERVENTION: Children with T1D admitted for DKA underwent serial serum copeptin and osmolality measurements from start of rehydration at 14 time points during 72 hours. MAIN OUTCOME MEASURES: Measurements included temporal course of copeptin and osmolality (kinetics), relationship between both (dynamics), and association between-subject variability (BSV) (coefficient of variation, CV%). RESULTS: Twenty-eight children (20 newly diagnosed T1D) aged 1 to 16 years were included. Copeptin decreased from 95 pmol/L (95% CI, 55-136 pmol/L) (CV%, 158%) to 9.7 pmol/L (95% CI, 8.1-11.4 pmol/L) (CV%, 31%) with a 50% recovery time (t1/2) of 7.1 hours (range, 5.1-11.5 hours) (114%). Serum osmolality decreased from 321 mOsm/kg (range, 315-327 mOsm/kg) (4%) to 294 mOsm/kg (range, 292-296 mOsm/kg) (1%) with a t1/2 of 4.3 hours (range, 3.0-5.6 hours) (64%). Copeptin levels doubled with each osmolality increase by 15 mOsm/kg (range, 10-21 mOsm/kg) (59%), from 9.8 pmol/L (range, 7.3-12.3 pmol/L) (48%) to 280 mOsm/kg. Copeptin kinetics differed between newly diagnosed and known T1D patients (P = .001), and less between mild vs moderate-severe DKA (P = .04). CONCLUSIONS: First, this study characterized for the first time copeptin kinetics and dynamics in the high hyperosmolar range in children with DKA. Second, it revealed significant differences in copeptin kinetics between newly diagnosed and known T1D patients that may be explained by changes at the osmoreceptor and renal AVP receptor level due to longstanding osmotic diuresis and DKA.