The management of diabetic ketoacidosis in children

The object of this review is to provide the definitions, frequency, risk factors, pathophysiology, diagnostic considerations, and management recommendations for diabetic ketoacidosis (DKA) in children and adolescents, and to convey current knowledge of the causes of permanent disability or mortality from complications of DKA or its management, particularly the most common complication, cerebral edema (CE). DKA frequency at the time of diagnosis of pediatric diabetes is 10%–70%, varying with the availability of healthcare and the incidence of type 1 diabetes (T1D) in the community. Recurrent DKA rates are also dependent on medical services and socioeconomic circumstances. Management should be in centers with experience and where vital signs, neurologic status, and biochemistry can be monitored with sufficient frequency to prevent complications or, in the case of CE, to intervene rapidly with mannitol or hypertonic saline infusion. Fluid infusion should precede insulin administration (0.1 U/kg/h) by 1–2 hours; an initial bolus of 10–20 mL/kg 0.9% saline is followed by 0.45% saline calculated to supply maintenance and replace 5%–10% dehydration. Potassium (K) must be replaced early and sufficiently. Bicarbonate administration is contraindicated. The prevention of DKA at onset of diabetes requires an informed community and high index of suspicion; prevention of recurrent DKA, which is almost always due to insulin omission, necessitates a committed team effort

Multiplicative Surrogate Standard Deviation: A Group Metric for the Glycemic Variability of Individual Hospitalized Patients

Objective: Group metrics are described to quantify blood glucose (BG) variability of hospitalized patients. Methods: The “multiplicative surrogate standard deviation” (MSSD) is the reverse-transformed group mean of the standard deviations (SD) of the logarithmically-transformed blood glucose (BG) data set of each patient. The “geometric group mean” (GGM) is the reverse-transformed group mean of the means of the logarithmically-transformed BG data set of each patient. Before reverse-transformation is performed, the mean of means and mean of SD’s each has its own SD, which becomes a multiplicative standard deviation (MSD) after reverse-transformation. Statistical predictions and comparisons of parametric or nonparametric tests remain valid after reverse-transformation. A subset of a previously-published BG data set of 20 critically ill patients from the first 72 hr of treatment under the SPRINT protocol was transformed logarithmically. After rank-ordering according to the mean of the SD of the logarithmically-transformed BG data of each patient, the cohort was divided into 2 equal groups, those having lower or higher variability. Results: For the entire cohort, the GGM was 106 mg/dL (÷/× 1.07), and MSSD was 1.24 (÷/× 1.07). For the subgroups having lower and higher variability respectively, the GGM in mg/dL did not differ, 104(÷/× 1.07) vs. 109 (÷/× 1.07), but the MSSD differed, 1.17 (÷/× 1.03) vs. 1.31 (÷/× 1.05), p = 0.00004. Conclusion: By using the MSSD with its MSD, groups can be characterized and compared according to glycemic variability of individual patient members

Lixisenatide reduces glycaemic variability in insulin-treated patients with type 2 diabetes

Chronic hyperglycaemia and glucose variability are associated with the development of chronic diabetes-related complications. We conducted a pooled analysis of patient-level data from three 24-week, randomized, phase III clinical trials to evaluate the impact of lixisenatide (LIXI) on glycaemic variability (GV) vs placebo as add-on to basal insulin. The main outcome GV measures were standard deviation (s.d.), mean amplitude of glycaemic excursions (MAGE), mean absolute glucose (MAG) level, area under the curve for fasting glucose (AUC-F), and high (HBGI) and low blood glucose index (LBGI). The change in GV metrics over 24 weeks and relationships among baseline GV, patient characteristics and outcomes were assessed. Data were pooled from 1198 patients (665 LIXI, 533 placebo). Values for s.d., MAG level, MAGE, HBGI, and AUC-F significantly decreased with LIXI vs placebo, while LBGI values were unchanged. Higher baseline GV measures correlated with older age, longer type 2 diabetes duration, lower body mass index, higher baseline glycated/haemogobin, greater reduction in postprandial glucose (PPG) level, and higher rates of symptomatic hypoglycaemia. These data show that LIXI added to basal insulin significantly reduced GV and PPG excursions vs placebo, without increasing the risk of hypoglycaemia (LBGI). © 2017 The Authors. Diabetes, Obesity and Metabolism published by John Wiley and Sons Ltd

Lixisenatide reduces glycaemic variability in insulin-treated patients with type 2 diabetes

Chronic hyperglycaemia and glucose variability are associated with the development of chronic diabetes-related complications. We conducted a pooled analysis of patient-level data from three 24-week, randomized, phase III clinical trials to evaluate the impact of lixisenatide (LIXI) on glycaemic variability (GV) vs placebo as add-on to basal insulin. The main outcome GV measures were standard deviation (s.d.), mean amplitude of glycaemic excursions (MAGE), mean absolute glucose (MAG) level, area under the curve for fasting glucose (AUC-F), and high (HBGI) and low blood glucose index (LBGI). The change in GV metrics over 24 weeks and relationships among baseline GV, patient characteristics and outcomes were assessed. Data were pooled from 1198 patients (665 LIXI, 533 placebo). Values for s.d., MAG level, MAGE, HBGI, and AUC-F significantly decreased with LIXI vs placebo, while LBGI values were unchanged. Higher baseline GV measures correlated with older age, longer type 2 diabetes duration, lower body mass index, higher baseline glycated/haemogobin, greater reduction in postprandial glucose (PPG) level, and higher rates of symptomatic hypoglycaemia. These data show that LIXI added to basal insulin significantly reduced GV and PPG excursions vs placebo, without increasing the risk of hypoglycaemia (LBGI). © 2017 The Authors. Diabetes, Obesity and Metabolism published by John Wiley and Sons Ltd

Case-control Investigation of Previously Undiagnosed Diabetes in the Critically Ill

Context: The outcome of patients requiring intensive care can be influenced by the presence of previously undiagnosed diabetes (undiagDM). Objective: This work aimed to define the clinical characteristics, glucose control metrics, and outcomes of patients admitted to the intensive care unit (ICU) with undiagDM, and compare these to patients with known DM (DM). Methods: This case-control investigation compared undiagDM (glycated hemoglobin A1c [HbA1c] ≥ 6.5%, no history of diabetes) to patients with DM. Glycemic ratio (GR) was calculated as the quotient of mean ICU blood glucose (BG) and estimated preadmission glycemia, based on HbA1c ([28.7 × HbA1c]-46.7mg/dL). GR was analyzed by bands: less than 0.7, 0.7 to less than or equal to 0.9, 0.9 to less than 1.1, and greater than or equal to 1.1. Risk-adjusted mortality was represented by the Observed:Expected mortality ratio (OEMR), calculated as the quotient of observed mortality and mortality predicted by the severity of illness (APACHE IV prediction of mortality). Results: Of 5567 patients 294 (5.3%) were undiagDM. UndiagDM had lower ICU mean BG (P <. 0001) and coefficient of variation (P <. 0001) but similar rates of hypoglycemia (P =. 08). Mortality and risk-adjusted mortality were similar in patients with GR less than 1.1 comparing undiagDM and DM. However, for patients with GR greater than or equal to 1.1, mortality (38.5% vs 10.3% [P =. 0072]) and risk-adjusted mortality (OEMR 1.18 vs 0.52 [P <. 0001]) were higher in undiagDM than in DM. Conclusion: These data suggest that DM patients may develop tolerance to hyperglycemia that occurs during critical illness, a protective mechanism not observed in undiagDM, for whom hyperglycemia remains strongly associated with higher risk of mortality. These results may shed light on the natural history of diabetes.SCOPUS: ar.jinfo:eu-repo/semantics/publishe