Johannes Plank

Long-term evaluation of a structured outpatient education programme for intensified insulin therapy in patients with Type 1 diabetes: a 12-year follow-up

Aims/hypothesisThis study was conducted to evaluate the long-term outcome of a structured outpatient diabetes teaching and treatment programme (DTTP) for intensified insulin therapy in patients with Type 1 diabetes, which aims to improve metabolic control without increasing the risk of severe hypoglycaemia.MethodsAll 123 diabetic outpatients (age 41±14 years; 64 women; BMI 23.5±3.1; diabetes duration 17±11 years; HbA1c 7.9±1.6%; 32 patients with a history of severe hypoglycaemia; 18 with overt nephropathy; 22 with proliferative retinopathy) who participated in the DTTP between June 1989 and June 1990 were invited for follow-up visits after 3, 6 and 12 years.ResultsOut of the 123 patients, 11 died during the follow-up period, two were lost for follow-up, and one was not willing to participate in re-evaluation after 12 years. Mean HbA1c levels decreased from 7.9±1.6% to 7.1±1.2% (p<0.01) after 3 years, and were 7.8±1.5% (NS) and 7.8±1.2% (NS) after 6 and 12 years respectively. Frequency of hypoglycaemia decreased from 0.49 episodes per patient per year to 0.14 after 3 years (p<0.01), 0.19 after 6 years (p<0.01) and 0.16 after 12 years (p<0.01). Of the participants, 41% were able to lower HbA1c levels without episodes of severe hypoglycaemia and to maintain this improvement at all follow-up visits over the 12-year period. At follow-up, intensified insulin therapy was carried out by 94% of the patients.Conclusions/interpretationA sustained reduction of the incidence of severe hypoglycaemia was observed in patients with Type 1 diabetes after participation in a structured outpatient DTTP over a 12-year period.

A simulation model of glucose regulation in the critically ill

Focused research is underway to improve the delivery of tight glycaemic control at the intensive care unit. A major component is the development of safe, efficacious and effective insulin titration algorithms, which are normally evaluated in time-consuming resource-demanding clinical studies. Simulation studies with virtual critically ill patients can substantially accelerate the development process. For this purpose, we created a model of glucoregulation in the critically ill. The model includes five submodels: a submodel of endogenous insulin secretion, a submodel of insulin kinetics, a submodel of enteral glucose absorption, a submodel of insulin action and a submodel of glucose kinetics. Model parameters are estimated utilizing prior knowledge and data collected routinely at the intensive care unit to represent the high intersubject and temporal variation in insulin needs in the critically ill. Bayesian estimation combined with the regularization method is used to estimate (i) time-invariant model parameters and (ii) a time-varying parameter, the basal insulin concentration, which represents the temporal variation in insulin sensitivity. We propose a validation process to validate virtual patients developed for the purpose of testing glucose controllers. The parameter estimation and the validation are exemplified using data collected in six critically ill patients treated at a medical intensive care unit. In conclusion, a novel glucoregulatory model has been developed to create a virtual population of critically ill facilitating in silico testing of glucose controllers at the intensive care unit.

Meta-analysis of short-acting insulin analogues in adult patients with type 1 diabetes: continuous subcutaneous insulin infusion versus injection therapy

Aims/hypothesisThis study aimed to compare the effect of treatment with short-acting insulin (SAI) analogues versus structurally unchanged short-acting insulin (regular insulin) on glycaemic control and on the risk of hypoglycaemic episodes in type 1 diabetic patients using different insulin treatment strategies.MethodsWe performed a meta-analysis of 27 randomised controlled trials that compared the effect of SAI analogues with regular insulin in patients with type 1 diabetes mellitus. The treatments were administered either via continuous subcutaneous insulin infusion (CSII) or by conventional intensified insulin therapy (IIT) with short-acting insulin injections before meals and basal insulin administered once or twice daily in most cases.ResultsHbA1c levels were reported for 20 studies. For studies using CSII, the weighted mean difference between values obtained using SAI analogues and regular insulin was −0.19% (95% CI: −0.27 to −0.12), whereas the corresponding value for injection studies was −0.08% (95% CI: −0.15 to −0.02). For the analysis of overall hypoglycaemia, we used the results from nine studies that reported the mean frequency of hypoglycaemic episodes per patient per month. For studies using CSII, the standardised mean difference between SAI analogues and regular insulin was −0.07 (95% CI: −0.43 to 0.28), whereas for IIT studies the corresponding value was −0.04 (95% CI: −0.24 to 0.16).Conclusions/interpretationTaking into consideration the low quality of the trials included, we can conclude that use of a short-acting insulin analogue in CSII therapy provides a small, but statistically significant improvement in glycaemic control compared with regular insulin. An even smaller effect was obtained with the use of ITT. The rate of overall hypoglycaemic episodes was not significantly reduced with short-acting insulin analogues in either injection regimen.

Plasma N‐terminal pro‐brain natriuretic peptide in Type 1 diabetic patients with and without diabetic nephropathy

Aims Plasma N‐terminal pro‐brain natriuretic peptide (NT proBNP) is produced and released from cardiac ventricles; it is elevated in patients with heart failure, hypertension and chronic renal failure. This study aimed to examine the plasma levels of NT proBNP and their relationship in Type 1 diabetic patients with and without diabetic nephropathy.

Angiotensin receptor blockers as anti-hypertensive treatment for patients with diabetes mellitus: meta-analysis of controlled double-blind randomized trials.

Aims  To assess the evidence for possible reduction of all‐cause mortality, cardiovascular morbidity and mortality, and end‐stage renal disease in diabetic patients treated with angiotensin II type 1 receptor blockers (ARBs) as an anti‐hypertensive treatment.

Efficacy and Safety of Glucose Control with Space GlucoseControl in the Medical Intensive Care Unit—An Open Clinical Investigation

BACKGROUND We aimed to investigate the performance of the Space GlucoseControl system (SGC) (B. Braun, Melsungen, Germany) in medical critically ill patients. The SGC is a nurse-driven, computer-assisted device for glycemic control combining infusion pumps with the enhanced Model Predictive Control algorithm. SUBJECTS AND METHODS The trial was designed as a single-center, open clinical investigation in a nine-bed medical intensive care unit in a tertiary center in Graz, Austria. Efficacy was assessed by percentage of time within the target range (4.4-8.3 mmol/L; primary end point), mean blood glucose, and sampling interval. Safety was assessed by the number of hypoglycemic episodes (≤2.2 mmol/L). RESULTS Twenty mechanically ventilated patients (age, 63±16 years; body mass index, 31.0±10.7 kg/m(2); Acute Physiology and Chronic Health Evaluation II score, 25.4±6.3; 14 males; six with diabetes) were included for a period of 7.0±3.6 days. Time within target range was 83.4±8.9% (mean±SD), and mean arterial blood glucose was 6.8±0.4 mmol/L. No severe hypoglycemic episodes (<2.2 mmol/L) occurred, and the percentage of time within 2.2 and 3.3 mmol/L was low (0.03±0.07%). The sampling interval was 2.0±0.4 h. The mean insulin dose was 93.5±80.1 IU/day, and the adherence to the given insulin dose advice was high (98.3%). A total of 11 unintended therapy interruptions (0.08 events/treatment day) caused by software problems occurred in four patients. CONCLUSIONS SGC is a safe and efficient method to control blood glucose in critically ill patients in the medical intensive care unit.

Evaluation of implementation of a fully automated algorithm (enhanced model predictive control) in an interacting infusion pump system for establishment of tight glycemic control in medical intensive care unit patients.

Background: The objective of this study was to investigate the performance of a newly developed decision support system for the establishment of tight glycemic control in medical intensive care unit (ICU) patients for a period of 72 hours. Methods: This was a single-center, open, non-controlled feasibility trial including 10 mechanically ventilated ICU patients. The CS-1 decision support system (interacting infusion pumps with integrated enhanced model predictive control algorithm and user interface) was used to adjust the infusion rate of administered insulin to normalize blood glucose. Efficacy and safety were assessed by calculating the percentage of values within the target range (80–110 mg/dl), hyperglycemic index, mean glucose, and hypoglycemic episodes (<40 mg/dl). Results: The percentage of values in time in target was 47.0% (±13.0). The average blood glucose concentration and hyperglycemic index were 109 mg/dl (±13) and 10 mg/dl (±9), respectively. No hypoglycemic episode (<40 mg/dl) was detected. Eleven times (1.5% of all given advice) the nurses did not follow and, thus, overruled the advice of the CS-1 system. Several technical malfunctions of the device (repetitive error messages and missing data in the data log) due to communication problems between the new hardware components are shortcomings of the present version of the device. As a consequence of these technical failures of system integration, treatment had to be stopped ahead of schedule in three patients. Conclusions: Despite technical malfunctions, the performance of this prototype CS-1 decision support system was, from a clinical point of view, already effective in maintaining tight glycemic control. Accordingly, and with technical improvement required, the CS-1 system has the capacity to serve as a reliable tool for routine establishment of glycemic control in ICU patients.

Hospital Glucose Control: Safe and Reliable Glycemic Control Using Enhanced Model Predictive Control Algorithm in Medical Intensive Care Unit Patients

BACKGROUND The aim of this study was to investigate the performance of the enhanced Model Predictive Control (eMPC) algorithm for glycemic control in medical critically ill patients for the whole length of intensive care unit (ICU) stay. METHODS The trial was designed as a single-center, open, noncontrolled clinical investigation in a nine-bed medical ICU in a tertiary teaching hospital. In 20 patients, blood glucose (BG) was controlled with a laptop-based bedside version of the eMPC. Efficacy was assessed by percentage of time within the target range (4.4-6.1 mM; primary end point), mean BG, and BG sampling interval. Safety was assessed by the number of severe hypoglycemic episodes (<2.2 mM). RESULTS Twenty patients (69 +/- 11 years old; body mass index, 27.4 +/- 4.5 kg/m(2); APACHE II, 25.5 +/- 5.2) were included for a period of 7.3 days (median; interquartile range, 4.4-10.2 days) in the study. Time within target range was 58.12 +/- 10.05% (mean +/- SD). For all patients with at least 7 days in the ICU, there was no statistically significant difference between the daily mean percentage of times in target range in respect of the averages. Mean arterial BG was 5.8 +/- 0.5 mM, insulin requirement was 101.3 +/- 50.7 IU/day, and mean carbohydrate intake (enteral and parenteral nutrition) was 176.4 +/- 61.9 g/day. Three hypoglycemic episodes occurred in three subjects, corresponding to a rate of 0.02 per treatment day. CONCLUSIONS In our single-center, noncontrolled study the eMPC algorithm was a safe and reliable method to control BG in critically medical ICU patients for the whole length of ICU stay.

Microdialysis--a versatile technology to perform metabolic monitoring in diabetes and critically ill patients.

Continuous subcutaneous glucose monitoring has been tested in type 1 diabetes (T1D). Since in critically ill patients vascular access is granted vascular microdialysis may be preferential. To test this hypothesis comparative accuracy data for microdialysis applied for peripheral venous and subcutaneous glucose monitoring was obtained in experiments in T1D patients. Twelve T1D patients were investigated for up to 30 h. Extracorporeal vascular (MDv) and subcutaneous microdialysis (MDs) was performed. Microdialysis samples were collected in 15-60 min intervals, analyzed for glucose and calibrated to reference. MDv and MDs glucose levels were compared against reference. Median absolute relative difference was 14.0 (5.0; 28.0)% (MDv) and 9.2 (4.4; 18.4)% (MDs). Clarke Error Grid analysis showed that 100% (MDv) and 98.8% (MDv) were within zones A and B. Extracorporeal vascular and standard subcutaneous microdialysis indicated similar performance in T1D. We suggest microdialysis as a versatile technology for metabolite monitoring in subcutaneous tissue and whole blood.

Evaluating Glycemic Control Algorithms by Computer Simulations

BACKGROUND Numerous guidelines and algorithms exist to achieve glycemic control. Their strengths and weaknesses are difficult to assess without head-to-head comparison in time-consuming clinical trials. We hypothesized that computer simulations may be useful. METHODS Two open-label randomized clinical trials were replicated using computer simulations. One study compared performance of the enhanced model predictive control (eMPC) algorithm at two intensive care units in the United Kingdom and Belgium. The other study compared three glucose control algorithms-eMPC, Matias (the absolute glucose protocol), and Bath (the relative glucose change protocol)-in a single intensive care unit. Computer simulations utilized a virtual population of 56 critically ill subjects derived from routine data collected at four European surgical and medical intensive care units. RESULTS In agreement with the first clinical study, computer simulations reproduced the main finding and discriminated between the two intensive care units in terms of the sampling interval (1.3 h vs. 1.8 h, United Kingdom vs. Belgium; P < 0.01). Other glucose control metrics were comparable between simulations and clinical results. The principal outcome of the second study was also reproduced. The eMPC demonstrated better performance compared with the Matias and Bath algorithms as assessed by the time when plasma glucose was in the target range between 4.4 and 6.1 mmol/L (65% vs. 43% vs. 42% [P < 0.001], eMPC vs. Matias vs. Bath) without increasing the risk of severe hypoglycemia. CONCLUSIONS Computer simulations may provide resource-efficient means for preclinical evaluation of algorithms for glycemic control in the critically ill.