Estimation of human leptin concentration in the subcutaneous adipose and skeletal muscle tissues.

BACKGROUND: Interstitial leptin concentrations in subcutaneous adipose and skeletal muscle tissues were determined by open-flow microperfusion. METHOD: In 12 lean male subjects (age: 25.6 ± 1.1 years), a zero flow rate experiment using different flow rates was applied. Recovery was determined by urea as an internal reference. In the no-net-flux experiments, catheters were perfused with five solutions containing different concentrations of leptin. Concentrations of interstitial leptin were calculated by applying linear regression analysis to perfusate as opposed to sampled leptin concentrations. RESULTS: The zero flow rate protocol showed significantly higher concentrations of leptin in the interstitial fluid of subcutaneous adipose compared to skeletal muscle tissue [36.8 ± 10.32 vs. 7.1 ± 2.5% of the corresponding plasma level (P = 0.018)]. The recovery of urea in the samples was comparable for all catheters [79.4 ± 6.8 vs. 83.0 ± 5.8 of the corresponding plasma level, flow rate of 0.3 µL/min; (P = ns)] and was higher when compared to leptin. In the no-net-flux protocol, the concentration of leptin in subcutaneous adipose tissue was almost identical to plasma [90. 5 ± 7.0%] and the skeletal muscle tissue concentration of leptin was 23.7 ± 2.5% of the corresponding plasma level. CONCLUSION: Open-flow microperfusion enables the estimation of leptin concentrations in subcutaneous adipose and skeletal muscle tissues in humans in vivo. This is the first documentation on the use of open-flow microperfusion to demonstrate that relevant amounts of leptin are also found in skeletal muscle tissue.

Recirculation--a novel approach to quantify interstitial analytes in living tissue by combining a sensor with open-flow microperfusion.

We report a novel approach to quantify interstitial analytes in living tissue by combining open-flow microperfusion (OFM) with a sensor and the re-circulation method. OFM is based on the unrestricted exchange of molecules between the interstitial fluid (ISF) and a perfusion medium through macroscopic perforations that enables direct access to the ISF. By re-circulating the perfusate and monitoring the changes of the analytes' concentration with a sensor, the absolute analyte concentration in the ISF can be calculated. In order to validate the new concept, the absolute electrical conductivity of the ISF was identified in six subjects to be 1.33 ± 0.08 S/m (coefficient of variation CV = 6 %), showing the robustness of this approach. The most striking feature of this procedure is the possibility to monitor several compounds simultaneously by applying different sensors which will allow not only the determination of the concentration of a single substance in vivo but also the simultaneous dynamics of different analytes. This will open new fields in analytical chemistry, pharmacology, as well as clinical experimental research.

Automatic system testing of a decision support system for insulin dosing using Google Android.

Hyperglycaemia in hospitalized patients is a common and costly health care problem. The GlucoTab system is a mobile workflow and decision support system, aiming to facilitate efficient and safe glycemic control of non-critically ill patients. Being a medical device, the GlucoTab requires extensive and reproducible testing. A framework for high-volume, reproducible and automated system testing of the GlucoTab system was set up applying several Open Source tools for test automation and system time handling. The REACTION insulin titration protocol was investigated in a paper-based clinical trial (PBCT). In order to validate the GlucoTab system, data from this trial was used for simulation and system tests. In total, 1190 decision support action points were identified and simulated. Four data points (0.3%) resulted in a GlucoTab system error caused by a defective implementation. In 144 data points (12.1%), calculation errors of physicians and nurses in the PBCT were detected. The test framework was able to verify manual calculation of insulin doses and detect relatively many user errors and workflow anomalies in the PBCT data. This shows the high potential of the electronic decision support application to improve safety of implementation of an insulin titration protocol and workflow management system in clinical wards.

Design of a mobile, safety-critical in-patient glucose management system.

Diabetes mellitus is one of the most widespread diseases in the world. People with diabetes usually have long stays in hospitals and need specific treatment. In order to support in-patient care, we designed a prototypical mobile in-patient glucose management system with decision support for insulin dosing. In this paper we discuss the engineering process and the lessons learned from the iterative design and development phases of the prototype. We followed a user-centered development process, including real-life usability testing from the outset. Paper mock-ups in particular proved to be very valuable in gaining insight into the workflows and processes, with the result that user interfaces could be designed exactly to the specific needs of the hospital personnel in their daily routine.

Safe and Sufficient Glycemic Control by Using a Digital Clinical Decision Support System for Patients With Type 2 Diabetes in a Routine Setting on General Hospital Wards.

The aim was to investigate the applicability of a clinical decision support system in a real-world inpatient setting for patients with type 2 diabetes on general hospital wards.A total of 150 patients with type 2 diabetes requiring subcutaneous insulin therapy were treated with basal-bolus insulin therapy guided by a decision support system (GlucoTab) providing automated workflow tasks and suggestions for insulin dosing to health care professionals.By using the system, a mean daily blood glucose (BG) of 159 ± 32 mg/dL was achieved. 68.8% of measurements were in the target range (70 to <180 mg/dL). The percentage of BG values <40, <70, and ≥300 mg/dL was 0.02%, 2.2%, and 2.3%, respectively. Health care professionals' adherence to suggested insulin doses and workflow tasks was high (>93% and 91%, respectively).The decision support system facilitates safe and efficacious inpatient diabetes care by standardizing treatment workflow and providing decision support for basal-bolus insulin dosing.

Microdialysis based device for continuous extravascular monitoring of blood glucose.

Glycemic control of intensive care patients can be beneficial for this patient group but the continuous determination of their glucose concentration is challenging. Current continuous glucose monitoring systems based on the measurement of interstitial fluid glucose concentration struggle with sensitivity losses, resulting from biofouling or inflammation reactions. Their use as decision support systems for the therapeutic treatment is moreover hampered by physiological time delays as well as gradients in glucose concentration between plasma and interstitial fluid. To overcome these drawbacks, we developed and clinically evaluated a system based on microdialysis of whole blood. Venous blood is heparinised at the tip of a double lumen catheter and pumped through a membrane based micro-fluidic device where protein-free microdialysate samples are extracted. Glucose recovery as an indicator of long term stability was studied in vitro with heparinised bovine blood and remained highly stable for 72 h. Clinical performance was tested in a clinical trial in eight healthy volunteers undergoing an oral glucose tolerance test. Glucose concentrations of the new system and the reference method correlated at a level of 0.96 and their mean relative difference was 1.9 +/- 11.2%. Clinical evaluation using Clark's Error Grid analysis revealed that the obtained glucose concentrations were accurate and clinically acceptable in 99.6% of all cases. In conclusion, results of the technical and clinical evaluation suggest that the presented device delivers microdialysate samples suitable for accurate and long term stable continuous glucose monitoring in blood.

Clinical evaluation of alternative-site glucose measurements in patients after major cardiac surgery.

OBJECTIVE: Tight glycemic control improves outcome in critically ill patients but requires frequent glucose measurements. Subcutaneous adipose tissue (SAT) has been characterized as promising for glucose monitoring in diabetes, but it remains unknown whether it can also be used as an alternative site in critically ill patients. The present study was performed to clinically evaluate the relation of glucose in SAT compared with arterial blood in patients after major cardiac surgery. RESEARCH DESIGN AND METHODS: Forty critically ill patients were investigated at two clinical centers after major cardiac surgery. Arterial blood and SAT microdialysis samples were taken in hourly intervals for a period of up to 48 h. The glucose concentration in dialysate was calibrated using a two-step approach, first using the ionic reference technique to calculate the SAT glucose concentration (SATg) and second using a one-point calibration procedure to obtain a glucose profile comparable to SAT-derived blood glucose (BgSAT). Clinical validation of the data was performed by introducing data analysis based on an insulin titration algorithm. RESULTS: Correlation between dialysate glucose and blood glucose (median 0.80 [interquartile range 0.68-0.88]) was significantly improved using the ionic reference calibration technique (SATg vs.blood glucose 0.90 [0.83-0.94]; P < 0.001). Clinical evaluation of the data indicated that 96.1% of glucose readings from SAT would allow acceptable treatment according to a well-established insulin titration protocol. CONCLUSIONS: The results indicate good correlation between SATg and blood glucose in patients after major cardiac surgery. Clinical evaluation of the data suggests that with minor limitations, glucose from SAT can be used to establish tight glycemic control in this patient group.

A Mobile Computerized Decision Support System to Prevent Hypoglycemia in Hospitalized Patients With Type 2 Diabetes Mellitus.

BACKGROUND: Diabetes management requires complex and interdisciplinary cooperation of health care professionals (HCPs). To support this complex process, IT-support is recommended by clinical guidelines. The aim of this article is to report on results from a clinical feasibility study testing the prototype of a mobile, tablet-based client-server system for computerized decision and workflow support (GlucoTab®) and to discuss its impact on hypoglycemia prevention. METHODS: The system was tested in a monocentric, open, noncontrolled intervention study in 30 patients with type 2 diabetes mellitus (T2DM). The system supports HCPs in performing a basal-bolus insulin therapy. Diabetes therapy, adverse events, software errors and user feedback were documented. Safety, efficacy and user acceptance of the system were investigated. RESULTS: Only 1.3% of blood glucose (BG) measurements were <70 mg/dl and only 2.6% were >300 mg/dl. The availability of the system (97.3%) and the rate of treatment activities documented with the system (>93.5%) were high. Only few suggestions from the system were overruled by the users (>95.7% adherence). Evaluation of the 3 anonymous questionnaires showed that confidence in the system increased over time. The majority of users believed that treatment errors could be prevented by using this system. CONCLUSIONS: Data from our feasibility study show a significant reduction of hypoglycemia by implementing a computerized system for workflow and decision support for diabetes management, compared to a paper-based process. The system was well accepted by HCPs, which is shown in the user acceptance analysis and that users adhered to the insulin dose suggestions made by the system.

Robust PBPK/PD-Based Model Predictive Control of Blood Glucose.

GOAL: Automated glucose control (AGC) has not yet reached the point where it can be applied clinically [3]. Challenges are accuracy of subcutaneous (SC) glucose sensors, physiological lag times, and both inter- and intraindividual variability. To address above issues, we developed a novel scheme for MPC that can be applied to AGC. RESULTS: An individualizable generic whole-body physiology-based pharmacokinetic and dynamics (PBPK/PD) model of the glucose, insulin, and glucagon metabolism has been used as the predictive kernel. The high level of mechanistic detail represented by the model takes full advantage of the potential of MPC and may make long-term prediction possible as it captures at least some relevant sources of variability [4]. Robustness against uncertainties was increased by a control cascade relying on proportional-integrative derivative-based offset control. The performance of this AGC scheme was evaluated in silico and retrospectively using data from clinical trials. This analysis revealed that our approach handles sensor noise with a MARD of 10%-14%, and model uncertainties and disturbances. CONCLUSION: The results suggest that PBPK/PD models are well suited for MPC in a glucose control setting, and that their predictive power in combination with the integrated database-driven (a priori individualizable) model framework will help overcome current challenges in the development of AGC systems. SIGNIFICANCE: This study provides a new, generic, and robust mechanistic approach to AGC using a PBPK platform with extensive a priori (database) knowledge for individualization.

Impact of errors in paper-based and computerized diabetes management with decision support for hospitalized patients with type 2 diabetes. A post-hoc analysis of a before and after study.

OBJECTIVE: Most preventable adverse drug events and medication errors occur during medication ordering. Medication order entry and clinical decision support are available on paper or as computerized systems. In this post-hoc analysis we investigated frequency and clinical impact of blood glucose (BG) documentation- and user-related calculation errors as well as workflow deviations in diabetes management. We aimed to compare a paper-based protocol to a computerized medication management system combined with clinical workflow and decision support. METHODS: Seventy-nine hospitalized patients with type 2 diabetes mellitus were treated with an algorithm driven basal-bolus insulin regimen. BG measurements, which were the basis for insulin dose calculations, were manually entered either into the paper-based workflow protocol (PaperG: 37 patients) or into GlucoTab(®)-a mobile tablet PC based system (CompG: 42 patients). We used BG values from the laboratory information system as a reference. A workflow simulator was used to determine user calculation errors as well as workflow deviations and to estimate the effect of errors on insulin doses. The clinical impact of insulin dosing errors and workflow deviations on hypo- and hyperglycemia was investigated. RESULTS: The BG documentation error rate was similar for PaperG (4.9%) and CompG group (4.0%). In PaperG group, 11.1% of manual insulin dose calculations were erroneous and the odds ratio (OR) of a hypoglycemic event following an insulin dosing error was 3.1 (95% CI: 1.4-6.8). The number of BG values influenced by insulin dosing errors was eightfold higher than in the CompG group. In the CompG group, workflow deviations occurred in 5.0% of the tasks which led to an increased likelihood of hyperglycemia, OR 2.2 (95% CI: 1.1-4.6). DISCUSSION: Manual insulin dose calculations were the major source of error and had a particularly strong influence on hypoglycemia. By using GlucoTab(®), user calculation errors were entirely excluded. The immediate availability and automated handling of BG values from medical devices directly at the point of care has a high potential to reduce errors. Computerized systems facilitate the safe use of more complex insulin dosing algorithms without compromising usability. In CompG group, missed or delayed tasks had a significant effect on hyperglycemia, while in PaperG group insufficient precision of documentation times limited analysis. The use of old BG measurements was clinically less relevant. CONCLUSION: Insulin dosing errors and workflow deviations led to measurable changes in clinical outcome. Diabetes management systems including decision support should address nurses as well as physicians in a computerized way. Our analysis shows that such systems reduce the frequency of errors and therefore decrease the probability of hypo- and hyperglycemia.

Insulin kinetics in type-I diabetes: continuous and bolus delivery of rapid acting insulin.

We investigated insulin lispro kinetics with bolus and continuous subcutaneous insulin infusion (CSII) modes of insulin delivery. Seven subjects with type-1 diabetes treated by CSII with insulin lispro have been studied during prandial and postprandial conditions over 12 hours. Eleven alternative models of insulin kinetics have been proposed implementing a number of putative characteristics. We assessed 1) the effect of insulin delivery mode, i.e., bolus or basal, on the insulin absorption rate, the effects of 2) insulin association state and 3) insulin dose on the rate of insulin absorption, 4) the remote insulin effect on its volume of distribution, 5) the effect of insulin dose on insulin disappearance, 6) the presence of insulin degradation at the injection site, and finally 7) the existence of two pathways, fast and slow, of insulin absorption. An iterative two-stage parameter estimation technique was used. Models were validated through assessing physiological feasibility of parameter estimates, posterior identifiability, and distribution of residuals. Based on the principle of parsimony, best model to fit our data combined the slow and fast absorption channels and included local insulin degradation. The model estimated that 67(53-82)% [mean (interquartile range)] of delivered insulin passed through the slow absorption channel [absorption rate 0.011(0.004-0.029) min(-1)] with the remaining 33% passed through the fast channel [absorption rate 0.021(0.011-0.040) min(-1)]. Local degradation rate was described as a saturable process with Michaelis-Menten characteristics [VMAX = 1.93(0.62 - 6.03) mU min(-1), KM = 62.6(62.6 - 62.6) mU]. Models representing the dependence of insulin absorption rate on insulin disappearance and the remote insulin effect on its volume of distribution could not be validated suggesting that these effects are not present or cannot be detected during physiological conditions.

Taking a Closer Look--Continuous Glucose Monitoring in Non-Critically Ill Hospitalized Patients with Type 2 Diabetes Mellitus Under Basal-Bolus Insulin Therapy.

BACKGROUND: Inpatient glucose management is based on four daily capillary blood glucose (BG) measurements. The aim was to test the capability of continuous glucose monitoring (CGM) for assessing the clinical impact and safety of basal-bolus insulin therapy in non-critically ill hospitalized patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: Eighty-four patients with T2DM (age, 68±10 years; glycosylated hemoglobin, 72±28 mmol/mol; body mass index, 31±7 kg/m(2)) were treated with basal-bolus insulin. CGM was performed with the iPro(®)2 system (Medtronic MiniMed, Northridge, CA) and calibrated retrospectively. RESULTS: A remarkable consistency between CGM and BG measurements and therapy improvement was shown over the study period of 501 patient-days. The number of CGM and BG measurements (CGM/BG) in the range from 3.9-10 mmol/L increased from 67.7%/67.2% (on Day 1) to 77.5%/78.6% (on the last day) (P<0.04). The number of low glycemic episodes (3.3 to <3.9 mmol/L) during nighttime detected by CGM was 15-fold higher, and the number of episodes >13.9 mmol/L detected by CGM during night was 12.5-fold higher than the values from the BG measurements. Ninety-nine percent of data points were in the clinically accurate or acceptable Clarke Error Grid Zones A+B, and the relative numbers of correctly identified episodes of <3.9 and >13.9 mmol/L detected by CGM (sensitivity) were 47.3% and 81.5%, respectively. CONCLUSIONS: Our data exhibit a good agreement between overall CGM and BG measurements, but there were a high number of missed hypo- and hyperglycemic episodes with BG measurements, particularly during nighttime. Overall assessment of glycemic control using CGM is feasible, whereas the use of CGM for individualized therapy decisions needs further improvement.

Standardized Glycemic Management with a Computerized Workflow and Decision Support System for Hospitalized Patients with Type 2 Diabetes on Different Wards.

BACKGROUND: This study investigated the efficacy, safety, and usability of standardized glycemic management by a computerized decision support system for non-critically ill hospitalized patients with type 2 diabetes on four different wards. MATERIALS AND METHODS: In this open, noncontrolled intervention study, glycemic management of 99 patients with type 2 diabetes (62% acute admissions; 41 females; age, 67±11 years; hemoglobin A1c, 65±21 mmol/mol; body mass index, 30.4±6.5 kg/m(2)) on clinical wards (Cardiology, Endocrinology, Nephrology, Plastic Surgery) of a tertiary-care hospital was guided by GlucoTab(®) (Joanneum Research GmbH [Graz, Austria] and Medical University of Graz [Graz, Austria]), a mobile decision support system providing automated workflow support and suggestions for insulin dosing to nurses and physicians. RESULTS: Adherence to insulin dosing suggestions was high (96.5% bolus, 96.7% basal). The primary outcome measure, percentage of blood glucose (BG) measurements in the range of 70-140 mg/dL, occurred in 50.2±22.2% of all measurements. The overall mean BG level was 154±35 mg/dL. BG measurements in the ranges of 60-70 mg/dL, 40-60 mg/dL, and <40 mg/dL occurred in 1.4%, 0.5%, and 0.0% of all measurements, respectively. A regression analysis showed that acute admission to the Cardiology Ward (+30 mg/dL) and preexisting home insulin therapy (+26 mg/dL) had the strongest impact on mean BG. Acute admission to other wards had minor effects (+4 mg/dL). Ninety-one percent of the healthcare professionals felt confident with GlucoTab, and 89% believed in its practicality and 80% in its ability to prevent medication errors. CONCLUSIONS: An efficacious, safe, and user-accepted implementation of GlucoTab was demonstrated. However, for optimized personalized patient care, further algorithm modifications are required.

Interstitial glucose kinetics in subjects with type 1 diabetes under physiologic conditions.

We investigated the dynamic relationship between interstitial glucose (IG) in the subcutaneous adipose tissue and plasma glucose (PG) during physiologic conditions in type 1 diabetes mellitus (T1DM). Nine subjects with T1DM (5/4 M/F; age, 33 +/- 13 years; body mass index, 26.6 +/- 4.3 kg/m(2); glycosylated hemoglobin [HbA(1c)], 8.6% +/- 0.9%; mean +/- SD) treated by continuous subcutaneous insulin infusion (CSII) with insulin lispro were studied over 12 hours after a standard meal (40 g carbohydrate [CHO]) and prandial insulin. IG was measured by open flow microperfusion. Nine compartment models were postulated to account for temporal variations in the IG/PG ratio. The models differed in the inclusion of physiologically motivated alterations of pathways entering/leaving the IG compartment in the adipose tissue. The best model included zero order (constant) glucose disposal from the interstitial fluid (ISF) and insulin-stimulated glucose transfer from plasma to the ISF. The former effect is expressed by a positive association between the IG/PG ratio and PG, eg, a decrease in PG from 9 to 3.3 mmol/L lowers the IG/PG ratio by 0.1. The latter effect results in the IG/PG ratio to be increased by 0.03 per 10 mU/L of plasma insulin. We were not able to detect the stimulatory effect of insulin on glucose disappearance from the ISF. In conclusion, we developed and quantified a model of IG kinetics in the adipose tissue applicable to physiologic conditions in subjects with T1DM.

Closing the loop: the adicol experience.

The objective of the project Advanced Insulin Infusion using a Control Loop (ADICOL) was to develop a treatment system that continuously measures and controls the glucose concentration in subjects with type 1 diabetes. The modular concept of the ADICOL's extracorporeal artificial pancreas consisted of a minimally invasive subcutaneous glucose system, a handheld PocketPC computer, and an insulin pump (D-Tron, Disetronic, Burgdorf, Switzerland) delivering subcutaneously insulin lispro. The present paper describes a subset of ADICOL activities focusing on the development of a glucose controller for semi-closed-loop control, an in silico testing environment, clinical testing, and system integration. An incremental approach was adopted to evaluate experimentally a model predictive glucose controller. A feasibility study was followed by efficacy studies of increasing complexity. The ADICOL project demonstrated feasibility of a semi-closed-loop glucose control during fasting and fed conditions with a wearable, modular extracorporeal artificial pancreas.

Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes.

A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously administered short-acting insulin Lispro and gut absorption. The controller uses Bayesian parameter estimation to determine time-varying model parameters. Moving target trajectory facilitates slow, controlled normalization of elevated glucose levels and faster normalization of low glucose values. The predictive capabilities of the model have been evaluated using data from 15 clinical experiments in subjects with type 1 diabetes. The experiments employed intravenous glucose sampling (every 15 min) and subcutaneous infusion of insulin Lispro by insulin pump (modified also every 15 min). The model gave glucose predictions with a mean square error proportionally related to the prediction horizon with the value of 0.2 mmol L(-1) per 15 min. The assessment of clinical utility of model-based glucose predictions using Clarke error grid analysis gave 95% of values in zone A and the remaining 5% of values in zone B for glucose predictions up to 60 min (n = 1674). In conclusion, adaptive nonlinear model predictive control is promising for the control of glucose concentration during fasting conditions in subjects with type 1 diabetes.

In vivo evaluation of a chip based near infrared sensor for continuous glucose monitoring.

In this paper we describe the concept and in vivo results of a minimally invasive, chip-based near infrared (NIR) sensor, combined with microdialysis, for continuous glucose monitoring. The sensor principle is based on difference absorption spectroscopy in selected wavelength bands of the near infrared spectrum (1300 nm, 1450 nm, and 1550 nm) in the 1st overtone band. In vitro measurements revealed a linear relationship between glucose concentration and the integrated difference spectroscopy signal with a coefficient of determination of 99% in the concentration range of 0-400mg/dl. The absolute error in this case is about 5mg/dl, corresponding to a relative error of about 5% for glucose concentrations larger than 50mg/dl and about 12% in the hypoglycemic range (<50mg/dl). In vivo measurements on 10 patients showed that the NIR-CGM sensor data reflects the blood reference values adequately, if a proper calibration and a signal drift correction is applied. The mean MARE (mean absolute relative error) value taken over all patient data is 13.8%. The best achieved MARE value is at 4.8%, whereas the worst lies at 25.8%, leading to a standard deviation of 5.5%.

Failure to control hyperglycemia in noncritically ill diabetes patients despite standard glycemic management in a hospital setting.

BACKGROUND: Successful control of hyperglycemia has been shown to improve outcomes for diabetes patients in a clinical setting. We assessed the quality of physician-based glycemic management in two general wards, considering the most recent recommendations for glycemic control for noncritically ill patients (<140 mg/dl for premeal glucose). METHODS: Quality of glycemic management of 50 patients in two wards (endocrinology, cardiology) was assessed retrospectively by analyzing blood glucose (BG) levels, the glycemic management effort, and the online questionnaire. RESULTS: Glycemic control was clearly above the recommended target (mean BG levels: endocrinology: 175 ± 62 mg/dl; cardiology: 186 ± 68 mg/dl). When comparing the first half with the second half of the hospital stay, we found no difference in glycemic control (endocrinology: 168 ± 32 vs 164 ± 42 mg/dl, P = .67; cardiology: 174 ± 36 mg/dl vs 170 ± 42 mg/dl, P =.51) and in insulin dose (endocrinology: 15 ± 14 IU vs 15 ± 13 IU per day, P = .87; cardiology: 27 ± 17 IU vs 27 ± 18 IU per day, P = .92), despite frequent BG measurements (endocrinology: 2.7 per day; cardiology: 3.2 per day). A lack of clearly defined BG targets was indicated in the questionnaire. CONCLUSION: The recommended BG target range was not achieved in both wards. Analysis of routine glycemic management demonstrated considerable glycemic management effort, but also a lack of translation into adequate insulin therapy. Implementation of corrective measures, such as structured treatment protocols, is essential.

Dermal PK/PD of a lipophilic topical drug in psoriatic patients by continuous intradermal membrane-free sampling.

BACKGROUND: Methodologies for continuous sampling of lipophilic drugs and high-molecular solutes in the dermis are currently lacking. We investigated the feasibility of sampling a lipophilic topical drug and the locally released biomarker in the dermis of non-lesional and lesional skin of psoriatic patients over 25h by means of membrane-free dermal open-flow microperfusion probes (dOFM) and novel wearable multi-channel pumps. METHODS: Nine psoriatic patients received a topical p-38 inhibitor (BCT194, 0.5% cream) on a lesional and a non-lesional application site once daily for 8 days. Multiple dOFM sampling was performed for 25 h from each site on day 1 and day 8. Patients were mobile as dOFM probes were operated by a novel light-weight push-pull pump. Ultrasound was used to verify intradermal probe placement, cap-LC-MS/MS for BCT194 and ELISA for TNFα analysis. RESULTS: dOFM was well tolerated and demonstrated significant drug concentrations in lesional as well as non-lesional skin after 8 days, but did not show significant differences between tissues. On day 8, TNFα release following probe insertion was significantly reduced compared to day 1. CONCLUSIONS: Novel membrane-free probes and wearable multi-channel pumps allowed prolonged intradermal PK/PD profiling of a lipophilic topical drug in psoriatic patients. This initial study shows that dOFM overcomes limitations of microdialysis sampling methodology, and it demonstrates the potential for PK/PD studies of topical products and formulations in a clinical setting.

Prediction of glucose concentration in post-cardiothoracic surgery patients using continuous glucose monitoring.

OBJECTIVE: This study evaluated the predictive capability of simple linear extrapolation of continuous glucose data in postsurgical patients undergoing intensive care. METHODS: Twenty patients, both with or without an established diagnosis of diabetes mellitus, scheduled to undergo cardiothoracic surgery were included. Glucose was continuously monitored in the intensive care unit with a microdialysis-based subcutaneous glucose monitoring system. The prediction horizon (PH) with respect to a given glucose reading was calculated by extrapolating the linear trend of the glucose signal and subjected to both analytical and clinical assessment (by calculation of the average duration of consecutive positive and negative glucose signal trends, the root mean squared error [RMSE], and by insulin titration error grid [ITEG] analysis, respectively). RESULTS: In total, 609 h of continuous glucose data from 17 patients were analyzed. The average duration of consecutive positive and negative glucose signal trends was 7.97 (3.99-19.98) min (median, interquartile range). An increase in the RMSE of 0.5 mmol/L (9 mg/dL) was associated with a PH of 37 min. A strong increase in the number of data points in the unacceptable violation zone of the ITEG was associated with a PH of approximately 20 min. CONCLUSIONS: Our data provide evidence that simple linear extrapolation of glucose trend information obtained by continuous glucose monitoring can be used to predict the course of glycemia in critically ill patients for up to 20-30 min. This "glimpse into the future" can be used to proactively prevent the occurrence of adverse events.