Biomedical subjects

Thomas Lotz

Publications and source records attributed to Thomas Lotz.

7 recordsLinked to original sources

PubMed2006

Integral-based filtering of continuous glucose sensor measurements for glycaemic control in critical care.

Hyperglycaemia is prevalent in critical illness and increases the risk of further complications and mortality, while tight control can reduce mortality up to 43%. Adaptive control methods are capable of highly accurate, targeted blood glucose regulation using limited numbers of manual measurements due to patient discomfort and labour intensity. Therefore, the option to obtain greater data density using emerging continuous glucose sensing devices is attractive. However, the few such systems currently available can have errors in excess of 20-30%. In contrast, typical bedside testing kits have errors of approximately 7-10%. Despite greater measurement frequency larger errors significantly impact the resulting glucose and patient specific parameter estimates, and thus the control actions determined creating an important safety and performance issue. This paper models the impact of the continuous glucose monitoring system (CGMS, Medtronic, Northridge, CA) on model-based parameter identification and glucose prediction. An integral-based fitting and filtering method is developed to reduce the effect of these errors. A noise model is developed based on CGMS data reported in the literature, and is slightly conservative with a mean Clarke Error Grid (CEG) correlation of R=0.81 (range: 0.68-0.88) as compared to a reported value of R=0.82 in a critical care study. Using 17 virtual patient profiles developed from retrospective clinical data, this noise model was used to test the methods developed. Monte-Carlo simulation for each patient resulted in an average absolute 1-h glucose prediction error of 6.20% (range: 4.97-8.06%) with an average standard deviation per patient of 5.22% (range: 3.26-8.55%). Note that all the methods and results are generalizable to similar applications outside of critical care, such as less acute wards and eventually ambulatory individuals. Clinically, the results show one possible computational method for managing the larger errors encountered in emerging continuous blood glucose sensors, thus enabling their more effective use in clinical glucose regulation studies.

Adult↗

PubMed2006

A simple insulin-nutrition protocol for tight glycemic control in critical illness: development and protocol comparison.

BACKGROUND: Hyperglycemia is prevalent in critical care, and tight control can significantly reduce mortality. However, current protocols have been considered taxing to administer and may require extra staff. In addition, increased insulin resistance and saturation effects limit the level of control possible using insulin alone. Thus, regulating both insulin and exogenous nutritional inputs is required to control blood glucose. METHODS: A robust, easy-to-use protocol ["SPRINT" (Specialized Relative Insulin Nutrition Tables)] that employs both insulin and feed modulation is developed and analyzed using retrospective data from 19 patients with average Acute Physiology and Chronic Health Evaluation II score of 21.8. Results are compared with several published protocols in simulation, and verified in a proof-of-concept trial. RESULTS: In simulation, 61.7% of measurements were in the 75-110 mg/dL band and 83.5% in the 75-140 mg/dL band. Results from the simulation of published protocols agreed with published results. Clinically, for two patients, 64% and 85% of measurements were between 75 and 110 mg/dL during the two proof-of-concept trials. Total enteral feeding was similar to, or exceeded, retrospective data. CONCLUSIONS: Tight control was achieved in simulation using a protocol that is easy to implement in an intensive care unit. Similarly tight control was also maintained during the two proof-of-concept clinical trials. Measurement frequency of 1-2 h is seen to be critical to achieving and maintaining tight control. The overall SPRINT protocol is easy to use for clinical staff and effective in achieving and maintaining normoglycemia in critical illness.

Adult↗

PubMed2006

A pilot study of the SPRINT protocol for tight glycemic control in critically Ill patients.

BACKGROUND: Stress-induced hyperglycemia is prevalent in critical care, even in patients with no history of diabetes. Increased counter-regulatory hormone response increases gluconeogenesis and effective insulin resistance, which can be exacerbated by drug therapy. Control of blood glucose levels to the 4.0-6.1 mmol/L range has been shown to reduce mortality and improve clinical outcomes. The Specialized Relative Insulin and Nutrition Tables (SPRINT) protocol is a simple alternative intensive care unit protocol for modulating insulin and nutritional input to gain tight blood glucose control in the 4.0-6.1 mmol/L target band. The look-up tables, implemented in a wheel-based format, are used by nurses to determine glycemic control actions based on hourly or 2-hourly blood glucose measurements and nutrition and insulin administration rates. METHODS: An 11 patient pilot study was conducted comprising 2,152 hours of blood glucose level control using the SPRINT protocol. The patient cohort average Acute Physiology and Chronic Health Evaluation II score was 22, which was higher than previous intensive insulin clinical studies. RESULTS: Overall, 64% of measurements were in the 4.0-6.1 mmol/L band, 89% in the 4.0-7.0 mmol/L band, and 96% of all measurements in the 4.0-7.75 mmol/L band. The average value was 5.8 +/- 0.9 mmol/L. Only 1.4% of all measurements were below 4 mmol/L, with a minimum of 3.2 mmol/L. The maximum value recorded was 11.8 mmol/L. CONCLUSIONS: Control of blood glucose level was achieved using a protocol implemented by the nursing staff without the need for physician intervention or interpretation, where control is defined as maximizing time within a desired band. The results led to a high level of support for the SPRINT protocol among clinical staff and acceptance of the frequent measurement requirement for effective control. The ease-of-use of the protocol resulted in minimal noncompliance by clinical staff.

APACHE↗

PubMed2006

Rethinking glycaemic control in critical illness--from concept to clinical practice change.

OBJECTIVE: To examine the practical difficulties in managing hyperglycaemia in critical illness and to present recently developed model-based glycaemic management protocols to provide tight control. BACKGROUND: Hyperglycaemia is prevalent in critical care. Current published protocols require significant added clinical effort and have highly variable results. No currently published methods successfully address the practical clinical difficulties and patient variation, while also providing safe, tight control. METHODS: We developed a unique model-based approach that manages both nutritional inputs and exogenous insulin infusions. Computerised glycaemic control methods and proof-of-concept clinical trial results are presented. The protocol has been simplified to a set of tables and adopted as a clinical practice change. Eight pilot test cases are presented to demonstrate the overall approach. RESULTS: Computerised control methods lowered blood glucose (BG) levels to the range 4.0-6.1 mmol/L within 10 hours. Over 90% of pre-set hourly blood glucose targets were achieved within measurement error. Eight pilot tests of the simplified, table-based SPRINT protocol, covering 1651 patient-hours produced an average BG level of 5.7 mmol/L (SD, 0.9 mmol/L). BG levels were in the 4.0-6.1 mmol/L band for 60% of the controlled time. Just under 90% of measurements were in the range 4.0-7.0 mmol/L, with 96% in the range 4.0-7.75 mmol/L. There were no hypoglycaemic episodes, with a minimum glucose level of 3.2 mmol/L, and no additional clinical intervention was required. SUMMARY: The overall approach of modulating nutrition as well as insulin challenges the current practice of relying on insulin alone to reduce glycaemic levels, which often results in large variability and poor control. The protocol was developed from model-based analysis and proof-of-concept clinical trials, and then generalised to a simple, clinical practice improvement. The results show extremely tight control within safe glycaemic bands.

Aged↗

PubMed2005

Integral-based parameter identification for long-term dynamic verification of a glucose-insulin system model.

Hyperglycaemia in critically ill patients increases the risk of further complications and mortality. This paper introduces a model capable of capturing the essential glucose and insulin kinetics in patients from retrospective data gathered in an intensive care unit (ICU). The model uses two time-varying patient specific parameters for glucose effectiveness and insulin sensitivity. The model is mathematically reformulated in terms of integrals to enable a novel method for identification of patient specific parameters. The method was tested on long-term blood glucose recordings from 17 ICU patients, producing 4% average error, which is within the sensor error. One-hour forward predictions of blood glucose data proved acceptable with an error of 2-11%. All identified parameter values were within reported physiological ranges. The parameter identification method is more accurate and significantly faster computationally than commonly used non-linear, non-convex methods. These results verify the model's ability to capture long-term observed glucose-insulin dynamics in hyperglycemic ICU patients, as well as the fitting method developed. Applications of the model and parameter identification method for automated control of blood glucose and medical decision support are discussed.

Adult↗

PubMed2005

Adaptive bolus-based targeted glucose regulation of hyperglycaemia in critical care.

Tight regulation of blood glucose can significantly reduce mortality in critical illness. Critically ill patients are extremely diverse in the dynamics of their hyperglycaemia. Hence, responses can vary significantly, due to variations in insulin levels, effective insulin utilization, glucose absorption and other factors. Consequently, fixed protocols and sliding scales can result in error, given this large variation in patient dynamics. A two-compartment glucose-insulin system model that accounts for time-varying insulin sensitivity and endogenous glucose removal, along with two different saturation kinetics, is developed and tested in preliminary proof-of-concept clinical trials for adaptive control of blood glucose levels. The adaptive control algorithm developed in this research monitors the physiological status of a critically ill patient, allowing real-time, tight glycaemic regulation. The bolus-based insulin administration provides a safe approach to glucose level management. The ability to track changing physiological status and account for insulin transport and effect saturation enabled targeted stepwise reduction in glycaemic levels in three test cases.

Adaptation, Physiological↗

PubMed2005

Targeted glycemic reduction in critical care using closed-loop control.

BACKGROUND: Critically ill patients are often hyperglycemic and extremely diverse in their dynamics. Consequently, fixed protocols and sliding scales can result in error and poor control. Tight glucose control has been shown to significantly reduce mortality in critical care. An improved physiological system model of the glucose-insulin dynamics of a critical care patient is used to develop an adaptive tight glucose control protocol that accounts for variable patient dynamics, and is verified in limited clinical trials. METHODS: A physiologically based two-compartment system model that accounts for time-varying insulin sensitivity, time-varying endogenous glucose removal, and two saturation kinetics mechanisms is developed. A bolus-based adaptive control protocol is developed that monitors the physiological status of a critically ill patient, enabling tight glycemic regulation to preset glycemic targets. The model and protocol are verified in three, 5-h preliminary proof-of-concept clinical trials. Ethics approval was granted by the Canterbury Ethics Committee (Christchurch, New Zealand). RESULTS: Preset glycemic targets are achieved with an average absolute error of 9%, with 75% of all targets achieved within the 7% measurement error. Absolute errors greater than 7% ranged from 17% to 21%. CONCLUSIONS: Tight stepwise control was exhibited in all cases, and the adaptive system was able to match the model and observed patient dynamics. Most errors are associated with external perturbations such as drug therapies, or mismodeled parameters that can be easily adjusted with longer trials and/or more data per hour. The overall result is targeted stepwise tight glycemic regulation using insulin boluses.

Aged↗