Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study

Personalized treatment in glycemic control (GC) is a visibly promising research area that requires improved mechanisms providing patient-specific procedures to enable complicated decision support. Available per-patient data must be more than written records, and be fully integrated in this personalization process. This article presents a process for relating the intensive care unit patients' demographic and admission data to their GC performance. With this objective, a probabilistic Bayesian network was chosen to provide more personalized decisions. As a case study, average daily blood glucose measurements were chosen as the interest target node in order to weigh GC that provides a reduced nursing workload. To test the idea, data from 482 patients, with nine variables from four Malaysian intensive care units with different controls were exploited. The identified steps crucial in building a dependable model are variable selection, continuous state discretization, and unsupervised structure learning. Using a multi-target node evaluation, a network with 80% mean overall classification precision was obtained with a normalized equal distance discretization algorithm and a maximum weight spanning tree technique. Meanwhile, the interest target node scored 90.39% precision. The results from this study, which are complemented with an evaluation of missing data, are proposed as a benchmark for using Bayesian networks in this type of application

Model-based glycemic control in a Malaysian intensive care unit: performance and safety study

Asma Abu-Samah,1 Jennifer Launa Knopp,2 Normy Norfiza Abdul Razak,3 Athirah Abdul Razak,3 Ummu Kulthum Jamaludin,3 Fatanah Mohamad Suhaimi,4 Azrina Md Ralib,5 Mohd Basri Mat Nor,6 James Geoffrey Chase,2 Christopher Grant Pretty21Institute of Energy Infrastructure, Universiti Tenaga Nasional, Kajang, 43000, Malaysia; 2Department of Mechanical Engineering, University of Canterbury, Christchurch, 8041, New Zealand; 3College of Engineering, Universiti Tenaga Nasional, Kajang, 43000, Malaysia; 4Faculty of Mechanical Engineering, Universiti Malaysia Pahang, Pekan, 26600, Malaysia; 5Advanced Medical and Dental Institute, Universiti Sains Islam Malaysia, Kepala Batas, 13200, Malaysia; 6Kulliyah of Medicine, International Islamic University Malaysia, Kuantan, 25200, MalaysiaBackground: Stress-induced hyperglycemia is common in critically ill patients. A few forms of model-based glycemic control have been introduced to reduce this phenomena and among them is the automated STAR protocol which has been used in the Christchurch and Gyulá hospitals’ intensive care units (ICUs) since 2010.Methods: This article presents the pilot trial assessment of STAR protocol which has been implemented in the International Islamic University Malaysia Medical Centre (IIUMMC) Hospital ICU since December 2017. One hundred and forty-two patients who received STAR treatment for more than 20 hours were used in the assessment. The initial results are presented to discuss the ability to adopt and adapt the model-based control framework in a Malaysian environment by analyzing its performance and safety.Results: Overall, 60.7% of blood glucose measurements were in the target band. Only 0.78% and 0.02% of cohort measurements were below 4.0 mmol/L and 2.2 mmol/L (the limitsfor mild and severe hypoglycemia, respectively). Treatment preference-wise, the clinical staff were favorable of longer intervention options when available. However, 1 hourly treatments were still used in 73.7% of cases.Conclusion: The protocol succeeded in achieving patient-specific glycemic control while maintaining safety and was trusted by nurses to reduce workload. Its lower performance results, however, give the indication for modification in some of the control settings to better fit the Malaysian environment.Keywords: glycemic control, intensive care unit, model-based control, pilot trial, Malaysian hospita

Model-based glycemic control in a Malaysian intensive care unit: performance and safety study.

Background: Stress-induced hyperglycemia is common in critically ill patients. A few forms of model-based glycemic control have been introduced to reduce this phenomena and among them is the automated STAR protocol which has been used in the Christchurch and Gyulá hospitals' intensive care units (ICUs) since 2010. Methods: This article presents the pilot trial assessment of STAR protocol which has been implemented in the International Islamic University Malaysia Medical Centre (IIUMMC) Hospital ICU since December 2017. One hundred and forty-two patients who received STAR treatment for more than 20 hours were used in the assessment. The initial results are presented to discuss the ability to adopt and adapt the model-based control framework in a Malaysian environment by analyzing its performance and safety. Results: Overall, 60.7% of blood glucose measurements were in the target band. Only 0.78% and 0.02% of cohort measurements were below 4.0 mmol/L and 2.2 mmol/L (the limitsfor mild and severe hypoglycemia, respectively). Treatment preference-wise, the clinical staff were favorable of longer intervention options when available. However, 1 hourly treatments were still used in 73.7% of cases. Conclusion: The protocol succeeded in achieving patient-specific glycemic control while maintaining safety and was trusted by nurses to reduce workload. Its lower performance results, however, give the indication for modification in some of the control settings to better fit the Malaysian environment