Nutrition delivery, workload and performance in a model-based ICU glycaemic control system. (November 2018)

• Record Type: Journal Article
• Authors: Stewart, Kent W.; Chase, J. Geoffrey; Pretty, Christopher G.; Shaw, Geoffrey M.
• Is Part Of: Computer methods and programs in biomedicine. Volume 166(2018)
• Page Start: 9
• Page End: 18
• Publication Date: 2018-11
• Subjects: Glycaemic control -- Nutrition delivery -- Clinical workload -- Intensive care unit -- Critical care -- Hyperglycaemia -- Hypoglycaemia -- Model-based -- Targeted -- Stochastic; STAR Stochastic TARgeted -- GC Glycaemic Control -- BG Blood Glucose -- IQR Inter-Quartile Range -- ICU Intensive Care Unit -- ACCP American College of Chest Physicians -- CDF Cumulative Distribution Function -- CB Cahill et al. Best -- SLQ STAR Lower Quartile -- PN Parenteral Nutrition; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2018.09.005
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Three simpler, lower workload and thus potentially more clinically desirable alternative nutrition protocols used in conjunction with the STAR insulin Glycaemic Control (GC) protocol are investigated. Each nutrition protocol is simulated on a 221 patient virtual cohort, and GC performance, safety and workload assessed. A fixed nutrition rate that varies in steps by day over the first three days of GC can offer similar performance and potentially enhanced safety, while still delivering world leading nutrition delivery to hyperglycemic, insulin resistant patients. The result is relatively general and could be adapted by STAR or any form of GC to reduce clinical workload without affecting GC safety and quality, and thus make it more clinically acceptable. The results delineate clear, more general tradeoffs between the safety and performance of glycemic control, workload, and nutrition delivery for hyperglycemic, insulin resistant ICU patients. Abstract: Background and Objective: Hyperglycaemia is commonplace in the adult intensive care unit (ICU), and has been associated with increased morbidity and mortality. Effective glycaemic control (GC) can reduce morbidity and mortality, but has proven difficult. STAR is a model-based GC protocol that uniquely maintains normoglycaemia by changing both insulin and nutrition interventions, and has been proven effective in controlling blood glucose (BG) in the ICU. However, most ICU GC protocols only change insulin interventions, making the variable nutrition aspect of STAR less clinically desirable. This paper compares the performance of STAR modulating only insulin, with three simpler alternative nutrition protocols in clinically evaluated virtual trials. Methods: Alternative nutrition protocols are fixed nutrition rate (100% caloric goal), CB (Cahill et al. best) stepped nutrition rate (60%, 80% and 100% caloric goal for the first 3 days of GC, and 100% thereafter) and SLQ (STAR lower quartile) stepped nutrition rate (65%, 75% and 85% caloric goal for the first 3 days of GC, and 85% thereafter). Each nutrition protocol is simulated with the STAR insulin protocol on a 221 patient virtual cohort, and GC performance, safety and total intervention workload are assessed. Results: All alternative nutrition protocols considerably reduced total intervention workload (14.6–19.8%) due to reduced numbers of nutrition changes. However, only the stepped nutrition protocols achieved similar GC performance to the current variable nutrition protocol. Of the two stepped nutrition protocols, the SLQ nutrition protocol also improved GC safety, almost halving the number of severe hypoglycaemic cases (5 vs. 9, P = 0.42). Conclusions: Overall, the SLQ nutrition protocol was the best alternative to the current variable nutrition protocol, but either stepped nutrition protocol could be adapted by STAR to reduce workload and make it more clinically acceptable, while maintaining its proven performance and safety.