ArticleJournal of diabetes science and technology2009
Intensive Care Unit Insulin Delivery Algorithms: Why So Many? How to Choose?
Article in Journal of diabetes science and technology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 51 citations in OpenAlex.
- Tight Glycemic Control in Critically Ill Children.The New England journal of medicine · 2017Trial
- Design and rationale of Heart and Lung Failure - Pediatric INsulin Titration Trial (HALF-PINT): A randomized clinical trial of tight glycemic control in hyperglycemic critically ill children.Contemporary clinical trials · 2017Trial
- Trial
- Design and rationale of safe pediatric euglycemia after cardiac surgery: a randomized controlled trial of tight glycemic control after pediatric cardiac surgery.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2013Trial
- Tight glycemic control versus standard care after pediatric cardiac surgery.The New England journal of medicine · 2012Trial
- Value of continuous glucose monitoring for minimizing severe hypoglycemia during tight glycemic control.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2011Trial
- Improvement of compliance to the Portland intensive insulin therapy during liver transplantation after introducing an application software: a retrospective single center cohort study.Anesthesia and pain medicine · 2022Article
- Practice of hyperglycaemia control in intensive care units of the Military Hospital, Sudan-Needs of a protocol.PloS one · 2022Article
- Portland Intensive Insulin Therapy During Living Donor Liver Transplantation: Association with Postreperfusion Hyperglycemia and Clinical Outcomes.Scientific reports · 2018Article
- Hypoglycemia Prevention by Algorithm Design During Intravenous Insulin Infusion.Current diabetes reports · 2018Review
- A Pediatric Intensive Care Unit Bedside Computer Clinical Decision Support Protocol for Hyperglycemia Is Feasible, Safe and Offers Advantages.Diabetes technology & therapeutics · 2017Article
- A comparison of two insulin infusion protocols in the medical intensive care unit by continuous glucose monitoring.Annals of intensive care · 2016Article
- Remote Blood Glucose Monitoring in mHealth Scenarios: A Review.Sensors (Basel, Switzerland) · 2016Review
- Impact of Glucose Meter Error on Glycemic Variability and Time in Target Range During Glycemic Control After Cardiovascular Surgery.Journal of diabetes science and technology · 2015Article
- Population-Specific Models of Glycemic Control in Intensive Care: Towards a Simulation-Based Methodology for Protocol Optimization.Proceedings of the ... American Control Conference. American Control Conference · 2015Article
- The impact of measurement frequency on the domains of glycemic control in the critically ill--a Monte Carlo simulation.Journal of diabetes science and technology · 2015Article
- Medanta insulin protocols in patients undergoing cardiac surgery.Indian journal of endocrinology and metabolism · 2014Review
- Tight glycemic control in the ICU - is the earth flat?Critical care (London, England) · 2014Article
- The future is now: software-guided intensive insulin therapy in the critically ill.Journal of diabetes science and technology · 2013Review
- Health technology assessment review: Computerized glucose regulation in the intensive care unit--how to create artificial control.Critical care (London, England) · 2009Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 2 countries.
Funding
Abstract
objectiveStudies showing improved outcomes with tight glycemic control in the intensive care unit (ICU) have resulted in a substantial number of new insulin delivery algorithms being proposed. The present study highlights mechanisms used in the better-known approaches, examines what might be critical differences among them, and uses systems theory to characterize the conditions under which each can be expected to perform best.
methodsAlgorithm dose (DeltaI/DeltaG) and step (response to a persistent elevation in glucose) response curves were calculated for written instruction algorithms, developed at the Providence Heart and Vascular Institute (Portland [P] protocol), the University of Washington (UW), and Yale University (Y), together with similar curves for the Glucommander (GM) and proportional integral derivative (PID) computer algorithms. From the simulated curves, different mechanisms used to adjust insulin delivery were identified.
resultsAll algorithms increased insulin delivery in response to persistent hyperglycemia, but the mechanism used altered the algorithm's sensitivity to glucose, or gain, in the GM, UW, and Y protocols, while leaving it unchanged for the P protocol and PID algorithm.
conclusionsThe increase in insulin delivery in response to persistent hyperglycemia observed with all the algorithms can be expected to bring subjects who respond to insulin to targeted glucose ranges. However, because the PID and P protocols did not alter the insulin delivery response curves, these algorithms can be expected to take longer to achieve target glucose levels in individuals who are insulin resistant and/or are exposed to increased carbohydrate loads (e.g., glucose infusions). By contrast, the GM, UW, and Y algorithms can be expected to adapt to the insulin resistance such that the time to achieve target levels is unchanged if the time for insulin to act does not change. If the insulin resistance is accompanied by a longer time for insulin to act, the UW, Y, and GM algorithms may increase the risk of hypoglycemia. Under these conditions, the longer time required for the PID and P protocols to achieve a target glucose level may be a reasonable trade-off for no increase in the risk of hypoglycemia.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.