ArticleCritical care (London, England)2008
Glycemic penalty index for adequately assessing and comparing different blood glucose control algorithms.
Article in Critical care (London, England), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 19 papers, 2 of them syntheses that pooled it.
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.
LOGIC-Insulin Computerized Algorithm-guided Versus Nurse-directed Blood Glucose Control in Critically Ill Patients: the LOGIC-1 Randomized Controlled Trial
LOGIC-Insulin Computerized Algorithm-guided Versus Nurse-directed Blood Glucose Control in Critically Ill Patients: the LOGIC-2 Multicentre Randomized Controlled Trial
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Ingredients for adequate evaluation of blood glucose algorithms as applied to the critically ill.Critical care (London, England) · 2009Pooled it
- A systematic review on quality indicators for tight glycaemic control in critically ill patients: need for an unambiguous indicator reference subset.Critical care (London, England) · 2008Pooled it
- Glycaemic penalty index as an independent predictor of healthcare-associated infection in surgical inpatients: A nested cohort study from the STOIC-D surgery trial.Diabetic medicine : a journal of the British Diabetic Association · 2026Trial
- Software-guided versus nurse-directed blood glucose control in critically ill patients: the LOGIC-2 multicenter randomized controlled clinical trial.Critical care (London, England) · 2017Trial
- LOGIC-insulin algorithm-guided versus nurse-directed blood glucose control during critical illness: the LOGIC-1 single-center, randomized, controlled clinical trial.Diabetes care · 2013Trial
- Computer decision support software safely improves glycemic control in the burn intensive care unit: a randomized controlled clinical study.Journal of burn care & research : official publication of the American Burn AssociationTrial
- Impact of post-procedural glycemic variability on cardiovascular morbidity and mortality after transcatheter aortic valve implantation: a post hoc cohort analysis.Cardiovascular diabetology · 2019Observational
- Extremum Seeking Control for Personalized Zone Adaptation in Model Predictive Control for Type 1 Diabetes.IEEE transactions on bio-medical engineering · 2018Article
- Comparative Simulation Study of Glucose Control Methods Designed for Use in the Intensive Care Unit Setting via a Novel Controller Scoring Metric.Journal of diabetes science and technology · 2017Article
- Glucose Control in the ICU: A Continuing Story.Journal of diabetes science and technology · 2016Review
- Predictive roles of intraoperative blood glucose for post-transplant outcomes in liver transplantation.World journal of gastroenterology · 2015Review
- Glycemic variability in hospitalized patients: choosing metrics while awaiting the evidence.Current diabetes reports · 2013Review
- Impact of a computer-generated alert system on the quality of tight glycemic control.Intensive care medicine · 2011Article
- Assessment of blood glucose control in the pediatric intensive care unit: extension of the glycemic penalty index toward children and infants.Journal of diabetes science and technology · 2011Article
- International recommendations for glucose control in adult non diabetic critically ill patients.Critical care (London, England) · 2010Article
- Computing the risk of postprandial hypo- and hyperglycemia in type 1 diabetes mellitus considering intrapatient variability and other sources of uncertainty.Journal of diabetes science and technology · 2009Article
- The impact of the severity of sepsis on the risk of hypoglycaemia and glycaemic variability.Critical care (London, England) · 2008Article
- Tight glucose control: should we move from intensive insulin therapy alone to modulation of insulin and nutritional inputs?Critical care (London, England) · 2008Article
- Patient-level glucose reporting: averages, episodes, or something in between?Critical care (London, England) · 2008Article
Corrections and comments
- Commented on by
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionBlood glucose (BG) control performed by intensive care unit (ICU) nurses is becoming standard practice for critically ill patients. New (semi-automated) 'BG control' algorithms (or 'insulin titration' algorithms) are under development, but these require stringent validation before they can replace the currently used algorithms. Existing methods for objectively comparing different insulin titration algorithms show weaknesses. In the current study, a new approach for appropriately assessing the adequacy of different algorithms is proposed.
methodsTwo ICU patient populations (with different baseline characteristics) were studied, both treated with a similar 'nurse-driven' insulin titration algorithm targeting BG levels of 80 to 110 mg/dl. A new method for objectively evaluating BG deviations from normoglycemia was founded on a smooth penalty function. Next, the performance of this new evaluation tool was compared with the current standard assessment methods, on an individual as well as a population basis. Finally, the impact of four selected parameters (the average BG sampling frequency, the duration of algorithm application, the severity of disease, and the type of illness) on the performance of an insulin titration algorithm was determined by multiple regression analysis.
resultsThe glycemic penalty index (GPI) was proposed as a tool for assessing the overall glycemic control behavior in ICU patients. The GPI of a patient is the average of all penalties that are individually assigned to each measured BG value based on the optimized smooth penalty function. The computation of this index returns a number between 0 (no penalty) and 100 (the highest penalty). For some patients, the assessment of the BG control behavior using the traditional standard evaluation methods was different from the evaluation with GPI. Two parameters were found to have a significant impact on GPI: the BG sampling frequency and the duration of algorithm application. A higher BG sampling frequency and a longer algorithm application duration resulted in an apparently better performance, as indicated by a lower GPI.
conclusionThe GPI is an alternative method for evaluating the performance of BG control algorithms. The blood glucose sampling frequency and the duration of algorithm application should be similar when comparing algorithms.
Indexed as
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.