Trial reportIntensive care medicine2008
Tight glycaemic control by an automated algorithm with time-variant sampling in medical ICU patients.
Trial report in Intensive care medicine, 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 37 papers, 6 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.
Mono-Centric, Open, Non-Controlled Study To Investigate The Feasibility Of Blood Glucose Control With The Software-Algorithm eMPC (Enhanced Model Predictive Control) In ICU Patients
Monocentric, Open Study to Investigate the Feasibility of Blood Glucose Control With the Space TGC System (With Incorporated Software-algorithm eMPC) in Medical ICU Patients
Who cites it
37 citing papers in PubMed, 6 syntheses or guidelines pooled it, 82 citations in OpenAlex.
- American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2022Guideline
- Effect of Electronic Prescribing Strategies on Medication Error and Harm in Hospital: a Systematic Review and Meta-analysis.Journal of general internal medicine · 2019Pooled it
- Nutrition Informatics Applications in Clinical Practice: a Systematic Review.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2015Pooled it
- Computerized advice on drug dosage to improve prescribing practice.The Cochrane database of systematic reviews · 2013Pooled it
- Glucose variability measures and their effect on mortality: a systematic review.Intensive care medicine · 2011Pooled it
- Tight glycemic control and computerized decision-support systems: a systematic review.Intensive care medicine · 2009Pooled it
- Feasibility of automated insulin delivery guided by continuous glucose monitoring in preterm infants.Archives of disease in childhood. Fetal and neonatal edition · 2020Trial
- Comparison of Space Glucose Control and Routine Glucose Management Protocol for Glycemic Control in Critically Ill Patients: A Prospective, Randomized Clinical Study.Chinese medical journal · 2017Trial
- Feasibility of fully automated closed-loop glucose control using continuous subcutaneous glucose measurements in critical illness: a randomized controlled trial.Critical care (London, England) · 2013Trial
- Implementing glucose control in intensive care: a multicenter trial using statistical process control.Intensive care medicine · 2010Trial
- Comparison of three protocols for tight glycemic control in cardiac surgery patients.Diabetes care · 2009Trial
- Validating medical digital twins for clinical decision support: beyond predictive accuracy.JAMIA open · 2026Review
- Glycemic targets in critically ill adults: A mini-review.World journal of diabetes · 2021Review
- Usability study of a new tool for nutritional and glycemic management in adult intensive care: Glucosafe 2.Journal of clinical monitoring and computing · 2021Article
- Diabetes Technology in the Inpatient Setting for Management of Hyperglycemia.Endocrinology and metabolism clinics of North America · 2020Review
- Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas.Critical care (London, England) · 2018Review
- Nutrition delivery of a model-based ICU glycaemic control system.Annals of intensive care · 2018Article
- Risk of Hypoglycemia During Insulin Infusion Directed by Paper Protocol Versus Electronic Glycemic Management System in Critically Ill Patients at a Large Academic Medical Center.Journal of diabetes science and technology · 2018Article
- Glucose Control in the ICU: A Continuing Story.Journal of diabetes science and technology · 2016Review
- Glucose control in intensive care: usability, efficacy and safety of Space GlucoseControl in two medical European intensive care units.BMC endocrine disorders · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTight glycaemic control (TGC) in critically ill patients improves clinical outcome, but is difficult to establish The primary objective of the present study was to compare glucose control in medical ICU patients applying a computer-based enhanced model predictive control algorithm (eMPC) extended to include time-variant sampling against an implemented glucose management protocol.
designOpen randomised controlled trial.
settingNine-bed medical intensive care unit (ICU) in a tertiary teaching hospital. PATIENTS AND
participantsFifty mechanically ventilated medical ICU patients.
interventionsPatients were included for a study period of up to 72 h. Patients were randomised to the control group (n = 25), treated by an implemented insulin algorithm, or to the eMPC group (n = 25), using the laptop-based algorithm. Target range for blood glucose (BG) was 4.4-6.1 mM. Efficacy was assessed by mean BG, hyperglycaemic index (HGI) and BG sampling interval. Safety was assessed by the number of hypoglycaemic-episodes < 2.2 mM. Each participating nurse filled-in a questionnaire regarding the usability of the algorithm. MEASUREMENTS AND MAIN
resultsBG and HGI were significantly lower in the eMPC group [BG 5.9 mM (5.5-6.3), median (IQR); HGI 0.4 mM (0.2-0.9)] than in control patients [BG 7.4 mM (6.9-8.6), p < 0.001; HGI 1.6 mM (1.1-2.4), p < 0.001]. One hypoglycaemic episode was detected in the eMPC group; no such episodes in the control group. Sampling interval was significantly shorter in the eMPC group [eMPC 117[Symbol: see text]min (+/- 34), mean (+/- SD), vs 174 min (+/- 27); p < 0.001]. Thirty-four nurses filled-in the questionnaire. Thirty answered the question of whether the algorithm could be applied in daily routine in the affirmative.
conclusionsThe eMPC algorithm was effective in maintaining tight glycaemic control in severely ill medical ICU patients.
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.