Evidence map›Paper›PMID 32349750›Full record

ArticleBiomedical engineering online2020

Risk and reward: extending stochastic glycaemic control intervals to reduce workload.

Vincent Uyttendaele, Jennifer L Knopp, Geoffrey M Shaw, Thomas Desaive, J Geoffrey Chase

Open access · goldAbstract read
In one paragraph

Article in Biomedical engineering online, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 29% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 12 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Vincent UyttendaeleGIGA-In Silico Medicine, University of Liège, Allée Du 6 Août 19, Bât. B5a, 4000, Liège, Belgium. vincent.uyttendaele@uliege.be.ORCID http://orcid.org/0000-0002-8499-6612
Jennifer L KnoppDepartment of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand.
Geoffrey M ShawDept of Intensive Care, Christchurch Hospital, Christchurch, New Zealand.
Thomas DesaiveGIGA-In Silico Medicine, University of Liège, Allée Du 6 Août 19, Bât. B5a, 4000, Liège, Belgium.
J Geoffrey ChaseDepartment of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand.
University of Canterbury · NZUniversity of Liège · BEChristchurch Hospital · NZ

Funding

MedTech Centre for Research Expertise (CoRE), New Zealand 3705718NZ National Challenge Science 7, Science for Technology and Innovation CRS-S3-2016
6 · The paper itself

Abstract

backgroundSTAR is a model-based, personalised, risk-based dosing approach for glycaemic control (GC) in critically ill patients. STAR provides safe, effective control to nearly all patients, using 1-3 hourly measurement and intervention intervals. However, the average 11-12 measurements per day required can be a clinical burden in many intensive care units. This study aims to significantly reduce workload by extending STAR 1-3 hourly intervals to 1 to 4-, 5-, and 6-hourly intervals, and evaluate the impact of these longer intervals on GC safety and efficacy, using validated in silico virtual patients and trials methods. A Standard STAR approach was used which allowed more hyperglycaemia over extended intervals, and a STAR Upper Limit Controlled approach limited nutrition to mitigate hyperglycaemia over longer intervention intervals.

resultsExtending STAR from 1-3 hourly to 1-6 hourly provided high safety and efficacy for nearly all patients in both approaches. For STAR Standard, virtual trial results showed lower % blood glucose (BG) in the safe 4.4-8.0 mmol/L target band (from 83 to 80%) as treatment intervals increased. Longer intervals resulted in increased risks of hyper- (15% to 18% BG > 8.0 mmol/L) and hypo- (2.1% to 2.8% of patients with min. BG < 2.2 mmol/L) glycaemia. These results were achieved with slightly reduced insulin (3.2 [2.0 5.0] to 2.5 [1.5 3.0] U/h) and nutrition (100 [85 100] to 90 [75 100] % goal feed) rates, but most importantly, with significantly reduced workload (12 to 8 measurements per day). The STAR Upper Limit Controlled approach mitigated hyperglycaemia and had lower insulin and significantly lower nutrition administration rates.

conclusionsThe modest increased risk of hyper- and hypo-glycaemia, and the reduction in nutrition delivery associated with longer treatment intervals represent a significant risk and reward trade-off in GC. However, STAR still provided highly safe, effective control for nearly all patients regardless of treatment intervals and approach, showing this unique risk-based dosing approach, modulating both insulin and nutrition, to be robust in its design. Clinical pilot trials using STAR with different measurement timeframes should be undertaken to confirm these results clinically.

Indexed as

WorkloadGlycemic ControlHumansModels, StatisticalRisk AssessmentStochastic ProcessesBlood glucoseGlycaemic controlHyperglycaemiaInsulin resistanceInsulin sensitivityInsulin therapyTrade-offWorkload

Identifiers

PMID32349750
PMCPMC7191799
OpenAlexW3021544281

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.