Evidence map›Paper›PMID 21210080›Full record

ArticleIntensive care medicine2011

The metrics of glycaemic control in critical care.

Iain M J Mackenzie, Tony Whitehouse, Peter G Nightingale

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Intensive care medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
10.9field-weighted citation impact, top 1% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 94 citations in OpenAlex.

  1. Guideline
  2. Trial
  3. Trial
  4. Trial
  5. Accuracy of continuous glucose monitoring in critically ill patients.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2025
    Article
  6. Utility of bedside artificial pancreas for postoperative glycemic control in cardiac surgery.Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs · 2021
    Article
  7. Study protocol and statistical analysis plan for the Liberal Glucose Control in Critically Ill Patients with Pre-existing Type 2 Diabetes (LUCID) trial.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2020
    Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Glucose Control in the ICU: A Continuing Story.Journal of diabetes science and technology · 2016
    Review
  13. Current topics in glycemic control by wearable artificial pancreas or bedside artificial pancreas with closed-loop system.Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs · 2016
    Review
  14. Article
  15. Article
  16. Review
  17. The Development of a Continuous Intravascular Glucose Monitoring Sensor.Journal of diabetes science and technology · 2015
    Article
  18. Hyperglycemia in Critically Ill Patients: Management and Prognosis.Medical archives (Sarajevo, Bosnia and Herzegovina) · 2015
    Observational
  19. Year in review 2013: Critical Care--metabolism.Critical care (London, England) · 2014
    Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

Iain M J MackenzieDepartment of Anaesthesia and Critical Care Medicine, Queen Elizabeth Hospital, University Hospital Birmingham NHS Foundation Trust, Edgbaston, Birmingham, UK. iain.mackenzie@uhb.nhs.uk
Tony Whitehouse
Peter G Nightingale
Queen Elizabeth Hospital · GBQueen Elizabeth Hospital Birmingham · GBUniversity of Birmingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTrials of tight glucose control have compared measures of central tendency, such as average blood glucose, and yielded conflicting results. Other metrics, such as standard deviation, reflect different properties of glucose control and are also associated with changes in outcome. It is possible, therefore, that the conflicting results from interventional studies arise from effects on glycaemic control that have not been reported.

methodsUsing glucose measurements from patients admitted to four adult intensive care units in one UK hospital, we sought to identify metrics of glycaemic control, examine the relationship between them and identify the metrics that are both independently and most strongly associated with outcome.

resultsWe examined nine previously described metrics and identified a further four. Cluster analysis classified these metrics into two families, namely, those reflecting measures of central tendency and those reflecting measures of dispersion. A measure of minimum glucose was also identified but related to neither family. Plots of the quintiles of these metrics against hospital mortality revealed population-specific relationships. Areas under receiver-operating characteristic curves could not identify an optimum metric of central tendency or dispersion. Using odds ratios, we were able to show that the effect of these metrics is independent of one another.

conclusionOur results suggest that glycaemic control is associated with outcome on the basis of three independent metrics, reflecting measures of central tendency, measures of dispersion and a measure of minimum glucose.

Indexed as

Critical CareAdultAgedBlood GlucoseCluster AnalysisCritical IllnessDose-Response Relationship, DrugEnglandHospital MortalityHumansHyperglycemiaHypoglycemic AgentsInsulinIntensive Care UnitsMiddle AgedPrognosisBlood GlucoseHypoglycemic AgentsInsulin

Identifiers

PMID21210080
OpenAlexW2005392873

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.