Evidence map›Paper›PMID 28645302›Full record

ArticleCritical care (London, England)2017

Untangling glycaemia and mortality in critical care.

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

Abstract read
In one paragraph

Article in Critical care (London, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
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

25 citing papers in PubMed.

  1. Observational
  2. Article
  3. Observational
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Estimating Increased EGP During Stress Response in Critically Ill Patients.Journal of diabetes science and technology · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Updates in Glycemic Management in the Hospital.Current diabetes reports · 2019
    Review
  18. Article
  19. Article
  20. Review
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.

Vincent UyttendaeleDepartment of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand. vincent.uyttendaele@pg.canterbury.ac.nz.ORCID http://orcid.org/0000-0002-8499-6612
Jennifer L DicksonDepartment of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand.
Geoffrey M ShawDepartment of Intensive Care, Christchurch Hospital, Private Bag 4710, Christchurch, New Zealand.
Thomas DesaiveGIGA - In Silico Medicine, University of Liège, Allée du 6 Août 19, bâtiment B5a, 4000, Liège, Belgium.
J Geoffrey ChaseDepartment of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperglycaemia is associated with adverse outcomes in the intensive care unit, and initial studies suggested outcome benefits of glycaemic control (GC). However, subsequent studies often failed to replicate these results, and they were often unable to achieve consistent, safe control, raising questions about the benefit or harm of GC as well as the nature of the association of glycaemia with mortality and clinical outcomes. In this study, we evaluated if non-survivors are harder to control than survivors and determined if glycaemic outcome is a function of patient condition and eventual outcome or of the glycaemic control provided.

methodsClinically validated, model-based, hour-to-hour insulin sensitivity (SI) and its hour-to-hour variability (%ΔSI) were identified over the first 72 h of therapy in 145 patients (119 survivors, 26 non-survivors). In hypothesis testing, we compared distributions of SI and %ΔSI in 6-hourly blocks for survivors and non-survivors. In equivalence testing, we assessed if differences in these distributions, based on blood glucose measurement error, were clinically significant.

resultsSI level was never equivalent between survivors and non-survivors (95% CI of percentage difference in medians outside ±12%). Non-survivors had higher SI, ranging from 9% to 47% higher overall in 6-h blocks, and this difference became statistically significant as glycaemic control progressed. %ΔSI was equivalent between survivors and non-survivors for all 6-hourly blocks (95% CI of difference in medians within ±12%) and decreased in general over time as glycaemic control progressed.

conclusionsWhereas non-survivors had higher SI levels, variability was equivalent to that of survivors over the first 72 h. These results indicate survivors and non-survivors are equally controllable, given an effective glycaemic control protocol, suggesting that glycaemia level and variability, and thus the association between glycaemia and outcome, are essentially determined by the control provided rather than by underlying patient or metabolic condition.

Indexed as

AgedBlood GlucoseFemaleGlycemic IndexHumansHyperglycemiaHypoglycemic AgentsInsulinInsulin ResistanceIntensive Care UnitsMaleMiddle AgedRetrospective StudiesSurvivorsBlood GlucoseHypoglycemic AgentsInsulinBlood glucoseCritical careGlycaemic controlHyperglycaemiaInsulinInsulin sensitivityVariability

Identifiers

PMID28645302
PMCPMC5482947

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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.