Evidence map›Paper›PMID 39417874›Full record

ArticleIntensive care medicine2024

Accuracy of continuous glucose monitoring systems in intensive care unit patients: a scoping review.

Christian G Nielsen, Milda Grigonyte-Daraskeviciene, Mikkel T Olsen, Morten H Møller, Kirsten Nørgaard, Anders Perner, Johan Mårtensson, Ulrik Pedersen-Bjergaard, Peter L Kristensen, Morten H Bestle

Abstract readScoping Review
PubMed Publisher
In one paragraph

Article in Intensive care medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 3 pooled it
–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

20 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. [Hospital diabetes management (Update 2026)].Wiener klinische Wochenschrift · 2026
    Guideline
  3. Pooled it
  4. Trial
  5. Article
  6. Review
  7. Diabetes Management Strategies in Intensive Care Settings.The Medical clinics of North America · 2026
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Observational
  18. Observational
  19. Article
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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

10 authors.

Christian G NielsenDepartment of Anesthesiology and Intensive Care, Copenhagen University Hospital-North Zealand, Hilleroed, Denmark. Christian.gantzel.nielsen@regionh.dk.ORCID 0000-0002-5105-1049
Milda Grigonyte-DaraskevicieneDepartment of Intensive Care, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Mikkel T OlsenDepartment of Endocrinology and Nephrology, Copenhagen University Hospital-North Zealand, Hilleroed, Denmark.
Morten H MøllerDepartment of Intensive Care, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Kirsten NørgaardDepartment of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.
Anders PernerDepartment of Intensive Care, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Johan MårtenssonDepartment of Physiology and Pharmacology, Section of Anesthesia and Intensive Care, Karolinska Institutet, Stockholm, Sweden.
Ulrik Pedersen-BjergaardDepartment of Endocrinology and Nephrology, Copenhagen University Hospital-North Zealand, Hilleroed, Denmark.
Peter L KristensenDepartment of Endocrinology and Nephrology, Copenhagen University Hospital-North Zealand, Hilleroed, Denmark.
Morten H BestleDepartment of Anesthesiology and Intensive Care, Copenhagen University Hospital-North Zealand, Hilleroed, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeGlycemic control poses a challenge in intensive care unit (ICU) patients and dysglycemia is associated with poor outcomes. Continuous glucose monitoring (CGM) has been successfully implemented in the type 1 diabetes out-patient setting and renewed interest has been directed into the transition of CGM into the ICU. This scoping review aimed to provide an overview of CGM accuracy in ICU patients to inform future research and CGM implementation.

methodsWe systematically searched PubMed and EMBASE between 5th of December 2023 and 21st of May 2024 and reported findings in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline for scoping reviews (PRISMA-ScR). We assessed studies reporting the accuracy of CGM in the ICU and report study characteristics and accuracy outcomes.

resultsWe identified 2133 studies, of which 96 were included. Most studies were observational (91.7%), conducted in adult patients (74%), in mixed ICUs (47.9%), from 2014 and onward, and assessed subcutaneous CGM systems (80%) using arterial blood samples as reference test (40.6%). Half of the studies (56.3%) mention the use of a prespecified reference test protocol. The mean absolute relative difference (MARD) ranged from 6.6 to 30.5% for all subcutaneous CGM studies. For newer factory calibrated CGM, MARD ranged from 9.7 to 20.6%. MARD for intravenous CGM was 5-14.2% and 6.4-13% for intraarterial CGM.

conclusionsIn this scoping review of CGM accuracy in the ICU, we found great diversity in accuracy reporting. Accuracy varied depending on CGM and comparator, and may be better for intravascular CGM and potentially lower during hypoglycemia.

Indexed as

Blood GlucoseIntensive Care UnitsContinuous Glucose MonitoringCritical CareHumansHypoglycemiaMonitoring, PhysiologicBlood GlucoseCGMContinuous Glucose MonitoringGlucose ManagementICUIntensive Care Unit

Identifiers

What Socratic 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 Socratic graph.