Evidence map›Paper›PMID 16981981›Full record

ArticleCritical care (London, England)2006

Accuracy and feasibility of point-of-care and continuous blood glucose analysis in critically ill ICU patients.

Anouk M Corstjens, Jack J M Ligtenberg, Iwan C C van der Horst, Rob Spanjersberg, Joline S W Lind, Jaap E Tulleken, John H J M Meertens, Jan G Zijlstra

Open access · goldAbstract readValidation Study
In one paragraph

Article in Critical care (London, England), 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 2 pooled it
5.9field-weighted citation impact, top 3% 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

61 citing papers in PubMed, 2 syntheses or guidelines pooled it, 163 citations in OpenAlex.

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  13. Effects of Glycemic Variability in Critically Ill Patients with Coronavirus Disease 2019: A Retrospective Observational Study.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2024
    Article
  14. Article
  15. Continuous Glucose Monitoring in the Hospital.Endocrinology and metabolism (Seoul, Korea) · 2021
    Review
  16. Review
  17. Article
  18. Article
  19. Inpatient Continuous Glucose Monitoring and Glycemic Outcomes.Journal of diabetes science and technology · 2017
    Review
  20. Article

1 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Anouk M CorstjensDepartment of Anesthesiology, University Medical Center Groningen, Groningen, The Netherlands. a.m.corstjens@anest.umcg.nl
Jack J M Ligtenberg
Iwan C C van der Horst
Rob Spanjersberg
Joline S W Lind
Jaap E Tulleken
John H J M Meertens
Jan G Zijlstra
University Medical Center Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTo obtain strict glucose regulation, an accurate and feasible bedside glucometry method is essential. We evaluated three different types of point-of-care glucometry in seriously ill intensive care unit (ICU) patients. The study was performed as a single-centre, prospective, observational study in a 12-bed medical ICU of a university hospital.

methodsPatients with an expected ICU stay of more than 48 hours were included. Because the reference laboratory delivers glucose values after approximately 30 to 60 minutes, which is too slow to use in a glucose regulation protocol and for calibration of the subcutaneous continuous glucose monitoring system (CGMS) (CGMS System Gold), we first validated the ICU-based blood gas/glucose analyser ABL715 (part 1 of the study). Subsequently, part 2 was performed: after inserting (and calibrating) the subcutaneous CGMS, heparinised arterial blood samples were drawn from an arterial line every 6 hours and analysed on both the Precision PCx point-of-care meter using test strips and on the blood gas/glucose analyser ABL715. CGMS glucose data were downloaded after 24 to 72 hours. The results of the paired measurements were analysed as a scatter plot by the method of Bland and Altman and were expressed as a correlation coefficient.

resultsPart 1: Four hundred and twenty-four blood samples were drawn from 45 critically ill ICU patients. The ICU-based blood gas/glucose analyser ABL715 provided a good estimate of conventional laboratory glucose assessment: the correlation coefficient was 0.95. In the Clarke error grid, 96.8% of the paired measurements were in the clinically acceptable zones A and B. Part 2: One hundred sixty-five paired samples were drawn from 19 ICU patients. The Precision PCx point-of-care meter showed a correlation coefficient of 0.89. Ninety-eight point seven percent of measurements were within zones A and B. The correlation coefficient for the subcutaneous CGMS System Gold was 0.89. One hundred percent of measurements were within zones A and B.

conclusionThe ICU-based blood glucose analyser ABL715 is a rapid and accurate alternative for laboratory glucose determination and can serve as a standard for ICU blood glucose measurements. The Precision PCx is a good alternative, but feasibility may be limited because of the blood sample handling. The subcutaneous CGMS System Gold is promising, but real-time glucose level reporting is necessary before it can be of clinical use in the ICU. When implementing a glucose-insulin algorithm in patient care or research, one should realise that the absolute glucose level may differ systematically among various measuring methods, influencing targeted glucose levels.

Indexed as

Intensive Care UnitsPoint-of-Care SystemsAdultAgedBlood GlucoseCritical IllnessFeasibility StudiesHumansMiddle AgedMonitoring, PhysiologicSensitivity and SpecificityBlood Glucose

Identifiers

PMID16981981
PMCPMC1751062
OpenAlexW2113662426

What OpenQuestion holds

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LicenceCC BY
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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.