Evidence map›Paper›PMID 24180327›Full record

Trial reportDiabetes technology & therapeutics2014

Accuracy of subcutaneous continuous glucose monitoring in critically ill adults: improved sensor performance with enhanced calibrations.

Lalantha Leelarathna, Shane W English, Hood Thabit, Karen Caldwell, Janet M Allen, Kavita Kumareswaran, Malgorzata E Wilinska, Marianna Nodale, Ahmad Haidar, Mark L Evans and 2 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Diabetes technology & therapeutics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

27 citing papers in PubMed, 46 citations in OpenAlex.

  1. Trial
  2. Feasibility of automated insulin delivery guided by continuous glucose monitoring in preterm infants.Archives of disease in childhood. Fetal and neonatal edition · 2020
    Trial
  3. Targeting glucose control in preterm infants: pilot studies of continuous glucose monitoring.Archives of disease in childhood. Fetal and neonatal edition · 2019
    Trial
  4. Trial
  5. Trial
  6. Strategies for optimization of hypoglycemia rat models.Animal models and experimental medicine · 2025
    Review
  7. Article
  8. Review
  9. Article
  10. Continuous Glucose Monitoring in the Intensive Care Unit.Journal of diabetes science and technology · 2023
    Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Consensus Statement on Inpatient Use of Continuous Glucose Monitoring.Journal of diabetes science and technology · 2017
    Article
  19. Inpatient Continuous Glucose Monitoring and Glycemic Outcomes.Journal of diabetes science and technology · 2017
    Review
  20. 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

12 authors at 2 institutions in 1 country.

Lalantha Leelarathna1 Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge , Cambridge, United Kingdom .
Shane W English
Hood Thabit
Karen Caldwell
Janet M Allen
Kavita Kumareswaran
Malgorzata E Wilinska
Marianna Nodale
Ahmad Haidar
Mark L Evans
Rowan Burnstein
Roman Hovorka
University of Cambridge · GBAddenbrooke's Hospital · GB

Funding

Wellcome Trust 100574
6 · The paper itself

Abstract

objectiveAccurate real-time continuous glucose measurements may improve glucose control in the critical care unit. We evaluated the accuracy of the FreeStyle(®) Navigator(®) (Abbott Diabetes Care, Alameda, CA) subcutaneous continuous glucose monitoring (CGM) device in critically ill adults using two methods of calibration. SUBJECTS AND

methodsIn a randomized trial, paired CGM and reference glucose (hourly arterial blood glucose [ABG]) were collected over a 48-h period from 24 adults with critical illness (mean±SD age, 60±14 years; mean±SD body mass index, 29.6±9.3 kg/m(2); mean±SD Acute Physiology and Chronic Health Evaluation score, 12±4 [range, 6-19]) and hyperglycemia. In 12 subjects, the CGM device was calibrated at variable intervals of 1-6 h using ABG. In the other 12 subjects, the sensor was calibrated according to the manufacturer's instructions (1, 2, 10, and 24 h) using arterial blood and the built-in point-of-care glucometer.

resultsIn total, 1,060 CGM-ABG pairs were analyzed over the glucose range from 4.3 to 18.8 mmol/L. Using enhanced calibration median (interquartile range) every 169 (122-213) min, the absolute relative deviation was lower (7.0% [3.5, 13.0] vs. 12.8% [6.3, 21.8], P<0.001), and the percentage of points in the Clarke error grid Zone A was higher (87.8% vs. 70.2%).

conclusionsAccuracy of the Navigator CGM device during critical illness was comparable to that observed in non-critical care settings. Further significant improvements in accuracy may be obtained by frequent calibrations with ABG measurements.

Indexed as

Critical IllnessMonitoring, PhysiologicBiosensing TechniquesBlood GlucoseCalibrationFemaleGlycated HemoglobinHumansHyperglycemiaIntensive Care UnitsMalePredictive Value of TestsProspective StudiesReproducibility of ResultsBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID24180327
PMCPMC3894676
OpenAlexW2330296161

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.