Evidence map›Paper›PMID 39888427›Full record

ArticleDiabetologia2025

Comparison of continuous glucose monitoring with self-monitoring of blood glucose in type 1 diabetes in the changing atmospheric pressures in aviation: a hypobaric flight simulation.

Ka Siu Fan, Antonios Manoli, Petra M Baumann, Fariba Shojaee-Moradie, Fereshteh Jeivad, Gerd Koehler, Monika Cigler, A Margot Umpleby, David Russell-Jones, Julia K Mader and 1 more

Abstract readComparative Study
In one paragraph

Article in Diabetologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Ka Siu FanDiscipline of Nutrition, Exercise, Sleep and Chronobiology, University of Surrey, Guildford, UK. k.fan@surrey.ac.uk.ORCID http://orcid.org/0000-0002-0861-1944
Antonios ManoliDepartment of Diabetes and Endocrinology, Medical University of Graz, Graz, Austria.
Petra M BaumannDepartment of Diabetes and Endocrinology, Medical University of Graz, Graz, Austria.ORCID http://orcid.org/0000-0002-7665-0929
Fariba Shojaee-MoradieDiscipline of Nutrition, Exercise, Sleep and Chronobiology, University of Surrey, Guildford, UK.ORCID http://orcid.org/0000-0002-3514-0447
Fereshteh JeivadCEDAR Centre, Royal Surrey County Hospital, Guildford, UK.
Gerd KoehlerDepartment of Diabetes and Endocrinology, Medical University of Graz, Graz, Austria.
Monika CiglerDepartment of Diabetes and Endocrinology, Medical University of Graz, Graz, Austria.ORCID http://orcid.org/0000-0001-5827-7991
A Margot UmplebyCEDAR Centre, Royal Surrey County Hospital, Guildford, UK.ORCID http://orcid.org/0000-0001-6147-7919
David Russell-JonesDiscipline of Nutrition, Exercise, Sleep and Chronobiology, University of Surrey, Guildford, UK. d.russell-jones@surrey.ac.uk.ORCID http://orcid.org/0000-0002-9490-2480
Julia K MaderDepartment of Diabetes and Endocrinology, Medical University of Graz, Graz, Austria.ORCID http://orcid.org/0000-0001-7854-4233
EASA Diabetes Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aim/hypothesisPilots with type 1 diabetes are required to perform capillary glucose monitoring regularly during flights. Continuous glucose monitoring (CGM) may be an effective and more practical alternative. This study aimed to assess the accuracy of CGM systems against self-monitoring of blood glucose (SMBG) during a hypobaric flight simulation.

methodsTwelve insulin pump users with type 1 diabetes were studied using two simulation protocols. Protocol A consisted of a ground phase, ascent, a 190 min cruise with ingestion of a liquid meal, descent and then ground. Protocol B consisted of a ground phase, ascent, a 60 min cruise while fasting, descent, a 20 min ground phase, ascent, a second flight of 120 min with ingestion of a meal, followed by descent and ground. Insulin was administered with or before the meal according to the participants' carbohydrate-counting regimen during both protocols. In Protocol A, capillary, interstitial and plasma glucose were measured during flight and at ground, while in Protocol B, glucose and oxygen were measured. Measurements from three CGM brands and two SMBG devices were recorded during the flight simulations. Findings at cabin pressures during flight (550 mmHg) and ground (750 mmHg) were compared. Fasted and postprandial glucose measurements were analysed using Spearman's correlations and mean absolute relative differences (MARDs).

resultsEleven men and one woman (n=6 men in Protocol A; n=5 men and n=1 woman in Protocol B) were studied. A total of 1533 data points were recorded. During flight vs ground level, Spearman's correlations for CGM system- and SMBG-derived glucose values were very strong in both Protocol A (r=0.96 during flight vs r=0.94 at ground) and Protocol B (r=0.85 during flight vs r=0.69 at ground). The differences in aggregated CGM MARDs during flight vs ground level were minimal across Protocol A (11.85%; 95% CI [9.78, 13.92] vs 9.08%; 95% CI [7.02, 11.14]) and Protocol B (12.01%; 95% CI [3.34, 20.69] vs 12.97%; 95% CI [4.30, 21.65]). CONCLUSIONS/

interpretationThe performance of CGM systems and SMBG are comparable during flight-associated atmospheric pressure changes. All tested measurement devices for CGM and SMBG were suitable for diabetes-care-based decisions during flight simulation.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 1AdultAtmospheric PressureAviationContinuous Glucose MonitoringFemaleHumansInsulinInsulin Infusion SystemsMaleMiddle AgedBlood GlucoseInsulinAviationContinuous glucose monitoring (CGM)PilotSelf-monitoring of blood glucose (SMBG)

Identifiers

PMID39888427
PMCPMC12021693

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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.