Evidence mapPaperPMID 41250885Full record

ArticleDiabetes, obesity & metabolism2026

Despite lower haemoglobin A1c with second-generation automated insulin delivery systems, mental burden remains high for all adults with type 1 diabetes: A BETTER registry analysis.

Zekai Wu, Laure Alexandre-Heymann, Maha Lebbar, Meryem K Talbo, Aude Bandini, Tamanna Chahal, Caroline Grou, Virginie Messier, Valérie Boudreau, Anne-Sophie Brazeau and 1 more

Abstract read
In one paragraph

Article in Diabetes, obesity & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

11 authors.

Zekai WuDivision of Experimental Medicine, Department of Medicine, McGill University, Montreal, Quebec, Canada.ORCID 0000-0002-0671-1888
Laure Alexandre-HeymannMontreal Clinical Research Institute, Montreal, Quebec, Canada.
Maha LebbarDivision of Experimental Medicine, Department of Medicine, McGill University, Montreal, Quebec, Canada.
Meryem K TalboSchool of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, Quebec, Canada.ORCID 0000-0002-7717-3335
Aude BandiniDepartment of Philosophy, Faculty of Arts and Sciences, Université de Montréal, Montreal, Quebec, Canada.
Tamanna ChahalDivision of Experimental Medicine, Department of Medicine, McGill University, Montreal, Quebec, Canada.
Caroline GrouMontreal Clinical Research Institute, Montreal, Quebec, Canada.
Virginie MessierMontreal Clinical Research Institute, Montreal, Quebec, Canada.
Valérie BoudreauMontreal Clinical Research Institute, Montreal, Quebec, Canada.
Anne-Sophie BrazeauMontreal Clinical Research Institute, Montreal, Quebec, Canada.ORCID 0000-0002-2699-2920
Rémi Rabasa-LhoretDivision of Experimental Medicine, Department of Medicine, McGill University, Montreal, Quebec, Canada.ORCID 0000-0003-4706-5170

Funding

Juvenile Diabetes Research Foundation Canada 3-SRA-2024-1523-M-NStrategy for Patient-Oriented Research JT1-157204
6 · The paper itself

Abstract

objectiveWe aim to compare second-generation automated insulin delivery systems (AIDs) with other treatment modalities regarding both glucose management outcomes and person-reported outcomes/experiences (PROs/PREs, measured by the Hypoglycemia Fear Survey, Hypoglycemic Confidence Scale, Hyperglycemia Avoidance Scale, Diabetes Distress Scale, Pittsburgh Sleep Quality Index, Well-being Scale, and treatment satisfaction) among adults with type 1 diabetes. RESEARCH DESIGN AND

methodsCross-sectional analysis of the Canadian BETTER type 1 diabetes registry. Adult participants were divided into five groups: second-generation AIDs, first-generation AIDs, continuous glucose monitoring (CGM) + pump, CGM + multiple daily injections (MDI), and non-CGM using MDI or pump. Generalized linear models were used to assess differences between the second-generation AID group and each of the other groups, with p < 0.05 considered significant.

resultsAmong 1731 participants (69.2% females), mean age was 45.3 ± 15.3 years with 24.7 ± 16.0 years of diabetes. The second-generation AID group had the highest proportion of achieving target haemoglobin A1c ≤ 7% (58.1%) compared to 40.6% in the first-generation AID group, 40.5% in the Pump + CGM group, 37.3% in the MDI + CGM group, and 32.3% in the non-CGM group, even after adjustment for multiple imbalanced characteristics (p < 0.001). While second-generation AID users reported higher treatment satisfaction, no other differences in measures of PROs/PREs were found between second-generation AID and other groups. Elevated diabetes distress (55%) and poor sleep quality (63%) remained common across all treatment groups, and even among those who had reached the optimal HbA1c target (48% and 60%, respectively).

conclusionsIn real-world settings, second-generation AIDs were associated with lower haemoglobin A1c and higher treatment satisfaction but not better PROs/PREs. Mental burden remained high despite the use of advanced diabetes technologies and optimal glucose management.

Indexed as

Diabetes Mellitus, Type 1Glycated HemoglobinHypoglycemic AgentsInsulinInsulin Infusion SystemsAdultBlood GlucoseBlood Glucose Self-MonitoringCanadaCross-Sectional StudiesFemaleGlycemic ControlHumansHypoglycemiaMaleMiddle AgedBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanHypoglycemic AgentsInsulinautomated insulin delivery systemglucose managementperson‐reported outcomes/person‐reported experiencesreal‐world studytype 1 diabetes

Identifiers

PMID41250885
PMCPMC12803586

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.