Evidence map›Paper›PMID 41555051›Full record

ReviewDiabetologia2026

Fully closed-loop systems: can people with type 1 diabetes just do it? Insights from open-source systems.

Rayhan Lal, Katarina Braune, Dana M Lewis, Lenka Petruzelkova, Martin de Bock, Sufyan Hussain

Abstract readReview
In one paragraph

Review in Diabetologia, 2026. 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. Review
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

6 authors.

Rayhan Lal *Departments of Medicine & Pediatrics, Division of Endocrinology, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-8055-944X
Katarina Braune *Hasso Plattner Institute for Digital Engineering, University of Potsdam, Potsdam, Germany.ORCID http://orcid.org/0000-0001-6590-245X
Dana M LewisOpenAPS, Seattle, WA, USA.ORCID http://orcid.org/0000-0001-9176-6308
Lenka PetruzelkovaDepartment of Pediatrics, Motol University Hospital and 2nd Faculty of Medicine, Charles University in Prague, Prague, Czech Republic.ORCID http://orcid.org/0000-0002-5535-3474
Martin de BockDepartment of Paediatrics, University of Otago, Christchurch, New Zealand.ORCID http://orcid.org/0000-0003-0454-6679
Sufyan HussainDepartment of Diabetes, School of Cardiovascular, Metabolic Medicine and Sciences, King's College London, London, UK. sufyan.hussain@kcl.ac.uk.ORCID http://orcid.org/0000-0001-6611-8245

Funding

Stanford Islet Research CoreP30DK116074 · NIDDK · STANFORD UNIVERSITY · PI Seung K Kim · 2017 to 2026
$19.5M
The Optimal Pathway to Implanted Autonomous Insulin DeliveryK23DK122017 · NIDDK · STANFORD UNIVERSITY · PI LAL, RAYHAN · 2020 to 2024
$958k
Division of Diabetes, Endocrinology, and Metabolic Diseases P30DK116074Medical Research Council MR/W030004/1NIDDK NIH HHS K23 DK122017NIDDK NIH HHS P30 DK116074
6 · The paper itself

Abstract

Automated insulin delivery (AID) systems have significantly advanced diabetes management, progressively reducing user interactions required for optimal glucose management. This review evaluates the current landscape and future potential of AID systems without meal announcement, particularly focusing on real-world insights from open-source AID (OS-AID) technologies. Although commercial AID systems operating in hybrid closed-loop (HCL) mode have improved glycaemic outcomes, they remain dependent on manual meal announcement and user-driven actions, limiting their real-world utility. Current versions of OS-AID systems, developed by the diabetes community, can allow operation without meal announcements, presenting an opportunity to move closer to truly automated diabetes management. Recent clinical trials suggest that OS-AID systems can effectively manage glucose levels without meal announcements, achieving glucose levels comparable with those obtained by AID systems in HCL mode, with the potential of reduced management burden for users. However, practical challenges persist, including the need for expert configuration and handling of rapid changes in insulin sensitivity, such as during exercise or rapid glucose fluctuations following predicted low-glucose. This review synthesises insights from user and healthcare professional experiences, and emerging clinical evidence. It highlights the fact that successful implementation of AID without meal announcement requires advanced algorithmic responsiveness, user personalisation and ongoing clinician engagement. Looking forward, integrating adjunctive therapies, artificial intelligence and enhanced physiological modelling will likely enhance system performance to drive the next generation of diabetes care towards wider adoption and true 'set-and-forget' functionality.

Indexed as

Diabetes Mellitus, Type 1Hypoglycemic AgentsInsulinInsulin Infusion SystemsBlood GlucoseBlood Glucose Self-MonitoringHumansIntelligent SystemsPancreas, ArtificialBlood GlucoseHypoglycemic AgentsInsulinAIDAutomated insulin deliveryDiabetes technologyDIYFully closed-loopHybrid closed-loopOpen-sourcePatient-led innovationReviewUnannounced meals

Identifiers

PMID41555051
PMCPMC12881006

What Socratic holds

Textmetadata
LicenceCC BY
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.