Evidence map›Paper›PMID 41355764›Full record

ArticleDiabetes technology & therapeutics2026

Variation in Hypoglycemia Risk During Real-World Physical Activity in Adults with Type 1 Diabetes: Insights from the Type 1 Diabetes Exercise Initiative.

Mehak Dhaliwal, Kenan Tang, Eleonora M Aiello, Dessi P Zaharieva, Rayhan A Lal, Cameron Summers, Brandon Arbiter, Kelly Watson, Mark J Connolly, Lauren E Figg and 6 more

Abstract read
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In one paragraph

Article in Diabetes technology & therapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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

16 authors.

Mehak DhaliwalUniversity of California, Santa Barbara, California, USA.
Kenan TangUniversity of California, Santa Barbara, California, USA.
Eleonora M AielloDepartment of Computer Science and Engineering, University of Trento, Povo di Trento, Italy.
Dessi P ZaharievaDivision of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Rayhan A LalDivision of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Cameron SummersTidepool, Palo Alto, California, USA.
Brandon ArbiterTidepool, Palo Alto, California, USA.
Kelly WatsonTidepool, Palo Alto, California, USA.
Mark J ConnollyTidepool, Palo Alto, California, USA.
Lauren E FiggDivision of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Ilenia BalistreriDivision of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Ana L CortesDivision of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Ryan S KingmanDivision of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Bailey SuhDivision of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Michael C RiddellSchool of Kinesiology and Health Science, Faculty of Health, Muscle Health Research Centre, York University, Toronto, Canada.
Yao QinUniversity of California, Santa Barbara, California, USA.

Funding

Stanford Islet Research CoreP30DK116074 · STANFORD UNIVERSITY · 2025 to 2025
$2.0M
NIDDK NIH HHS K23 DK122017NIDDK NIH HHS P30 DK116074
6 · The paper itself

Abstract

backgroundPhysical activity (PA) poses significant challenges in glucose management for individuals with type 1 diabetes (T1D). Real-world PA is more frequent than structured PA, but remains underexplored. We analyzed 8171 real-world PA sessions comprising 45 activity types from the Type 1 Diabetes Exercise Initiative, examining hypoglycemia risk correlations with PA-level and population-level factors.

methodsHypoglycemia risk was measured by change in continuous glucose monitoring (ΔCGM) from PA onset to end, low blood glucose index (LBGI), and hypoglycemia event occurrence. Primary analyses used analysis of variance and Tukey's range test to measure correlations. Secondary analyses compared risk across activity types and categories (aerobic, mixed, and anaerobic).

resultsHigher hypoglycemia risk was associated with longer PA duration (median [Interquartile Range (IQR)] ΔCGM -24 [-60, 11] mg/dL for 60-120 min vs. -12 [-31, 5] mg/dL for 15-30 min), lower starting glucose (90% of sessions starting <50 mg/dL had hypoglycemia), and declining glucose rates before PA (all

conclusionsReal-world PA has a highly variable glycemic impact, with longer duration, lower starting glucose, and higher IoB increasing hypoglycemia risk. Glycemic responses differed significantly by activity type, with aerobic activities resulting in the greatest decline. These findings highlight the need for tailored strategies to mitigate PA-related hypoglycemia in T1D.

Indexed as

Diabetes Mellitus, Type 1ExerciseHypoglycemiaAdultBlood GlucoseBlood Glucose Self-MonitoringFemaleHumansHypoglycemic AgentsInsulinMaleMiddle AgedRisk FactorsYoung AdultBlood GlucoseHypoglycemic AgentsInsulincontinuous glucose monitoringexercisehypoglycemiaphysical activitytype 1 diabetes

Identifiers

PMID41355764
PMCPMC12915491

What Socratic holds

Textmetadata
LicenceTDM
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.