Evidence map›Paper›PMID 42814765›Full record

ArticleJMIR formative research2026

Remote Glucose Monitoring Engagement and Glycemic Control in Type 2 Diabetes and Prediabetes: Retrospective Cohort Study.

Yong Huang, Nitish Nagesh, Ajan Subramanian, Li Wang, Zhiyu Liu, Yichen Sun, Weiyi Hou, Iman Azimi, Amir M Rahmani, Randall S Stafford

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In one paragraph

Article in JMIR formative research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Yong Huang *Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.ORCID 0000-0002-3235-3543
Nitish Nagesh *Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.ORCID 0000-0002-9398-6598
Ajan SubramanianDepartment of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.ORCID 0000-0003-3253-1300
Li WangUnika Health, Sunnyvale, CA, United States.ORCID 0009-0000-7300-0990
Zhiyu LiuUnika Health, Sunnyvale, CA, United States.ORCID 0009-0001-6093-4708
Yichen SunUnika Health, Sunnyvale, CA, United States.ORCID 0009-0003-8264-655X
Weiyi HouUnika Health, Sunnyvale, CA, United States.ORCID 0009-0008-3735-0406
Iman AzimiDepartment of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.ORCID 0000-0001-5003-299X
Amir M RahmaniDepartment of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.ORCID 0000-0003-0725-1155
Randall S StaffordStanford University, Palo Alto, CA, United States.ORCID 0000-0003-1805-1271

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Suboptimal glycemic control remains a significant public health challenge among adults with type 2 diabetes and prediabetes, with 47.4% of US adults with diagnosed diabetes having hemoglobin A Objective: This study aimed to estimate the causal dose-response relationship between patient engagement, operationalized as weekly glucose monitoring frequency, and glycemic control measured by HbA Methods: We conducted a retrospective cohort study of 1436 adults with type 2 diabetes or prediabetes enrolled in the Unika Health program between 2019 and 2024. The program integrated Bluetooth-connected glucose meters, a mobile app, structured lifestyle coaching, and primary care coordination across 74 physician practices. Engagement was defined as mean weekly glucose monitoring frequency during the first 6 months. The causal effect of monitoring frequency on 6-month HbA Results: The cohort was predominantly older (95.4%, 1370/1436 aged ≥46 years), with 82.6% (1186/1436) having hypertension and 45.9% (659/1436) classified as obese. Overall, HbA Conclusions: Higher engagement with a digitally enabled, primary care-integrated remote glucose monitoring program was causally associated with significantly greater HbA

Indexed as

Blood Glucose Self-MonitoringDiabetes Mellitus, Type 2Glycemic ControlPatient ParticipationPrediabetic StateAdultAgedBlood GlucoseCohort StudiesFemaleGlycated HemoglobinHumansMaleMiddle AgedRemote Patient MonitoringRetrospective StudiesBlood GlucoseGlycated Hemoglobincausal inferencedigital healthglucose monitoringglycemic controlmarginal structural modelspatient-centered careprediabetic stateremote patient monitoringtype 2 diabetes mellitus

Identifiers

PMID42814765
PMCPMC13626191

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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.