Evidence mapPaperPMID 38564266Full record

Trial reportJournal of medical Internet research2024

The Impact of Digital Self-Monitoring of Weight on Improving Diabetes Clinical Outcomes: Quasi-Randomized Study.

Yifat Fundoiano-Hershcovitz, Marilyn D Ritholz, David L Horwitz, Ephraim Behar, Omar Manejwala, Pavel Goldstein

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2024. 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
2.5field-weighted citation impact, top 11% of its field
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, 3 citations in OpenAlex.

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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

6 authors at 2 institutions in 2 countries.

Yifat Fundoiano-HershcovitzDario Health, Caesarea, Israel.ORCID 0000-0002-8526-0252
Marilyn D RitholzJoslin Diabetes Center, Harvard Medical School, Boston, MA, United States.ORCID 0000-0002-5020-4621
David L HorwitzDLH Biomedical Consulting, Las Vegas, NV, United States.ORCID 0000-0001-5801-1640
Ephraim BeharDario Health, Caesarea, Israel.ORCID 0009-0007-8927-9376
Omar ManejwalaDario Health, Caesarea, Israel.ORCID 0000-0002-6450-6831
Pavel GoldsteinSchool of Public Health, University of Haifa, Haifa, Israel.ORCID 0000-0002-5224-1725
Joslin Diabetes Center · USUniversity of Haifa · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe management of type 2 diabetes (T2D) and obesity, particularly in the context of self-monitoring, remains a critical challenge in health care. As nearly 80% to 90% of patients with T2D have overweight or obesity, there is a compelling need for interventions that can effectively manage both conditions simultaneously. One of the goals in managing chronic conditions is to increase awareness and generate behavioral change to improve outcomes in diabetes and related comorbidities, such as overweight or obesity. There is a lack of real-life evidence to test the impact of self-monitoring of weight on glycemic outcomes and its underlying mechanisms.

objectiveThis study aims to assess the efficacy of digital self-monitoring of weight on blood glucose (BG) levels during diabetes management, investigating whether the weight changes may drive glucose fluctuations.

methodsIn this retrospective, real-world quasi-randomized study, 50% of the individuals who regularly used the weight monitoring (WM) feature were propensity score matched with 50% of the users who did not use the weight monitoring feature (NWM) based on demographic and clinical characteristics. All the patients were diagnosed with T2D and tracked their BG levels. We analyzed monthly aggregated data 6 months before and after starting their weight monitoring. A piecewise mixed model was used for analyzing the time trajectories of BG and weight as well as exploring the disaggregation effect of between- and within-patient lagged effects of weight on BG.

resultsThe WM group exhibited a significant reduction in BG levels post intervention (P<.001), whereas the nonmonitoring group showed no significant changes (P=.59), and both groups showed no differences in BG pattern before the intervention (P=.59). Furthermore, the WM group achieved a meaningful decrease in BMI (P<.001). Finally, both within-patient (P<.001) and between-patient (P=.008) weight variability was positively associated with BG levels. However, 1-month lagged back BMI was not associated with BG levels (P=.36).

conclusionsThis study highlights the substantial benefits of self-monitoring of weight in managing BG levels in patients with diabetes, facilitated by a digital health platform, and advocates for the integration of digital self-monitoring tools in chronic disease management. We also provide initial evidence of testing the underlying mechanisms associated with BG management, underscoring the potential role of patient empowerment.

Indexed as

Diabetes Mellitus, Type 2Digital HealthHumansObesityOverweightRetrospective Studiesblood glucoseclinical outcomediabetes managementdigital health platformobesitypatient empowermentself-monitoringtype 2 diabetesweight changesweight monitoring

Identifiers

PMID38564266
PMCPMC11022133
OpenAlexW4393399355

What Socratic holds

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LicenceCC BY
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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.