Evidence mapPaperPMID 35133284Full record

ArticleJournal of medical Internet research2022

Blood Pressure Monitoring as a Digital Health Tool for Improving Diabetes Clinical Outcomes: Retrospective Real-world Study.

Yifat Fundoiano-Hershcovitz, Dror Bacher, Marilyn D Ritholz, David L Horwitz, Omar Manejwala, Pavel Goldstein

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 12 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-HershcovitzDarioHealth, Caesarea, Israel.ORCID 0000-0002-8526-0252
Dror BacherDarioHealth, Caesarea, Israel.ORCID 0000-0001-8610-4617
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
Omar ManejwalaDarioHealth, 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

backgroundRemote data capture for blood glucose (BG) or blood pressure (BP) monitoring and the use of a supportive digital app are becoming the model in diabetes and hypertension chronic care. One of the goals in chronic condition management is to increase awareness and generate behavioral change in order to improve outcomes in diabetes and related comorbidities, such as hypertension. In addition, there is a lack of understanding of the association between BG and BP levels when using digital health tools.

objectiveBy applying a rigorous study framework to digital health data, this study investigated the relationship between BP monitoring and BG and BP levels, as well as a lagged association between BP and BG. We hypothesized that during the first 6 months of BP monitoring, BG and BP levels would decrease. Finally, we suggested a positive association between BP levels and the following month's BG levels.

methodsIn this retrospective, real-world case-control study, we extracted the data of 269 people with type 2 diabetes (T2D) who tracked their BG levels using the Dario digital platform for a chronic condition. We analyzed the digital data of the users who, in addition to BG, monitored their BP using the same app (BP-monitoring [BPM] group, n=137) 6 months before and after starting their BP monitoring. Propensity score matching established a control group, no blood pressure monitoring (NBPM, n=132), matched on demographic and baseline clinical measures to the BPM group. A piecewise mixed model was used for analyzing the time trajectories of BG, BP, and their lagged association.

resultsAnalysis revealed a significant difference in BG time trajectories associated with BP monitoring in BPM and NBPM groups (t=-2.12, P=.03). The BPM group demonstrated BG reduction improvement in the monthly average BG levels during the first 6 months (t=-3.57, P<.001), while BG did not change for the NBPM group (t=0.39, P=.70). Both groups showed similarly stable BG time trajectories (B=0.98, t=1.16, P=.25) before starting the use of the BP-monitoring system. In addition, the BPM group showed a significant reduction in systolic (t=-6.42, P<.001) and diastolic (t=-4.80, P<.001) BP during the first 6 months of BP monitoring. Finally, BG levels were positively associated with systolic (B=0.24, t=2.77, P=.001) and diastolic (B=0.30, t=2.41, P=.02) BP.

conclusionsThe results of this study shed light on the association between BG and BP levels and on the role of BP self-monitoring in diabetes management. Our findings also underscore the need and provide a basis for a comprehensive approach to understanding the mechanism of BP regulation associated with BG.

Indexed as

Diabetes Mellitus, Type 2HypertensionMobile ApplicationsBlood PressureCase-Control StudiesHumansRetrospective Studiesappblood glucoseblood pressurechronic diseasediabetesdigital therapeutichealth datahypertensionmodelmonitoring

Identifiers

PMID35133284
PMCPMC8864523
OpenAlexW4210902264

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.