Evidence mapPaperPMID 39372467Full record

ArticleJACC. Advances2024

Digital Twin in Managing Hypertension Among People With Type 2 Diabetes: 1-Year Randomized Controlled Trial.

Paramesh Shamanna, Shashank Joshi, Mala Dharmalingam, Arun Vadavi, Ashok Keshavamurthy, Lisa Shah, Shambo Samrat Samajdar, Jeffrey I Mechanick

Abstract read
In one paragraph

Article in JACC. Advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Human digital twins in women's health nursing.Women's health nursing (Seoul, Korea) · 2026
    Article
  3. Article
  4. Article
  5. Analysis of digital twin applications in nursing practice and education: a scoping review.Journal of educational evaluation for health professions · 2026
    Article
  6. Article
  7. Review
  8. Review
  9. Review
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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

8 authors.

Paramesh ShamannaDepartment of Diabetes, Bangalore Diabetes Centre, Bangalore, Karnataka, India. Electronic address: drparamesh2@gmail.com.
Shashank JoshiDepartment of Diabetology and Endocrinology, Lilavati Hospital and Research Center, Mumbai, India.
Mala DharmalingamMS Ramaiah Medical College, Bangalore Endocrinology & Diabetes Research Centre, Bangalore, Karnataka, India.
Arun VadaviDepartment of Diabetes, Sudha Prevention Centre, Bangalore, Karnataka, India.
Ashok KeshavamurthyDepartment of Diabetes, Chandana Clinic, Bangalore, Karnataka, India.
Lisa ShahTwin Health, Mountain View, California.
Shambo Samrat SamajdarDepartment of Clinical and Experimental Pharmacology, Calcutta School of Tropical Medicine, Kolkata, India.
Jeffrey I MechanickThe Marie-Josee and Henry R. Kravis Center for Cardiovascular Health at Mount Sinai Fuster Heart Hospital, New York City, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Digital twin (DT)-guided lifestyle changes induce type 2 diabetes (T2D) remission but effects on hypertension (HTN) in this population are unknown. Objectives: The purpose of this study was to assess effects of DT vs standard of care (SC) on blood pressure (BP), anti-HTN medication, HTN remission, and microalbuminuria in participants with T2D. Methods: This is a secondary analysis of a randomized controlled trial in India of 319 participants with T2D. Participants were randomized to DT group (N = 233), which used artificial intelligence-enabled DT technology, or SC group (N = 86). A Home Blood Pressure Monitoring system guided anti-HTN medication adjustments. BP, anti-HTN medications, HTN remission rates, and microalbuminuria were compared between groups. Results: Among the 319 participants, 44 in DT and 15 in SC group were on anti-HTN medications, totaling 59 (18.4%) participants. DT group achieved significant reductions in systolic blood pressure (-7.6 vs -3.2 mm Hg; Conclusions: Artificial intelligence -enabled DT technology is more effective than SC in reducing BP and anti-HTN medications and inducing HTN remission and normoalbuminuria in participants with HTN and T2D. (A Novel WholeBody Digital Twin Enabled Precision Treatment for Reversing Diabetes; CTRI/2020/08/027072).

Indexed as

artificial intelligencedigital twinhypertension remissioninternet of thingsnormoalbuminurianormotension

Identifiers

PMID39372467
PMCPMC11450914

What Socratic holds

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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.