ReviewHypertension research : official journal of the Japanese Society of Hypertension2026
Digital hypertension in 2024-2025: emerging evidence and future directions.
Review in Hypertension research : official journal of the Japanese Society of Hypertension, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advances in digital technology are remarkable, and they are driving profound transformations in healthcare and medical research. Within this context, digital hypertension has emerged as a multidisciplinary paradigm that integrates novel digital technologies into the prevention, diagnosis, and management of hypertension. Digital hypertension encompasses diverse domains such as advanced sensor development, continuous physiological monitoring, information processing, artificial intelligence, big data analytics, digital therapeutics, and telemedicine. These innovations enable more personalized, efficient, and data-driven hypertension care. A growing body of research has explored applications ranging from home-based blood pressure monitoring systems to AI-assisted risk prediction models and remote therapeutic interventions, producing promising and clinically relevant outcomes. This review summarizes the latest evidence, highlights technological and clinical advances, and discusses future perspectives and challenges for the broader adoption of digital hypertension strategies.
Indexed as
Identifiers
41593333What Socratic holds
Registered trials
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.