Evidence map›Paper›PMID 40231350›Full record

ReviewHypertension (Dallas, Tex. : 1979)2025

Cuffless Blood Pressure Measurement: Where Do We Actually Stand?

Ramakrishna Mukkamala, Sanjeev G Shroff, Konstantinos G Kyriakoulis, Alberto P Avolio, George S Stergiou

Abstract readReview
In one paragraph

Review in Hypertension (Dallas, Tex. : 1979), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Tackling the epidemic of obesity and hypertension in children and young people.Current opinion in nephrology and hypertension · 2026
    Review
  6. Review
  7. The quest for accurate wearable blood pressure monitors.Hypertension research : official journal of the Japanese Society of Hypertension · 2026
    Review
  8. Vascular waveform analysis using Bayesian pulse deconvolution.bioRxiv : the preprint server for biology · 2026
    Article
  9. Article
  10. Remote Blood Pressure Monitoring: A Comprehensive Review.American journal of hypertension · 2026
    Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Nocturnal blood pressure burden: towards a better understanding of the OSA-hypertension relationship.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Article
  19. Article
  20. Review
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

5 authors.

Ramakrishna MukkamalaDepartment of Bioengineering (R.M., S.G.S.), University of Pittsburgh, PA.ORCID 0000-0001-8918-4050
Sanjeev G ShroffDepartment of Bioengineering (R.M., S.G.S.), University of Pittsburgh, PA.ORCID 0000-0003-1868-3826
Konstantinos G KyriakoulisHypertension Center STRIDE-7, School of Medicine, Third Department of Medicine, Sotiria Hospital, National and Kapodistrian University of Athens, Greece (K.G.K., G.S.S.).ORCID 0000-0001-8986-2704
Alberto P AvolioMacquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, New South Wales, Australia (A.P.A.).ORCID 0000-0002-8311-2010
George S StergiouHypertension Center STRIDE-7, School of Medicine, Third Department of Medicine, Sotiria Hospital, National and Kapodistrian University of Athens, Greece (K.G.K., G.S.S.).ORCID 0000-0002-6132-0038

Funding

A Smartphone-Based Device for Cuff-Less and Calibration-Free Blood Pressure MonitoringR01HL146470 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MUKKAMALA, RAMAKRISHNA · 2019 to 2022
$1.1M
NHLBI NIH HHS R01 HL146470
6 · The paper itself

Abstract

Cuffless blood pressure (BP) measurement offers considerable potential for clinical practice but is a challenging technological field. Many are investigating pulse wave analysis with or without pulse arrival time in which machine learning is applied to pulsatile waveforms obtained with mobile devices (eg, wristbands, smartphones) to estimate BP. These methods generally require individual user calibration with cuff BP measurements or demographics (eg, age, sex). This calibration makes it difficult to evaluate the method's accuracy, and many studies claiming accuracy used inadequate testing procedures. Yet, publications and regulatory-cleared devices continue to rise, seemingly implying technological advancements. An update is provided on the flurry of activity in cuffless BP technologies over the last 2 to 3 years, covering the clinical need, the latest devices, recent publications based on pulse wave analysis and pulse arrival time, progress in developing validation standards for cuffless BP devices, and recent publications on other cuffless BP measurement principles. Despite the high volume of research and development, to date, there is no compelling evidence that pulse wave analysis and pulse arrival time can provide significant added value in BP measurement accuracy beyond the cuff BP or demographic data for calibration. Thus, it is reasonable to at least be skeptical of published and future studies on pulse wave analysis and pulse arrival time for cuffless BP measurement with uncertain testing procedures. It is important to focus on establishing robust validation standards for cuffless BP devices requiring individual user calibration and also pursuing cuffless and calibration-free BP measurement methodologies going forward.

Indexed as

Blood PressureBlood Pressure DeterminationHypertensionPulse Wave AnalysisHumansReproducibility of Resultsartificial intelligenceblood pressure determinationcalibrationmachine learningphotoplethysmographypulse wave analysis

Identifiers

PMID40231350
PMCPMC12331212

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.