Evidence map›Paper›PMID 37622843›Full record

ArticleBiosensors2023

Computation of Vascular Parameters: Implementing Methodology and Performance Analysis.

Mohamed Yacin Sikkandar, Sridharan Padmanabhan, Bobby Mohan, Ibrahim AlMohimeed, Ahmad Alassaf, Shady A Alshewaier, Ali Abdullah Almukil, Sabarunisha Begum

Abstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mohamed Yacin SikkandarDepartment of Medical Equipment Technology, College of Applied Medical Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia.ORCID 0000-0002-7971-1504
Sridharan PadmanabhanDepartment of Biomedical Engineering, Rajalakshmi Engineering College, Chennai 602105, India.
Bobby MohanDepartment of Biomedical Engineering, Rajalakshmi Engineering College, Chennai 602105, India.ORCID 0000-0002-0359-3898
Ibrahim AlMohimeedDepartment of Medical Equipment Technology, College of Applied Medical Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia.
Ahmad AlassafDepartment of Medical Equipment Technology, College of Applied Medical Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia.
Shady A AlshewaierDepartment of Physical Therapy, College of Applied Medical Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia.ORCID 0000-0002-8568-0046
Ali Abdullah AlmukilDepartment of Medical Equipment Technology, College of Applied Medical Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia.
Sabarunisha BegumDepartment of Biotechnology, P.S.R. Engineering College, Sivakasi 626140, India.

Funding

Majmaah University IFP-2022-05
6 · The paper itself

Abstract

This paper presents the feasibility of automated and accurate in vivo measurements of vascular parameters using an ultrasound sensor. The continuous and non-invasive monitoring of certain parameters, such as pulse wave velocity (PWV), blood pressure (BP), arterial compliance (AC), and stiffness index (SI), is crucial for assessing cardiovascular disorders during surgeries and follow-up procedures. Traditional methods, including cuff-based or invasive catheter techniques, serve as the gold standard for measuring BP, which is then manually used to calculate AC and SI through imaging algorithms. In this context, the Continuous and Non-Invasive Vascular Stiffness and Arterial Compliance Screener (CaNVAS) is developed to provide continuous and non-invasive measurements of these parameters using an ultrasound sensor. By driving 5 MHz (ranging from 2.2 to 10 MHz) acoustic waves through the arterial walls, capturing the reflected echoes, and employing pre-processing techniques, the frequency shift is utilized to calculate PWV. It is observed that PWV measured by CaNVAS correlates exponentially with BP values obtained from the sphygmomanometer (BPMR-120), enabling the computation of instantaneous BP values. The proposed device is validated through measurements conducted on 250 subjects under pre- and post-exercise conditions, demonstrating an accuracy of 95% and an average coefficient of variation of 12.5%. This validates the reliability and precision of CaNVAS in assessing vascular parameters.

Indexed as

Cardiovascular DiseasesPulse Wave AnalysisAlgorithmsBlood PressureHumansReproducibility of Resultsacoustic wavesarterial complianceblood pressurepulse wave velocitystiffness index

Identifiers

PMID37622843
PMCPMC10452122

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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 OpenQuestion graph.