Evidence map›Paper›PMID 40566789›Full record

ReviewSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2025

[Research progress in central aortic pressure estimation algorithms].

Shuo Du, Shuran Zhou, Guanglei Wang, Haijun Zhu, Lisheng Xu

Abstract readReviewEnglish Abstract
In one paragraph

Review in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2025. 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
–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

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

5 authors.

Shuo DuCollege of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R .China.
Shuran ZhouCenter of Clinical Aerospace Medicine, School of Aerospace Medicine, Key Laboratory of Aerospace Medicine of Ministry of Education, Air Force Medical University, Xi'an 710032, P. R. China.
Guanglei WangCollege of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R .China.
Haijun ZhuCollege of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P. R .China.
Lisheng XuCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110016, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertension is a major factor leading to cardiovascular events and death, and accurate blood pressure measurement is a fundamental means of evaluating blood pressure levels, achieving hypertension diagnosis, and observing antihypertensive efficacy. Compared to traditional brachial pressure, central aortic pressure (CAP) exhibits a stronger correlation with cardiovascular events. However, its non-invasive detection technology has not yet been widely adopted in clinical practice. In order to promote the clinical application of CAP and optimize blood pressure management, this article systematically summarizes the research progress of CAP estimation algorithms. These algorithms were categorized into three types: direct substitution methods, generalized model-based methods and personalized estimation methods. The characteristics and clinical adaptability of each algorithm were analyzed. The findings highlight that CAP estimation algorithms are moving towards personalization and non-linearity.

Indexed as

AlgorithmsArterial PressureBlood PressureBlood Pressure DeterminationHypertensionAortaHumansCentral aortic pressureHypertensionNon-invasive estimation

Identifiers

PMID40566789
PMCPMC12236221

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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.