Evidence map›Paper›PMID 36120719›Full record

ReviewVascular health and risk management2022

Comparison of Predictive Ability of Arterial Stiffness Parameters Including Cardio-Ankle Vascular Index, Pulse Wave Velocity and Cardio-Ankle Vascular Index

Daiji Nagayama, Kentaro Fujishiro, Kenji Suzuki, Kohji Shirai

Open access · goldAbstract readReview
In one paragraph

Review in Vascular health and risk management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.1field-weighted citation impact, top 11% of its field
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

9 citing papers in PubMed, 14 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Daiji NagayamaDepartment of Internal Medicine, Nagayama Clinic, Tochigi, Japan.ORCID 0000-0001-6119-8012
Kentaro FujishiroResearch and Development Division, Japan Health Promotion Foundation, Tokyo, Japan.ORCID 0000-0003-1824-5746
Kenji SuzukiResearch and Development Division, Japan Health Promotion Foundation, Tokyo, Japan.
Kohji ShiraiInternal Medicine, Mihama Hospital, Chiba, Japan.
Toho University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardio-ankle vascular index (CAVI) was developed to reflect the stiffness of the arterial tree from the aortic origin to the ankle. This arterial stiffness parameter is useful for assessing the severity of cardiovascular disease (CVD) and its risk. However, compared to pulse wave velocity (PWV), the conventional gold standard of arterial stiffness parameter, there has been a concern regarding CAVI that there are fewer longitudinal studies for CVD. Furthermore, the accuracy of CAVI for atherosclerotic diseases compared to other parameters has not been well validated. This review article aims to summarize recent findings to clarify the predictive ability of CAVI in longitudinal studies. First, several large longitudinal studies have found that not only baseline CAVI but also CAVI changes during the observation period predict cardiovascular events. Second, CAVI may have superior discriminatory power for all-cause mortality and major adverse cardiovascular endpoints compared to PWV. Furthermore, one large longitudinal study found CAVI to be a stronger predictor for renal function decline compared to PWV as well as CAVI

Indexed as

Cardiovascular DiseasesVascular StiffnessAnkleHumansLongitudinal StudiesPulse Wave Analysiscardio-ankle vascular indexcardiovascular diseaseCAVI0longitudinal studypulse wave velocityrenal function decline

Identifiers

PMID36120719
PMCPMC9480590
OpenAlexW4295235066

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.