Evidence map›Paper›PMID 38336639›Full record

ArticleBMC pulmonary medicine2024

Ultrasonic AccV: a potential indicator of peripheral arteriosclerosis in patients with chronic obstructive pulmonary disease.

Li Lin, Yuting Yan, Bin Jiang, Gang Hou, Yan Yin, Lei Wang, Jian Kang, Qiuyue Wang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC pulmonary medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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 at 4 institutions in 1 country.

Li Lin *Department of Pulmonary and Critical Care Medicine, Institute of Respiratory Disease, The First Hospital of China Medical University, No. 155 Nanjing North Street, Shenyang, 110001, China.
Yuting Yan *Department of Critical Care Medicine, The affiliated hospital of Qingdao university, Qingdao, China.
Bin JiangDepartment of Ultrasound, The First Hospital of China Medical University, Shenyang, 110001, China.
Gang HouDepartment of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, Beijing, China.
Yan YinDepartment of Pulmonary and Critical Care Medicine, Institute of Respiratory Disease, The First Hospital of China Medical University, No. 155 Nanjing North Street, Shenyang, 110001, China.
Lei WangDepartment of vascular surgery, The First Hospital of China Medical University, Shenyang, China.
Jian KangDepartment of Pulmonary and Critical Care Medicine, Institute of Respiratory Disease, The First Hospital of China Medical University, No. 155 Nanjing North Street, Shenyang, 110001, China.
Qiuyue WangDepartment of Pulmonary and Critical Care Medicine, Institute of Respiratory Disease, The First Hospital of China Medical University, No. 155 Nanjing North Street, Shenyang, 110001, China. qywang2002@hotmail.com.
China Medical University · CNFirst Hospital of China Medical University · CNChina-Japan Friendship Hospital · CNQingdao University · CN

Funding

National Key Technology Research and Development Program of the 13th National 5-year Development Plan 2016YFC1304103The 73rd batch of grant from China Postdoctoral Science Foundation 2023M733904
6 · The paper itself

Abstract

objectiveThis study aimed to investigate the risk factors for peripheral arteriosclerosis (PAS) and peripheral artery disease (PAD) in chronic obstructive pulmonary disease (COPD) patients and potential ultrasound indicators that could be used to improve detection.

methodOutpatients seeking care between January 1, 2017, and December 31, 2020, in The First Affiliated Hospital of China Medical University were prospectively recruited. Subjects were divided into COPD and non-COPD (control) groups, and the COPD group was further divided into PAD and non-PAD subgroup, at the same time, PAS and non-PAS subgroup. Indicators of PAD -ankle-brachial index (ABI), indicators of PAS- pulse wave velocity (PWV), and ultrasound indices -peak systolic blood flow velocity (PSV) and blood flow acceleration velocity (AccV) were compared.

resultSixty-nine (61.6%) of 112 enrolled subjects had COPD. COPD patients had higher age, and blood pressure (BP)lower than controls. Seventeen (24.6%) COPD patients had PAD, the prevalence of PAD increases with the decrease of lung function, and seven (16.3%) non-COPD patients had PAD, however, there was no significant statistical difference between COPD and non-COPD groups. Fifty (72.5%) COPD patients had PAS, and thirty-four (79.1%) non-COPD patients had PAS, however, there was also no significant difference. The PAS subgroup had higher age, body mass index(BMI), body fat percentage(BFP), lower FEV1 and FEV1/FVC, as well as higher levels of right brachial artery and left dorsalis pedis artery AccV. Factors that correlated with ABI were 6MWD, post-bronchodilator FEV1, FEV1/ FVC, and maximal middle expiratory flow between 75% and 25% of FVC. Age, BP, and 6MWD, but not pulmonary function, were associated with brachial-ankle PWV (baPWV). There was a positive correlation between baPWV and radial artery AccV bilaterally.

conclusionRadial artery AccV correlated well with baPWV, which suggests that ultrasound could be used to assess both morphological and functional changes in vessels, may serving as a better method to identify PAS in high-risk COPD patients.

Indexed as

Peripheral Arterial DiseasePulmonary Disease, Chronic ObstructiveBrachial ArteryHumansPulse Wave AnalysisUltrasonicsAnkle-brachial indexBlood flow acceleration velocityPeak systolic blood flow velocityPeripheral arteriosclerosisPeripheral artery diseasePulse wave velocity

Identifiers

PMID38336639
PMCPMC10854041
OpenAlexW4391680690

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.