Evidence map›Paper›PMID 36329393›Full record

ArticleBMC medical imaging2022

Cone-beam computed tomography is not a mandatory procedure in adrenal venous sampling for primary hyperaldosteronism.

Ran Cai, Chao Hu, Hai-Yang Li

Abstract read
In one paragraph

Article in BMC medical imaging, 2022. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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. Selective venous sampling for secondary hypertension.Hypertension research : official journal of the Japanese Society of Hypertension · 2024
    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

3 authors.

Ran CaiDepartment of Radiology, The Second Xiangya Hospital of Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, People's Republic of China.
Chao HuDepartment of Radiology, The Second Xiangya Hospital of Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, People's Republic of China. huchao0101@csu.edu.cn.ORCID 0000-0002-0913-2590
Hai-Yang LiDepartment of Radiology, The Second Xiangya Hospital of Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, People's Republic of China. lihaiyang1012@csu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the necessity of cone-beam computed tomography (CBCT) in adrenal venous sampling (AVS).

methodsThis retrospective study included 120 consecutive patients with primary hyperaldosteronism who underwent AVS. Based on the learning curve of the interventional radiologists, the patients were divided into the learning (n = 36) and proficiency (n = 84) groups chronologically. Based on the imaging pattern of the right adrenal vein (RAV), the patients were divided into the typical (n = 36) and atypical (n = 84) groups. The success rate, radiation dose, and sampling time were compared among the entire study population and each subgroup.

resultsA total of 69 patients underwent CBCT, whereas 51 patients did not. The overall success rate was 85.8%, and no difference was noted between patients with and without CBCT (P = 0.347). However, radiation dose (P = 0.018) and sampling time (P = 0.001) were significantly higher in patients who underwent CBCT than in patients who did not. In learning group, CBCT improved success rate from 62.5 to 96.4% (P = 0.028), whereas it was not found in the proficiency group (P = 0.693). Additionally, success rate in patients with an atypical RAV imaging pattern was significantly higher when CBCT was used than when it was not used (P = 0.041), whereas no difference was noted in patients with typical RAV imaging pattern (P = 0.511).

conclusionFor physicians not very experienced doing AVS, there is a clear significant improvement in success rate when CBCT is used. However, CBCT only has minimal benefit for experienced operators, meanwhile CBCT may take an extra time and increase the radiation dose during AVS.

Indexed as

HyperaldosteronismAdrenal GlandsCatheterizationCone-Beam Computed TomographyHumansRetrospective StudiesAdrenal glandsAdrenal venous samplingCone-beam computed tomographyImaging patternLearning curve

Identifiers

PMID36329393
PMCPMC9635157

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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.