Evidence map›Paper›PMID 34382594›Full record

ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2021

Progress in volume assessment for the hemodialysis patients.

Xiejia Li, Fang Yuan, Hong Liu

Open access · greenAbstract read
In one paragraph

Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2021. 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
0.2field-weighted citation impact, top 46% 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

3 authors at 1 institution in 1 country.

Xiejia LiDepartment of Nephrology, Second Xiangya Hospital, Central South University; Institution of Nephrology, Second Xiangya Hospital, Central South University; Hunan Provincial Key Laboratory of Nephrology and Blood Purification, Changsha 410011, China.
Fang YuanDepartment of Nephrology, Second Xiangya Hospital, Central South University; Institution of Nephrology, Second Xiangya Hospital, Central South University; Hunan Provincial Key Laboratory of Nephrology and Blood Purification, Changsha 410011, China.
Hong LiuDepartment of Nephrology, Second Xiangya Hospital, Central South University; Institution of Nephrology, Second Xiangya Hospital, Central South University; Hunan Provincial Key Laboratory of Nephrology and Blood Purification, Changsha 410011, China.
Central South University · CN

Funding

the National Natural Science Foundation 81900696the Natural Science Foundation of Hunan Province 2020JJ5814
6 · The paper itself

Abstract

Volume overload is widespread in the hemodialysis (HD) patients, which is closely related to cardiovascular complications, hospitalization rates, hospitalization costs, and mortality. Meanwhile it is an important independent prognostic risk factor. Some new technologies for volume assessment have made some progress and are gradually applied in clinical practice, such as blood volume monitoring, lung ultrasound examination, bioelectrical impedance analysis, and corrected flow time. The new technologies can provide clinicians more objective and efficient methods for assessing the volume status of the HD patients, which is beneficial to the HD patients because they can achieve an ideal volume balance and improve the prognosis.

Indexed as

Kidney Failure, ChronicBlood VolumeHumansLungRenal DialysisUltrasonographybioelectrical impedanceblood volume monitoringhemodialysislung ultrasoundvolume assessment

Identifiers

PMID34382594
PMCPMC10930120
OpenAlexW3190782284

What OpenQuestion holds

Textmetadata
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.