Evidence map›Paper›PMID 42549834›Full record

ArticleRenal failure2026

Real-world effectiveness of central dialysis fluid delivery system (CDDS) in maintenance hemodialysis: a retrospective multicenter study.

Yashuang Luo, Wendi Cheng, Ruimin Li, Yuyan Fu, Ying Li, Jun Xue, Yin Zheng, Haiyin Wang

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Renal failure, 2026. 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

8 authors.

Yashuang LuoDepartment of Health Technology Assessment, Shanghai Health Development Research Center (Shanghai Medical Information Center), Shanghai, P.R. China.
Wendi ChengDepartment of Health Technology Assessment, Shanghai Health Development Research Center (Shanghai Medical Information Center), Shanghai, P.R. China.ORCID 0000-0002-4198-7767
Ruimin LiDepartment of Statistics and Data Science, Southern University of Science and Technology, ShenZhen, P.R. China.
Yuyan FuDepartment of Health Technology Assessment, Shanghai Health Development Research Center (Shanghai Medical Information Center), Shanghai, P.R. China.
Ying LiDepartment of Nephrology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai, P.R. China.
Jun XueDepartment of Nephrology, Huashan Hospital Affiliated to Fudan University, Shanghai, P.R. China.
Yin ZhengDepartment of Nephrology, Huashan Hospital Affiliated to Fudan University, Shanghai, P.R. China.
Haiyin WangDepartment of Health Technology Assessment, Shanghai Health Development Research Center (Shanghai Medical Information Center), Shanghai, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to compare the real-world effectiveness of a central dialysis fluid delivery system (CDDS) with single-patient dialysis delivery systems (SPDDS) in patients undergoing maintenance hemodialysis (MHD), focusing on inflammation markers, nutritional status, and dialysis adequacy. We conducted a retrospective cohort analysis of 368 MHD patients from three hemodialysis centers in Shanghai, China, between January 2020 and June 2023 was analyzed (CDDS,

Indexed as

Dialysis SolutionsKidney Failure, ChronicRenal DialysisAgedChinaFemaleHemoglobinsHumansInflammationMaleMiddle AgedNutritional StatusRetrospective StudiesDialysis SolutionsHemoglobinscentral dialysis delivery systemHemodialysisinflammationnutritional statusreal-world evidence

Identifiers

PMID42549834
PMCPMC13439772

What OpenQuestion holds

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LicenceCC BY
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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.