Evidence map›Paper›PMID 42651080›Full record

ReviewDiagnostics (Basel, Switzerland)2026

Multimodal Diagnostic Ultrasound for Congestion, Perfusion, and Ultrafiltration Tolerance in Maintenance Hemodialysis: A Narrative Review.

Kexin Yin, Jie Sun, Kun Liu

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 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

3 authors.

Kexin YinDepartment of Ultrasound Medicine, The Third People's Hospital of Hubei Province Graduate Joint Training Base, School of Medicine, Wuhan University of Science and Technology, Wuhan 430033, China.ORCID 0009-0004-1295-7317
Jie SunDepartment of Ultrasound Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.ORCID 0000-0001-5732-3183
Kun LiuDepartment of Ultrasound Medicine, Third People's Hospital of Hubei Province, Wuhan 430033, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMaintenance hemodialysis is characterized by repetitive changes in fluid distribution, blood pressure, and organ perfusion. Conventional clinical examination, empirical dry-weight adjustment, and biomarkers do not fully resolve the compartment-specific nature of congestion in this population. This narrative review reframes ultrasound-based volume assessment as a multimodal diagnostic problem involving pulmonary congestion, intravascular filling, systemic venous congestion, cardiac reserve, tissue response, and perfusion vulnerability.

methodsWe synthesized clinically relevant evidence indexed in PubMed and Google Scholar for studies published between January 2016 and April 2026, prioritizing dialysis-specific randomized trials, prospective cohorts, systematic reviews, consensus statements, and methodological studies related to diagnostic ultrasound, Doppler-based congestion assessment, contrast-enhanced ultrasound, elastography, artificial intelligence, point-of-care ultrasound, and remote ultrasound monitoring.

resultsLung ultrasound currently has the strongest dialysis-specific evidence for detecting and tracking pulmonary congestion. Inferior vena cava ultrasound provides adjunctive information on intravascular filling and right-sided pressure but is not a surrogate for total body water. Echocardiographic parameters help characterize filling pressure and cardiac tolerance to fluid removal, whereas venous Doppler and the Venous Excess Ultrasound Score provide an emerging approach to systemic venous congestion. Elastography and contrast-enhanced ultrasound remain investigational tools for tissue characterization and perfusion vulnerability, while AI-assisted analysis, handheld point-of-care ultrasound, and tele-ultrasound may improve standardization, automated B-line quantification, and scalability.

conclusionsDifferent ultrasound modalities answer different diagnostic questions in maintenance hemodialysis. A compartment-specific framework integrating congestion, perfusion, and cardiac-reserve domains may better support individualized ultrafiltration planning, hemodynamic risk assessment, and future outcome-oriented research.

Indexed as

artificial intelligencediagnostic ultrasoundhemodialysislung ultrasoundultrafiltration tolerancevenous congestion

Identifiers

PMID42651080
PMCPMC13512204

What OpenQuestion holds

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Registered trials

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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.