Evidence map›Paper›PMID 42478470›Full record

ReviewRenal failure2026

Augmented renal clearance: from pathophysiological mechanisms to clinical implications and research perspectives.

Beiming Xu, Minqiao Chen, Yang Chu

Abstract readReview
In one paragraph

Review 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

3 authors.

Beiming XuDepartment of Pharmacy, The First Hospital of China Medical University, Shenyang, People's Republic of China.ORCID 0009-0007-1829-3496
Minqiao ChenDepartment of Pharmacy, The First Hospital of China Medical University, Shenyang, People's Republic of China.
Yang ChuDepartment of Pharmacy, The First Hospital of China Medical University, Shenyang, People's Republic of China.ORCID 0009-0006-1987-4906

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAugmented renal clearance (ARC) is a critical clinical phenomenon characterized by altered renal excretory function in patients. Although ARC has garnered growing clinical and research attention in recent years, notable gaps remain in its investigation. Inadequate recognition of ARC-related risks may lead to underappreciation of this clinically significant condition in practice. This narrative review synthesizes current evidence on ARC.

methodsCurrent evidence on ARC was narratively reviewed, including pathophysiological hypotheses, diagnostic criteria, predictive models, drug-dosing implications and emerging monitoring techniques. Compared with earlier summaries, we place particular emphasis on recent changes in kidney-function assessment for drug dosing, including the distinction between measured glomerular filtration rate (GFR), measured creatinine clearance (CrCl), Cockcroft-Gault estimated CrCl, and contemporary estimated GFR equations.

resultsWe discuss the limitations of predictive equations in unstable kidney function, the potential role of repeated short-interval CrCl, bedside hemodynamic assessment, standardized experimental models and multi-omics approaches.

conclusionsARC should be regarded as a dynamic pharmacokinetic phenotype requiring timely recognition, drug-specific interpretation, therapeutic drug monitoring and direct or repeated assessment of renal clearance in high-risk patients.

Indexed as

KidneyKidney DiseasesRenal EliminationCreatinineDrug MonitoringGlomerular Filtration RateHumansKidney Function TestsMetabolic Clearance RateCreatinineantibiotics dosingAugmented renal clearanceclinical implicationscritical illnessrenal diseasestherapeutic drug monitoring

Identifiers

PMID42478470
PMCPMC13390178

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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.