Evidence map›Paper›PMID 42224801›Full record

ArticleJACC. Basic to translational science2026

Cardiorenal Hemodynamic Coupling: Mechanical Circulatory Support Augments Renal Blood Flow via Renal Vasodilation.

Rachel E Zale, Elazer R Edelman

Abstract read
In one paragraph

Article in JACC. Basic to translational science, 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

2 authors.

Rachel E ZaleInstitute of Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. Electronic address: rzale@mit.edu.
Elazer R EdelmanInstitute of Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robust cardiorenal hemodynamic coupling influences outcomes in cardiogenic shock (CS), with concomitant renal failure a persistent challenge despite the use of mechanical circulatory support (MCS). The authors investigated cardiorenal hemodynamic coupling during progressive left ventricular failure and percutaneous ventricular assist device (pVAD) unloading in a porcine model. Renal blood flow (RBF) and aortic, left ventricular, and central venous pressures were continuously measured across progressive CS and varying pVAD support. During CS progression, increased left ventricular end-diastolic pressure and reduced mean arterial pressure correlated with elevated renal vascular resistance (RVR) and decreased RBF. Increasing pVAD support reduced left ventricular end-diastolic pressure and increased mean arterial pressure in correlation with decreased RVR, demonstrating bidirectional cardiorenal coupling. RBF depended primarily on RVR across modeled physiological states, and elevated RVR limited the renal hemodynamic impact of pVAD support. These findings suggest that relative renal vascular tone strongly affects the effect of MCS on renal perfusion, which may have critical implications in CS management.

Indexed as

cardiogenic shockcardiorenal couplingmechanical circulatory supportrenal perfusion

Identifiers

PMID42224801
PMCPMC13241879

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.