Evidence map›Paper›PMID 42429729›Full record

ArticleJACC. Case reports2026

Bedside IVC Echocardiography to Distinguish Autonomic Dysfunction-Predominant Orthostasis From Right Ventricular Failure in Patients With LVADs.

Ivan Nenadic, Alexandria Danyluk, Karen Flores Rosario, Camille Frazier-Mills, Kevin Cox, Marat Fudim

Abstract readCase Reports
In one paragraph

Article in JACC. Case reports, 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

6 authors.

Ivan NenadicDuke Heart Center, Duke University, Durham, North Carolina, USA.
Alexandria DanylukDuke Heart Center, Duke University, Durham, North Carolina, USA. Electronic address: Alexandria.danyluk@duke.edu.
Karen Flores RosarioDuke Heart Center, Duke University, Durham, North Carolina, USA.
Camille Frazier-MillsDuke Heart Center, Duke University, Durham, North Carolina, USA.
Kevin CoxDuke Heart Center, Duke University, Durham, North Carolina, USA.
Marat FudimDuke Heart Center, Duke University, Durham, North Carolina, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo present a bedside echocardiography approach using inferior vena cava size and collapsibility to distinguish between autonomic dysfunction-predominant orthostatic hypotension and right ventricular failure in symptomatic continuous-flow left ventricular assist device patients. KEY STEPS: Identify patients with a continuous-flow left ventricular assist device and presenting orthostatic intolerance symptoms or low-flow alarms. Perform bedside echocardiography evaluating inferior vena cava size and collapsibility while the patient is supine, and again after standing for 3 to 5 minutes. Categorize findings. Right ventricular failure: Indicated by a plethoric, poorly collapsible inferior vena cava. Autonomic dysfunction-predominant orthostatic hypotension: Indicated by a small, highly collapsible inferior vena cava. POTENTIAL PITFALLS: Failing to optimize volume status and device parameters prior to testing may lead to unclear or inaccurate clinical assessments. TAKE-HOME MESSAGES: Autonomic dysfunction orthostatic hypotension is a frequently underrecognized complication of continuous-flow left ventricular assist device support caused by reduced pulsatility. Bedside assessment of inferior vena cava collapsibility serves as a method to identify the underlying phenotype and guide clinical management.

Indexed as

cardiac assist deviceschronic heart failureechocardiographyright-sided catheterizationultrasound

Identifiers

PMID42429729
PMCPMC13554887

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.