Dataset Information

A novel technique for invasive aortic valve pressure gradient measurement using a 6 Fr Swan-Ganz catheter: a case series.

ABSTRACT:

Background

Simultaneous left ventricular (LV) and aortic (Ao) pressure gradient assessment has been rendered challenging since the recall of the Langston catheter. Here we describe a simple method for simultaneous LV and Ao pressure gradient assessment using a Swan-Ganz catheter.

Case summary

We describe two cases where assessment of simultaneous left ventricle and Ao valve gradients was done using a Swan-Ganz catheter to assess the degree of Ao stenosis and dynamic LV outflow obstruction.

Discussion

Using Swan-Ganz catheter assessment of simultaneous left ventricle and Ao valve gradients can simplify the procedure with reduced cost and increased patient safety.

SUBMITTER: Agarwal N

PROVIDER: S-EPMC8495136 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Publications

A novel technique for invasive aortic valve pressure gradient measurement using a 6 Fr Swan-Ganz catheter: a case series.

Agarwal Nayan N Rastogi Ujjwal U Mahmoud Ahmed N AN Bhatt Deepak L DL

European heart journal. Case reports 20210924 10

<h4>Background</h4>Simultaneous left ventricular (LV) and aortic (Ao) pressure gradient assessment has been rendered challenging since the recall of the Langston catheter. Here we describe a simple method for simultaneous LV and Ao pressure gradient assessment using a Swan-Ganz catheter.<h4>Case summary</h4>We describe two cases where assessment of simultaneous left ventricle and Ao valve gradients was done using a Swan-Ganz catheter to assess the degree of Ao stenosis and dynamic LV outflow obs ...[more]

PMID: 34632266

Similar Datasets

Project description:BackgroundIn patients with aortic stenosis undergoing transcatheter aortic valve replacement (TAVR), studies have suggested that reduced left ventricular (LV) ejection fraction (LVEF) and low aortic valve gradient (AVG) are associated with worse long-term outcomes. Because these conditions commonly coexist, the extent to which they are independently associated with outcomes after TAVR is unknown.ObjectivesThe purpose of this study was to evaluate the impact of LVEF and AVG on clinical outcomes after TAVR and to determine whether the effect of AVG on outcomes is modified by LVEF.MethodsUsing data from 11,292 patients who underwent TAVR as part of the Transcatheter Valve Therapies Registry, we examined rates of 1-year mortality and recurrent heart failure in patients with varying levels of LV dysfunction (LVEF <30% vs. 30% to 50% vs. >50%) and AVG (<40 mm Hg vs. ≥40 mm Hg). Multivariable models were used to estimate the independent effect of AVG and LVEF on outcomes.ResultsDuring the first year of follow-up after TAVR, patients with LV dysfunction and low AVG had higher rates of death and recurrent heart failure. After adjustment for other clinical factors, only low AVG was associated with higher mortality (hazard ratio: 1.21; 95% confidence interval: 1.11 to 1.32; p < 0.001) and higher rates of heart failure (hazard ratio: 1.52; 95% confidence interval: 1.36 to 1.69; p <0.001), whereas the effect of LVEF was no longer significant. There was no evidence of effect modification between AVG and LVEF with respect to either endpoint.ConclusionsIn this series of real-world patients undergoing TAVR, low AVG, but not LV dysfunction, was associated with higher rates of mortality and recurrent heart failure. Although these findings suggest that AVG should be considered when evaluating the risks and benefits of TAVR for individual patients, neither severe LV dysfunction nor low AVG alone or in combination provide sufficient prognostic discrimination to preclude treatment with TAVR.

Dataset Information

A novel technique for invasive aortic valve pressure gradient measurement using a 6 Fr Swan-Ganz catheter: a case series.

Background

Case summary

Discussion

Publications

A novel technique for invasive aortic valve pressure gradient measurement using a 6 Fr Swan-Ganz catheter: a case series.

Similar Datasets

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