Evidence map›Paper›PMID 35842813›Full record

ArticleJournal of cardiac surgery2022

A systemic congestive index (systemic pulse pressure to central venous pressure ratio) predicts adverse outcomes in patients undergoing valvular heart surgery.

Ziyad O Knio, Frances L Morales, Kajal P Shah, Olivia K Ondigi, Christian E Selinski, Cherisse M Baldeo, David X Zhuo, Kenneth C Bilchick, Nishaki K Mehta, Younghoon Kwon and 4 more

Abstract read
In one paragraph

Article in Journal of cardiac surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

14 authors.

Ziyad O KnioDepartment of Anesthesiology, University of Virginia Health System, Charlottesville, Virginia, USA.ORCID http://orcid.org/0000-0001-5696-873X
Frances L MoralesUniversity of Virginia School of Medicine, Charlottesville, Virginia, USA.
Kajal P ShahDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.
Olivia K OndigiDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.
Christian E SelinskiDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.
Cherisse M BaldeoDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.
David X ZhuoDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.
Kenneth C BilchickDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.
Nishaki K MehtaDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.
Younghoon KwonDivision of Cardiology, Department of Medicine, University of Washington, Seattle, Washington, USA.
Khadijah BreathettDivision of Cardiovascular Medicine, Indiana University, Indianapolis, Indiana, USA.
Robert H ThieleDepartment of Anesthesiology, University of Virginia Health System, Charlottesville, Virginia, USA.
Matthew C HulseDepartment of Anesthesiology, University of Virginia Health System, Charlottesville, Virginia, USA.
Sula MazimbaDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.

Funding

Multiscale Models for Predicting Short and Long-term Outcome of Cardiac Resynchronization TherapyR01HL159945 · NHLBI · UNIVERSITY OF VIRGINIA · PI BILCHICK, KENNETH C, HOLMES, JEFFREY W · 2021 to 2024
$2.6M
NHLBI NIH HHS R01 HL159945
6 · The paper itself

Abstract

BACKGROUND AND

aimsInvasive hemodynamics may provide a more nuanced assessment of cardiac function and risk phenotyping in patients undergoing cardiac surgery. The systemic pulse pressure (SPP) to central venous pressure (CVP) ratio represents an integrated index of right and left ventricular function and thus may demonstrate an association with valvular heart surgery outcomes. This study hypothesized that a low SPP/CVP ratio would be associated with mortality in valvular surgery patients.

methodsThis retrospective cohort study examined adult valvular surgery patients with preoperative right heart catheterization from 2007 through 2016 at a single tertiary medical center (n = 215). Associations between the SPP/CVP ratio and mortality were investigated with univariate and multivariate analyses.

resultsAmong 215 patients (age 69.7 ± 12.4 years; 55.8% male), 61 died (28.4%) over a median follow-up of 5.9 years. A SPP/CVP ratio <7.6 was associated with increased mortality (relative risk 1.70, 95% confidence interval [CI] 1.08-2.67, p = .019) and increased length of stay (11.56 ± 13.73 days vs. 7.93 ± 4.92 days, p = .016). It remained an independent predictor of mortality (adjusted odds ratio 3.99, 95% CI 1.47-11.45, p = .008) after adjusting for CVP, mean pulmonary artery pressure, aortic stenosis, tricuspid regurgitation, smoking status, diabetes mellitus, dialysis, and cross-clamp time.

conclusionsA low SPP/CVP ratio was associated with worse outcomes in patients undergoing valvular heart surgery. This metric has potential utility in preoperative risk stratification to guide patient selection, prognosis, and surgical outcomes.

Indexed as

Cardiac Surgical ProceduresVentricular Function, LeftAdultAgedAged, 80 and overBlood PressureCentral Venous PressureFemaleHumansMaleMiddle AgedRetrospective Studiesheart failurehemodynamic monitoringperioperative mortalitypulmonary hypertensionvalvular surgeryventricular dysfunction

Identifiers

PMID35842813
PMCPMC9543661

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.