Evidence map›Paper›PMID 29049339›Full record

ArticlePloS one2017

Reliability of transcardiopulmonary thermodilution cardiac output measurement in experimental aortic valve insufficiency.

Martin Petzoldt, Constantin J Trepte, Jan Ridder, Stefan Maisch, Philipp Klapsing, Jan F Kersten, Hans Peter Richter, Jens C Kubitz, Daniel A Reuter, Matthias S Goepfert

Open access · goldAbstract readValidation Study
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 37% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
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

10 authors at 1 institution in 1 country.

Martin PetzoldtDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.ORCID http://orcid.org/0000-0001-5295-2925
Constantin J TrepteDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Jan RidderDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Stefan MaischDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Philipp KlapsingDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Jan F KerstenDepartment of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Hans Peter RichterDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Jens C KubitzDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Daniel A ReuterDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Matthias S GoepfertDepartment of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Universität Hamburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMonitoring cardiac output (CO) is important to optimize hemodynamic function in critically ill patients. The prevalence of aortic valve insufficiency (AI) is rising in the aging population. However, reliability of CO monitoring techniques in AI is unknown. The aim of this study was to investigate the impact of AI on accuracy, precision, and trending ability of transcardiopulmonary thermodilution-derived COTCPTD in comparison with pulmonary artery catheter thermodilution COPAC.

methodsSixteen anesthetized domestic pigs were subjected to serial simultaneous measurements of COPAC and COTCPTD. In a novel experimental model, AI was induced by retraction of an expanded Dormia basket in the aortic valve annulus. The Dormia basket was delivered via a Judkins catheter guided by substernal epicardial echocardiography. High (HPC), moderate (MPC) and low cardiac preload conditions (LPC) were induced by fluid unloading (20 ml kg-1 blood withdrawal) and loading (subsequent retransfusion of the shed blood and additional infusion of 20 ml kg-1 hydroxyethyl starch). Within each preload condition CO was measured before and after the onset of AI. For statistical analysis, we used a mixed model analysis of variance, Bland-Altman analysis, the percentage error and concordance analysis.

resultsExperimental AI had a mean regurgitant volume of 33.6 ± 12.0 ml and regurgitant fraction of 42.9 ± 12.6%. The percentage error between COTCPTD and COPAC during competent valve function and after induction of substantial AI was: HPC 17.7% vs. 20.0%, MPC 20.5% vs. 26.1%, LPC 26.5% vs. 28.1% (pooled data: 22.5% vs. 24.1%). The ability to trend CO-changes induced by fluid loading and unloading did not differ between baseline and AI (concordance rate 95.8% during both conditions).

conclusionDespite substantial AI, transcardiopulmonary thermodilution reliably measured CO under various cardiac preload conditions with a good ability to trend CO changes in a porcine model. COTCPTD and COPAC were interchangeable in substantial AI.

Indexed as

Cardiac OutputAnimalsAortic Valve InsufficiencyReproducibility of ResultsSwineThermodilution

Identifiers

PMID29049339
PMCPMC5648193
OpenAlexW2766818919

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.