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Record W4318168302 · doi:10.1097/cce.0000000000000847

Longitudinal Validation of Right Ventricular Pressure Monitoring for the Assessment of Right Ventricular Systolic Dysfunction in a Large Animal Ischemic Model

2023· article· en· W4318168302 on OpenAlexaff
Étienne J. Couture, Kevin Moses, Manuel Ignacio Monge García, Cristhian Potes, François Haddad, Lars Grønlykke, Fernando García-García, Eden Paster, Philippe Pîbarot, André Denault

Bibliographic record

VenueCritical Care Explorations · 2023
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsMontreal Heart InstituteInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsCardiologyInternal medicineMedicineBlood pressure

Abstract

fetched live from OpenAlex

CONTEXT: Right ventricular (RV) dysfunction is a major cause of morbidity and mortality in intensive care and cardiac surgery. Early detection of RV dysfunction may be facilitated by continuous monitoring of RV waveform obtained from a pulmonary artery catheter. The objective is to evaluate the extent to which RV pressure monitoring can detect changes in RV systolic performance assess by RV end-systolic elastance (E es ) following the development of an acute RV ischemic in a porcine model. HYPOTHESIS: RV pressure monitoring can detect changes in RV systolic performance assess by RV E es following the development of an acute RV ischemic model. METHODS AND MODELS: Acute ischemic RV dysfunction was induced by progressive embolization of microsphere in the right coronary artery to mimic RV dysfunction clinically experienced during cardiopulmonary bypass separation caused by air microemboli. RV hemodynamic performance was assessed using RV pressure waveform-derived parameters and RV E es obtained using a conductance catheter during inferior vena cava occlusions. RESULTS: Acute ischemia resulted in a significant reduction in RV E es from 0.26 mm Hg/mL (interquartile range, 0.16–0.32 mm Hg/mL) to 0.14 mm Hg/mL (0.11–0.19 mm Hg/mL; p < 0.010), cardiac output from 6.3 L/min (5.7–7 L/min) to 4.5 (3.9–5.2 L/min; p = 0.007), mean systemic arterial pressure from 72 mm Hg (66–74 mm Hg) to 51 mm Hg (46–56 mm Hg; p < 0.001), and mixed venous oxygen saturation from 65% (57–72%) to 41% (35–45%; p < 0.001). Linear mixed-effect model analysis was used to assess the relationship between E es and RV pressure-derived parameters. The reduction in RV E es best correlated with a reduction in RV maximum first derivative of pressure during isovolumetric contraction (dP/dt max ) and single-beat RV E es . Adjusting RV dP/dt max for heart rate resulted in an improved surrogate of RV E es . INTERPRETATION AND CONCLUSIONS: Stepwise decreases in RV E es during acute ischemic RV dysfunction were accurately tracked by RV dP/dt max derived from the RV pressure waveform.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.316
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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