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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 (Ees) 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 Ees 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 Ees obtained using a conductance catheter during inferior vena cava occlusions. RESULTS: Acute ischemia resulted in a significant reduction in RV Ees 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 Ees and RV pressure-derived parameters. The reduction in RV Ees best correlated with a reduction in RV maximum first derivative of pressure during isovolumetric contraction (dP/dtmax) and single-beat RV Ees. Adjusting RV dP/dtmax for heart rate resulted in an improved surrogate of RV Ees. INTERPRETATION AND CONCLUSIONS: Stepwise decreases in RV Ees during acute ischemic RV dysfunction were accurately tracked by RV dP/dtmax 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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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