Predictive Accuracy of Traditional Methods to Assess Left Ventricular Stiffness in a Porcine Model of Heart Failure with Preserved Ejection Fraction
Notice bibliographique
Résumé
Objective: Left ventricular (LV) stiffening is a key pathophysiological component of heart failure with preserved ejection fraction (HFpEF) and contributes to pulmonary congestion and exertional dyspnea. Accurate assessment of LV stiffness is commonly accomplished via construction of end-diastolic pressure-volume relationships (EDPVRs) during transient reductions in venous return (i.e., preload). However, the extent to which this method accurately predicts the rise in LV pressure in response to an increase in preload is unknown. Accordingly, we sought to assess the predictive accuracy of preload reduction-derived EDPVRs in a porcine model of repetitive pressure overload (RPO)-induced HFpEF. Methods: Swine (n=8) were subjected to 2-weeks of RPO via daily administration of phenylephrine (PE; 400 ug/min; 1 hour/day) through an indwelling jugular vein catheter. This model has previously been shown to produce a HFpEF-like cardiac phenotype characterized by a persistent hypertrophy-independent reduction in LV diastolic compliance. Admittance catheter-based PV analysis (Transonic, ADV500) was subsequently performed at rest and during transient preload reduction to construct the LV EDPVR. The predicted change in LV end-diastolic pressure (EDP) for a given change in LV end-diastolic volume (EDV) was compared to the actual change in LVEDP measured in response to an acute PE-mediated increase in preload. Results were compared to those from a series of size-matched control animals (n=8) that underwent the same physiological study protocol. Results: Construction of the EDPVR via transient preload reduction revealed an increase in the LV diastolic stiffness coefficient (ß) from 0.016±.003 in normal control animals to 0.047±.008 after RPO (p<0.01). As a result, the predicted increase in LVEDP for a 20% increase in LVEDV was significantly greater in RPO animals (22.0±4.3 mmHg) than normal controls (8.5±1.3 mmHg; p<0.01). However, administration of PE demonstrated that this was a significant underestimation, as the actual change in LVEDP in response to an increase in preload was nearly 2-fold higher in each group (RPO: 38.1±7.3 mmHg; Control: 15.3±2.2 mmHg; both p<0.05 vs. predicted change in LVEDP). As a result, LV diastolic stiffness (ΔLVEDP/ΔLVEDV) was significantly higher when measured in response to an increase in preload (RPO: 1.78±0.31 mmHg/mL; Control: 0.59±0.09 mmHg/mL) than when extrapolated from EDPVRs derived from the hemodynamic response to preload reduction (RPO: 1.08±0.23 mmHg/mL; Control: 0.33±0.05 mmHg/mL; both p<0.05). Conclusions: Traditional approaches to determine the LV EDPVR underestimate the actual rise in LVEDP for a given rise in LVEDV. These findings highlight challenges in quantifying myocardial stiffness and reinforce the importance of assessing the hemodynamic response to increased preload directly, rather than extrapolating from EDPVRs created via transient preload reduction. The National Heart Lung and Blood Institute, the National Center for Advancing Translational Sciences, and the Department of Veterans Affairs. This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».