Pressure drop-derived index associated with plaque vulnerability of coronary atherosclerosis
Notice bibliographique
Résumé
Abstract Background The clinical importance of physiological distribution of coronary atherosclerosis is emerging. However, this concept has limited clinical application because of complex formulas and technical difficulties in measurement. Purpose We aimed to evaluate the utility of a simple physiological metric using pressure drop across the lesion, through the analysis of association with hemodynamic and plaque characteristics. Methods The analysis was conducted on a total 246 lesions in 136 vessels from DISCOVER-FLOW study, which was the first-in-human, prospective, international, multi-center study demonstrating the diagnostic accuracy of coronary computational tomographic angiography (CCTA)-derived fractional flow reserve (FFRCT) for invasive FFR. All vessel- and lesion-level hemodynamic as well as plaque parameters were analyzed by independent core laboratories using CCTA and computational fluid dynamic techniques. Functional significance (FS) was defined as CTA-derived FFR (FFRCT) ≤ 0.80, and physiological focal disease (PFD) was defined as change in FFRCT across the lesion (ΔFFRCT) ≥ 0.06 and FFR drop across the lesion ≥ 0.0015/mm. The lesions were categorized into four groups based on the existence of FS and/or PFD and denoted as follows: FS(-) PFD(-) for group A, FS(-) PFD(+) for group B, FS(+) PFD(-) for group C, FS(+) PFD(+) for group D; Statistics of hemodynamic and plaque characteristics among the four groups were compared. Results 48.8% and 54.5% of total lesions were designated as FS and PFD, respectively. Vessel-level characteristics such as total plaque volume (TPV) of vessel and percent atheroma volume (PAV) of vessel were positively associated with FS (all p<0.001 for A vs C and B vs D). In the lesion level, wall shear stress (WSS) was higher when PFD was present, regardless of FS (136.5 vs 260.8, p<0.001 with A vs B; 125.6 vs 299.9, p<0.001 with C vs D, Figure panel a). Plaque burden at minimal lumen area (PB) was significantly greater with PFD in both negative FS and positive FS (52.3 vs 68.5, p<0.001 with A vs B; 49.5 vs 81.1, p<0.001 with C vs D, Figure panel b). Other volumetric plaque factors such as plaque volume (PV) and PAV, were also significantly greater with PFD in both negative FS and positive FS (all p<0.01 for A vs B and C vs D, Figure panel c and d). Adverse plaque characteristics (APC) were found to be frequently present in conjunction with PFD, regardless of FS (30.0% vs 53.6%, p=0.013 with A vs B; 26.2% vs 68.0%, p<0.001 with C vs D, Figure panel e). PFD without FS showed significantly higher in all hemodynamic and plaque characteristics compared to FS without PFD (B vs C - p<0.001 for WSS, PV, PAV; p=0.002 for PB; p=0.012 for APC, Figure). Conclusions Hemodynamic and morphological characteristics related to plaque vulnerability were associated with a pressure drop-derived index, PFD, independent of functional significance of the vessel.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».