Late enhancement in 39 cardiac transplant patients: prevalence, pattern, and extent
Notice bibliographique
Résumé
Cardiac transplant patients experience significant morbidity related to transplant vasculopathy and acute transplant rejection, both of which can cause scarring of the myocardium. Contrast enhanced cardiovascular magnetic resonance (CMR) has the unique ability to visualize and quantify myocardial scarring. It is well understood that myocardial infarctions resulting from transplant vasculopathy adversely affect prognosis and modify therapy. There is a growing body of evidence from non-transplant disease states, that the presence of non-infarct myocardial scar is also correlated to poor prognosis. Currently there is very little data on the scarring patterns present in the cardiac transplant population and it is our goal to better describe this pathology. Thirty-nine transplant patients underwent contrast enhancement imaging at the time of routine myocardial biopsy at two hospital centers in Alberta, Canada. Standard phase sensitive inversion recovery sequences were used on commercially available scanners (Siemens Avanto and Sonata, Siemens, Erlangen, Germany). Delayed enhancement (DE) was evaluated visually using CMR (Circle Canada Inc, Calgary, Canada) software analysis package by two independent readers. DE had to be cross-referenced in two orthogonal views. Disagreements were settled by consensus. The extent of DE was assessed semi-quantitatively by scoring each of the 17 myocardial segments according to the proportion of DE in each segment (1 = 75%). The scores of the 17 individual myocardial segments were added together to give an aggregate DE burden. Three (8%) out of 39 patients scanned had to be excluded due to poor image quality. There were seven women (18%) and thirty two men (82%). Fifteen (45%) patients had grade 1R cellular rejection rejection, and two (6%) had grade 2R rejection. Mean time since transplant was 37 months (standard deviation = 55 months). Eighteen (50%) of 36 patients had DE. Among patients with DE, four patients (22%) had a subendocardial or transmural pattern consistent with myocardial infarction (Figure 1 ), and 14 (78%) had a midwall or subepicardial pattern (Figure 2 ) consistent with non-ischemic injury. Overall, patients with DE had scores ranging from 1 to 19, with a mean of 5.4 (standard deviation = 4.8). Non-ischemic DE was most commonly seen in the anterolateral and inferior walls (Figure 3 ). There was no significant association between the presence of DE and time since transplant or current biopsy result. Transmural lateral wall infarction (a) and Inferoapical infarction (b) . Example of non-ischemic fibrosis . Subepicardial delayed enhancement of the anteroseptal and anterior walls (a) and inferior wall (b). Frequency of any delayed enhancement by myocardial segment . DE is a common feature in the transplant population. Most DE observed is in a non-ischemic pattern; however a significant proportion had DE patterns consistent with infarction. The relationship between DE and cumulative episodes of rejection, hospitalization, and long term prognosis needs to be explored in more detail.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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 ».