Differentiation of physiologic versus pathologic basal septal fibrosis: Proposed diagnostic criteria and associations with clinical and CMR-based markers of cardiovascular disease
Notice bibliographique
Résumé
Abnormal late gadolinium enhancement (LGE) is commonly identified in the basal septum of patients with dilated cardiomyopathy, hypertrophic cardiomyopathy and sarcoidosis, and has been associated with major adverse events. However, basal septal LGE may also be seen in otherwise normal individuals (Figure 1 ) and may be "physiologic". No diagnostic criteria to differentiate the latter have been established, and both its prevalence and clinical significance remain uncertain. In this study we propose such criteria and examine its prevalence and association with markers of cardiovascular disease. (A) Apical long axis 3-chamber late gadolinium enhancement (LGE) image in a patient with "physiologic basal septal LGE" according to the criteria of; (1) direct contact with the aortic root, and (2) decreasing signal intensity apically . (B) Basal short axis view with mid myocardial late gadolinium enhancement. A total of 615 consecutive LGE CMR studies were evaluated. Patients with prior valvular surgery (n = 91) or congenital heart disease (n = 94) were excluded, resulting in 430 studies. All were blindly scored for the presence of "physiologic septal LGE" according to pre-defined criteria, as follows; (1) LGE in direct contact with the aortic root, AND (2) decreasing in signal intensity towards the apex (see Figure 1 ). Baseline clinical and CMR-based measures of structural heart disease, inclusive of total LGE volume (> 5SD threshold) were compared between those with and without diagnostic criteria being met. Mean age and LVEF of the entire population were 55.8 ± 14.5 years and 49.1 ± 21.7%, respectively. A total of 73 patients (20.4%) met criteria for "physiologic basal septal LGE". As shown in Table 1 no association of this finding with any other clinical or CMR markers of cardiovascular disease was identified. The only identified difference identified among those with the finding was a slightly higher LV ejection fraction (53.8 ± 19.4 vs. 48.1 ± 22.2, p = 0.045) and age at time of imaging (59.2 ± 12.7 vs. 55.1 ± 14.9, p = 0.030). No association was seen between the presence of "physiologic basal septal LGE" and total LGE (inclusive of all patterns of disease), measuring 10.9 ± 14.3% by signal-threshold based quantification. By comparison, those patients having basal septal LGE but not meeting "physiologic" criteria showed a significantly lower mean LVEF of (30.2 ± 14.6% (p < 0.001) and higher total burden of LGE (13.4 ± 14.9%, p = 0.025). A similar prevalence of "physiologic basal septal LGE" was found in a population of 35 healthy volunteers. Among a large CMR referral population "physiologic basal septal LGE" was identified in 20% of all patients. This finding does not show association with any clinical or CMR-based marker of cardiovascular disease. While outcome-based studies are both preferred and required, the proposed criteria for "physiologic basal septal LGE" provides a practical tool for the differentiation of benign versus pathologic septal LGE in patients referred for CMR.
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 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».