Predictive value of cardiac magnetic resonance for the diagnosis and surgical relief of pericardial constriction
Notice bibliographique
Résumé
Background The diagnosis of pericardial constriction (PC) remains challenging and cardiac magnetic resonance (CMR) is increasingly used as a diagnostic tool. The objective of this study was to evaluate CMR findings for the prediction of subsequent surgical pericardiectomy. Methods CMR studies of 36 patients referred to assess for PC were evaluated retrospectively. Patients were divided into two groups depending on whether they subsequently had their pericardium stripped (n=18) or did not (n=18). IVC and aortic areas were determined by manual contouring on a single axial-SSFP image in maximum systole at the level of the esophageal hiatus. The ratio of IVC to aortic (I:A) area was calculated. Cross-sectional areas were indexed to body surface area (BSA). Quantitative data was assessed with a two-sample t-test and qualitative data was assessed with Fisher’s exact test. A logistic regression model was used to determine the predictive probability of surgical pericardiectomy based on CMR features. Odds ratios (ORs) were calculated and receiver operating characteristic (ROC) analysis was performed. Results Mean age of patients was 53.9±15.3 years, 72% (n=26) male, with no significant difference in mean age between the two groups (p=0.429). In patients with constriction, the underlying etiology was idiopathic (39%, n=7), infectious (28%, n=5), post-surgical (17%, n=3), connective-tissue disease (11%, n=2), and post-radiation (6%, n=1). IVC area, indexed IVC area, I:A ratio, pericardial thickness, RV area and indexed RV area were significantly different in patients who underwent pericardiectomy compared to those who did not (Table 1). Pericardiectomy was significantly associated with pericardial enhancement (p=0.011) as well as septal bounce (p<0.0001). The odds ratio (OR) for undergoing pericardiectomy in patients with septal bounce was 289 (95% confidence interval (CI) (16.681, 5007). Using ROC analysis, the area under the curve (AUC) and 95% CI for the prediction of pericardiectomy was 0.968 (0.92, 1.00) for IVC area, 0.932 (0.86, 1.00) for indexed IVC area and 0.963 (0.91, 1.00) for I:A ratio (Figure 1). An IVC area of 7.0 cm 2 had 92% accuracy (sensitivity=94%, specificity=89%), an indexed IVC area of 3.4 cm 2 /m 2 had 86% accuracy (sensitivity=94%, specificity=78%) and a I:A ratio of 1.8 had 92% accuracy (sensitivity=89%, specificity=94%). Conclusions
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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) | 0,000 | 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 tête enseignante, 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 ».