Predicting Right Ventricular Failure After Left Ventricular Assist Device Implant: A Novel Approach
Notice bibliographique
Résumé
AIMS: Right ventricular (RV) failure (RVF) after left ventricular assist device (LVAD) implant is an important cause of morbidity and mortality. Modern, data-driven approaches for defining and predicting RVF have been under-utilized. METHODS: Two hundred thirty-two patients were identified with a mean age of 55 years; 40 (17%) were women, 132 were (59%) Caucasian and 74 (32%) were Black. Patients were split between Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) Classes 1, 2 and 3 (25%, 38% and 34%, respectively). Within this group, 'provisional RVF' patients were identified, along with 'no RVF' patients. 'No RVF' patients were defined as patients who never demonstrated more than moderate RV dysfunction on a post-LVAD transthoracic echocardiogram (TTE) (ordinal RV function <3), never required an RV assist device (RVAD), were not discharged on sildenafil and were not on a pulmonary vasodilator or inotropic medication at 3 months after LVAD implant. In total, n = 67 patients were defined as 'no RVF'. The remaining patients represented the 'provisional RVF' population (n = 165). Extensive electronic health records queries yielded >1200 data points per patient. Using <1 and >1 month post-LVAD time windows motivated by established, expert-consensus definitions of 'early' and 'late' post-implant RVF, unbiased clustering analysis was performed to identify hidden patient 'phenogroups' within these two established RVF populations. Clusters were compared on post-implant clinical metrics and 1 year outcomes. Lastly, pre-implant metrics were used to generate models for predicting post-implant RVF phenogroup. RESULTS: Within the 'early RVF' time window, distinct 'well' and 'sick' patient phenogroup clusters were identified. These clusters had similar RV function and pulmonary vasodilator usage during the first month after LVAD but differed significantly in heart failure therapy tolerance, renal (P < 0.001) and hepatic (P = 0.013) function, RVAD usage (P = 0.001) and 1 year mortality (P = 0.047). Distinct 'well' and 'sick' phenogroups were also identified in the 'late RVF' time window. These clusters had similar RV function (P = 0.111) and RVAD proportions (P = 0.757) but differed significantly in heart failure medication tolerance, pulmonary vasodilator usage (P = 0.001) and 1 year mortality (P < 0.001). Prediction of phenogroup clusters from the 'early RVF' population achieved an area under the receiver operating characteristic curve (AUROC) of 0.84, with top predictors including renal function, liver function, heart rate and pre-LVAD RV function. CONCLUSIONS: Distinct, potentially predictable phenogroups of patients who have significantly different long-term outcomes exist within consensus-defined post-LVAD RVF populations.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,001 |
| 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 ».