Risk calculator of multimorbid risk of rehospitalization and death from heart failure: including the contribution of the gut microbiome
Notice bibliographique
Résumé
AIMS: The elucidation of the contributory role of multimorbidity to heart failure (HF) including the gut-heart axis has added a new dimension to our understanding of HF pathophysiology that is not reflected in currently available risk scores. The present investigation aimed to develop and validate a novel risk score model of multimorbidity for HF risk stratification. METHODS AND RESULTS: A risk model was developed based on the contribution of markers associated with HF multimorbidities on outcomes of mortality and/or rehospitalization due to HF (death/HF) at one year. Two independent HF cohorts were combined and randomly split 70:30 using a split-sample validation approach for training and validation cohorts that were not significantly different for investigated variables. Backward logistic regression was used to develop the risk model with a further scoring system to create a simple risk calculator. A final 11-variable risk model (age, previous HF hospitalization, NYHA group III/IV, NT-proBNP, diastolic blood pressure, loop diuretic use, beta-blocker non-use, creatinine, COPD, diabetes, and combined gut metabolites) showed a diagnostic performance of 0.71 in the training cohort (C-statistic validation cohort, 0.70, P < 0.001). A risk score/calculator was further developed based on this model with categorization into three (low-, mid-, and high-) and two (low- and high-) risk groups, with both approaches demonstrating increased incidence of death/HF in patients at the highest risk (P < 0.001). CONCLUSION: A novel risk model and score were derived that showed the contribution of comorbidities including the added value of the gut-heart axis on risk stratification of HF patients on rehospitalization and death. LAY SUMMARY: The contributory role of multimorbidity is not well understood in heart failure (HF), including the more recent addition of the gut microbiome (gut-heart axis). However, in current HF risk scores, the contributory role of multimorbidity is seldom considered. In this study, we developed an 11-variable risk model and a simple risk score calculator for clinical use that considers the contribution of HF multimorbidity, including the gut microbiome. The clinical risk score was developed and validated in a clinical cohort from two combined independent European studies from inpatient heart failure subjects. The outcomes were death due to HF and/or rehospitalization at 1 year. The final model showed diagnostic performance comparable to current HF risk scores. Furthermore, the risk score calculator, developed for clinical use, is able to stratify patients into low-, mid-, and high-risk groups, with worsening outcomes seen with increasing risk group. The importance and novelty of this risk model over current HF risk scores are the contribution of comorbidities including the added value of the gut-heart axis on HF risk stratification.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,000 | 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 ».