Abstract 74: A Population-Based Study to Evaluate the Effectiveness of Multi-Disciplinary Heart Failure Clinics and Identify Important Service Components
Notice bibliographique
Résumé
Background Multi-disciplinary heart failure (HF) clinics improve outcomes for HF patients in randomized clinical trials. It is unclear if this efficacy translates to real world effectiveness. Accordingly, our objectives were to 1) compare real world outcomes of HF patient treated in HF clinics vs that in standard care and 2) identify HF clinic features associated with improved outcomes. Methods The service components at all 34 HF clinics in Ontario, Canada were evaluated and scored using a validated instrument. Based these scores, the clinics were categorized by an expert panel into high/medium or low intensity strata. Our cohort consisted of all patients discharged alive after a HF hospitalization in 2006-07. Patients were classified as either HF clinic or standard care patients and followed until March 31st, 2010, to evaluate mortality, all-cause hospitalization, and HF hospitalization. Propensity score matching was used to compare outcomes between comparable groups of patients in the two groups, using Kaplan-Meier survival curves. We explored the clinic level characteristics associated with improved outcomes by developing marginal Cox-proportional hazard models, restricted to the overall sample of HF clinic patients, so as to account for clustering by HF clinic. Results We identified 14,468 HF patients, of whom 1,288 were seen in HF clinics. In a matched sample of 1,288 pairs, systematic differences between groups were substantially reduced. Over 3 years of follow-up, 52.1% of HF clinic patients died, compared to 54.7% of standard care patients (p-value 0.02). HF clinic patients had a significant increase in hospitalization (87.4% vs 86.6% for all-cause [p-value 0.009]; 58.7% vs 47.3% for HF-related [p-value <0.001]). Clinics in the high intensity strata were associated with lower mortality (hazard ratio [HR] 0.68 (95% confidence interval [CI] 0.48-0.98; p-value 0.04) but higher rates of all-cause hospitalization (HR 1.48; 95% CI 1.01-2.18; p-value 0.04) and HF hospitalization (HR 1.98; 95% CI 1.42-2.77; p-value <0.001), compared to low intensity clinics. HF clinics that targeted both the patient and caregiver were associated with improved survival compared to those that only focused on the patient, as were clinics with an emphasis on peer support. Clinics with frequent contacts between providers and patients had a significant reduction in mortality (HR 0.15; 95% CI 0.09-0.25; p-value <0.0001). A more intensive medication management program was associated with reduced all cause and HF hospitalization (HR 0.35 and HR 0.27 respectively). Conclusions Multi-disciplinary HF clinics are associated with a decrease in mortality but increase in re-hospitalizations compared to standard care. A gradient was observed between clinic intensity and outcomes whereby greater intensity of clinic services was associated with mortality reductions but increased hospitalization.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».