Implantable Cardiac Defibrillators for Primary Prevention of Sudden Cardiac Death in High Risk Patients: A Meta-Analysis and Economic Review
Notice bibliographique
Résumé
Background and objectives Sudden cardiac death (SCD) due to cardiac arrhythmia is responsible for many deaths each year. Since only 5% of patients survive a cardiac arrest, primary prevention in high risk patients is necessary. Because of the large amount of patients eligible for an implantable cardiac defibrillator (ICD), the uncertain clinical efficacy of ICD therapy, and the device high cost, this work aims to provide health policy makers of the evidence on clinical efficacy and cost-effectiveness of this therapy. Methods A meta-analysis of randomized controlled trials reporting clinical outcomes from the use of ICDs for primary prevention was done. A literature review of cost-effectiveness surrounding ICD treatment and a budget impact analysis were performed. Using a population-based approach, we defined the budgetary impact of ICD therapy for primary prevention of SCD as the difference between budgets with and without ICD prophylactic use. Microsoft Excel was used to program the budget impact analysis. Results ICDs in addition to conventional therapy significantly reduced the risk of SCD by 67% in ischemic and 74% in non-ischemic, patients. Numbers-needed-to-treat to prevent one SCD were 12 and 28 in ischemic and non-ischemic patients, respectively. Our review showed that ICDs generally cost more than conventional management but were more effective in treating patients without prior clinical arrhythmia. If effectiveness was measured by life-year, the majority of incremental cost-effectiveness ratio (ICER) estimations were below or slightly above the commonly-used willingness to pay threshold of US$50,000 per life year gained. If effectiveness was measured by quality adjusted life year (QALY), the ICER ranged from US$34,000 to $97,863, but all were below US$100,000 per QALY gained for patients with ejection fraction (EF) ≤ 0.30. For patients with 0.31 to 0.40 EF, the ICER went up to US$195,700 per QALY gained. From the perspective of the health care system, if the cost associated with SCD was C$300 per case, the estimated budget impact of using ICD for primary prevention of SCD was C$88.58 millions, C$332.37 millions, C$634.39 millions, C$834.40 millions and C$1.04 billions respectively for 1-, 3-, 5-, 6-, and 7-year time horizons. Conclusions Our review provides evidence that the use of ICDs, combined with optimized pharmacological therapy, can significantly reduce all-cause death and SCD in patients at high-risk of ventricular arrhythmia. Whether the ICD treatment is cost effective or not compared with conventional therapy depends on the threshold of willingness-to-pay for one life year or one QALY gained. Our review indicated that the cost-effectiveness of ICD treatment was mainly driven by the device efficacy, implantation cost and patient's health utility. ICD prophylactic use would result in a substantial budget impact for the Canadian health care system. Compared with the cardiac event risk a patient with usual medical therapy would experience and the resulting cost, the expensive ICD device and its replacement cost within five to ten years absolutely determined the budget impact.
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 | 0,012 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,012 | 0,032 |
| Bibliométrie | 0,007 | 0,006 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».