The impact of insulin resistance on long-term outcomes in heart failure: a systematic review
Notice bibliographique
Résumé
Introduction Insulin resistance (IR) is a metabolic condition in which the cells in the body become less responsive to insulin, the blood glucose regulation hormone. While typically associated with type 2 diabetes mellitus (T2DM), IR worsens cardiovascular disease (CVD) progression. 1 Heart failure (HF) is highly prevalent in the UK, contributing to 2% of NHS hospital bed stays and 5% of emergency admissions. 2 Although HF is an established T2DM complication, it can occur in patients with IR independent of diabetes. 3 While the link between IR and HF is well documented, the impact of IR on HF prognosis remains underexplored. Thus, this systematic review assessed the role of IR in HF outcomes. Materials and Methods A systematic literature review was conducted with adherence to PRISMA guidelines. 4 Databases used included PubMed, Ovid Medline and Cochrane Library. Search terms included mesh (insulin resistance, heart failure, Mortality, hospitalisation) and non-mesh (Long-term outcomes) terms. Boolean operations and truncations were used to refine results. Inclusion criteria included studies assessing IR in patients with HF (both preserved and reduced ejection fractions), and studies that reported long-term outcomes (≥6 months) addressing mortality, hospitalisations or functional decline. Exclusion criteria included studies focusing solely on T2DM without IR analysis, studies with an extremely small sample size (<50), or with high methodological bias, or with follow-up periods, where relevant. Tools, such as the Newcastle Ottawa scale and Cochrane’s risk of bias, were used to minimise bias and data were extracted into a table for comparison. Results and Discussion The studies included in this review are summarised in Table 1 with their relevant findings. Overall, they indicate a strong association between IR and adverse long-term HF outcomes. A range of study designs were included. However, many were retrospective rather than prospective, limiting the ability to establish causality in long-term outcomes. More high-quality prospective studies are needed because they better establish disease progression over time. Long-term outcomes were evaluated through measures such as hospitalisation rates, mortality, disease severity and functional decline. Some studies included participants from Japan and Vietnam, improving ethnic diversity but with genetic and metabolic differences being possible confounders. Despite limitations, this review highlights the use of IR as a key factor in long-term outcomes in HF. Conclusion Given its strong association with HF outcomes, IR should be integrated into risk stratification tools and considered for incorporation into National Institute of Health and Care Excellence (NICE) guidelines for HF prognosis and management. Multicentre prospective studies will help further validate the role of IR in HF risk assessment and strengthen its integration into clinical practice.
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 | 0,004 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,010 | 0,002 |
| 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 ».