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Enregistrement W2965058723 · doi:10.1002/ejhf.1268

August 2019 at a Glance: Arrhythmogenic Cardiomyopathy, Biomarkers of Inflammation, Insulin Treatment, Initiation of Sacubitril/Valsartan, and Pharmacy-Based Intervention to Increase Medication Adherence

2019· article· en· W2965058723 sur OpenAlexaff
Marco Metra

Notice bibliographique

RevueEuropean Journal of Heart Failure · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueCardiovascular Effects of Exercise
Établissements canadiensSurgical Specialties (Canada)
Organismes subventionnairesnon disponible
Mots-clésMedicineHeart failureEjection fractionInternal medicineCardiologyCardiomyopathySacubitrilDiabetes mellitusSacubitril, ValsartanDiseaseEndocrinology

Résumé

récupéré en direct d'OpenAlex

Our knowledge about cardiomyopathies is rapidly evolving.1 The clinical paradigm of arrhythmogenic right ventricular cardiomyopathy has shifted from that of a right ventricular disease with malignant arrhythmia to a broader disease spectrum including macro- and microscopic structural myocardial abnormalities with possible involvement of both ventricles, arrhythmias and a genetic basis, so-called arrhythmogenic cardiomyopathy. The pathogenesis, clinical characteristics and direction for future research for this relatively new disease entity are outlined in a consensus document.2 Inflammation has a central role in the pathophysiology of heart failure (HF).3 Interleukin (IL)-6 is an important inflammatory mediator and might constitute a potential pharmacologic target in HF. IL-6 was measured in patients from the A systems BIOlogy Study to TAilored Treatment in Chronic HF (BIOSTAT-CHF) cohort. Among the 2329 studied patients, 56% had plasma IL-6 values greater than the 95th percentile of normal values at baseline and they had distinct clinical characteristics. IL-6 independently predicted the primary outcome of all-cause mortality and HF hospitalization as well as cardiovascular and non-cardiovascular mortality.4 Diabetes is a major co-morbidity of HF.5-7 Antidiabetic treatment has a major effect on outcomes.7, 8 Insulin may cause sodium retention and hypoglycaemia and its use has been associated with worse outcomes in patients with HF with reduced ejection fraction (HFrEF).9 Shen et al.10 analysed the association between antidiabetic treatment and outcomes in patients with HF and preserved ejection fraction from three major trials. Of the 8466 patients analysed, 31% had diabetes and 37% of them were on insulin. The primary outcome of cardiovascular death or HF hospitalization occurred at a rate of 6.3 per 100 patient-years in patients without diabetes, 10.2 and 17.1 per 100 patient-years in diabetic patients without and with insulin use, respectively, with a fully adjusted hazard ratio (aHR) of 1.41 (95% confidence interval 1.23–1.63) for insulin-treated diabetic patients vs. other diabetics. Although these data do not show a causal relation, they show the need for intervention studies to assess the safety of insulin vs. alternative glucose-lowering treatments in HF patients. Microvascular function is a major determinant of cardiac function and HF progression.11 Dynamic retinal vessel analysis is a novel, non-invasive, method to assess microvascular function. Barthelmes et al.12 compared retinal microcirculation, assessed as flicker-induced arterial dilatation (FIDa), in healthy controls and patients with coronary artery disease (CAD) without and with HF. FIDa was impaired in patients with CAD and, to a larger extent, in those with HF, suggesting a continuum of microvascular damage from CAD to HF. Sacubitril/valsartan is a major breakthrough in the treatment of chronic HF.13 The Prospective Comparison of Angiotensin Receptor–Neprilysin Inhibitor with Angiotensin-Converting Enzyme Inhibitor to Determine Impact on Global Mortality and Morbidity in HF (PARADIGM-HF) trial established its beneficial effects on outcomes and recurrent events.14, 15 Unmet needs regard implementation of this drug. Hypotension, above all if symptomatic, remains a major limitation, and a strategy of slow dose titration may allow better tolerability and adherence to treatment.16 In-hospital initiation may also allow treatment implementation. Sacubitril/valsartan initiation in an in-hospital setting vs. an outpatient setting, such as in PARADIGM-HF, was compared in the Comparison of Pre- and Post-discharge Initiation of LCZ696 Therapy in HFrEF Patients After an Acute Decompensation Event (TRANSITION) study.17 Patients hospitalized for acute HF initiated sacubitril/valsartan either ≥12 h pre-discharge or 1–14 days post-discharge. The primary endpoint was the proportion of patients attaining 97/103 mg bid target dose after 10 weeks. It was reached in a similar proportion of patients in the two study groups (45.4% vs. 50.7%). The proportion of patients who achieved and maintained the target dose for ≥2 weeks was also similar.17 Adherence to evidence-based medications is an independent prognostic factor and a major goal of treatment.18 PHARMacy-based interdisciplinary programme for patients with Chronic HF (PHARM-CHF) was a randomized controlled trial to assess the efficacy of a pharmacy-based intervention on medication adherence.19 The primary endpoint was medication adherence assessed as proportion of days covered (PDC) within 365 days for three classes of HF medications (beta-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and mineralocorticoid receptor antagonists). Compared with usual care, pharmacy care resulted in an absolute increase in mean adherence to the three HF medications for 365 days and in the proportion of patients classified as adherent. Pharmacy care also improved quality of life after 2 years. It did not affect the safety endpoints of hospitalizations or deaths.20

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,452
Score d'incertitude au seuil0,632

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,010
Tête enseignante GPT0,263
Écart entre enseignants0,253 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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