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Enregistrement W648214004 · doi:10.1097/jcn.0000000000000271

Risk Stratification

2015· article· en· W648214004 sur OpenAlexaboutno aff
Debra R. Haber, Eileen Stuart‐Shor

Notice bibliographique

RevueThe Journal of Cardiovascular Nursing · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueAtrial Fibrillation Management and Outcomes
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineStroke (engine)Atrial fibrillationPopulationRisk factorRisk stratificationRisk assessmentIncidence (geometry)Psychological interventionPopulation ageingEmergency medicinePhysical therapyInternal medicineEnvironmental health

Résumé

récupéré en direct d'OpenAlex

The population of the United States is aging, with estimates indicating there will be 72.1 million people older than 65 years by the year 2030.1 Age is a risk factor for atrial fibrillation (AF), with individuals older than 60 years accounting for 64% of stroke incidence.2 The oldest old are at highest risk, with individuals older than 80 years having a 4- to 5-fold increased risk of stroke,2 an increased risk of myocardial infarction, increased hospitalization rate,3 and increased mortality.4 The American Heart Association identified paroxysmal, persistent, and permanent AF as a modifiable independent risk factor for stroke because the risk decreases significantly with the use of anticoagulants.5 Optimal use of anticoagulation to prevent stroke in the population with AF and to reduce the severity of the stroke, degree of disability, and mortality in this population is an important prevention strategy.6,7 Current published guidelines provide treatment recommendations based on accurate risk stratification to guide interventions to reduce the risk of stroke and minimize bleeding risk.8–10 Although risk stratification instruments are available to assess the stroke risk and bleeding risk among individuals with AF, a Canadian study that examined the usual practice of 438 general practitioners found that stroke risk tools were used only 50% of the time and bleeding risk tools only 25% of the time.11 A task force was organized under the leadership of the Alliance for Aging Research to determine optimal treatment for AF, resulting in a roundtable composed of experts from the United States and United Kingdom.12 The consensus recommendations were to (a) assess stroke risk using an established scoring instrument and (b) record the value in the electronic health record annually to capture changes in risk that may occur over time.12 Moderate- and high-risk patients with AF should be placed on oral anticoagulant treatment with an evaluation of bleeding risk completed using an available scoring instrument.12 For these moderate- to high-risk patients, the task force suggested the benefit of oral anticoagulants will outweigh the risk of bleeding. The expert panel highlighted the fact that risk assessment tools are underutilized, resulting in high-risk patients having strokes without having received oral anticoagulation. Furthermore, they suggest that the use of any evidence-based instrument to stratify risk will be superior to not using a tool at all.12 To facilitate the translation of evidence to practice, the American College of Cardiology convened the Anticoagulation Consortium Roundtable in September 2013, which resulted in recommendations for increasing (a) clinician knowledge about AF stroke risk stratification and anticoagulation treatment, (b) access to relevant clinical tools to facilitate risk stratification, and (c) access to toolkits for clinicians to use at the point-of-care to facilitate implementation of stroke risk reduction therapies (personal communication, September 21, 2013).13 There is an urgent need to equip providers with evidence-based information and tools to optimize AF management in the elderly.14 The American College of Cardiology Web site provides open access to an AF toolkit with online tools for risk stratification, treatment and management, and patient education at http://www.acc.org/tools-and-practice-support/clinical-toolkits/atrial-fibrillation-afib. Studies have varied regarding the most reliable instruments, leading to the suggestion that providers select an instrument and use it consistently.15–17 Once the diagnosis of AF is confirmed, the next step should be risk stratification to determine the appropriate evidence-based intervention. Risk stratification and the use of evidence-based treatment protocols reassure clinicians who are often reluctant to prescribe antiplatelet and/or anticoagulant therapy because of the individual’s age or risk of falls. Of note, studies have reported that fewer than 50% of clinicians adhere to guideline concordant care in older patients with AF.11 It has been reported that for every 10% increase in guideline adherence by providers, there is a 10% decrease in mortality among patients with AF.18 There is consensus that completion of risk stratification for stroke and serious bleeding adds critical information for the prescribing providing when selecting the most appropriate stroke risk reduction treatment. Selection of an easily accessible instrument that is provider-friendly to use may increase stratification in the clinical setting. The Table displays some risk stratification instruments, their features, and Web link to access the instruments.TABLE: Resources for Risk Stratification and Guideline Based InterventionsBroad dissemination of evidence-based protocols, guidelines, and toolkits that emphasize the importance of risk stratification will likely increase the number of individuals with nonvalvular AF who are risk stratified. In turn, accurate and reliable risk stratification has the potential to enhance realization of stroke prevention goals, improve guideline concordant care, and decrease the burden of stroke and stroke recurrence in the United States. There is a need for continued efforts to ensure immediate access to time efficient stratification tools to guide the selection of anticoagulation options including warfarin, dabigatran, rivaroxaban, or apixaban.10 Nurses across the continuum of care have an important role in the prevention of stroke in the elderly patient with AF. Cardiovascular nurses are positioned to complete risk stratification for bleeding and stroke, document and communicate the risk scores to prescribing providers, and provide patient and family education about nonvalvular AF, stroke risk, bleeding risk, and guideline-based recommendations. Older patients with AF, and their caregivers, need to be engaged as full partners in their care to understand and optimize their stroke and bleeding risk care plan. Cardiovascular nurses can assess and discuss patient and caregiver preferences related to stroke risk reduction interventions, an important strategy to engage patients in the process. As prescribing clinicians, advanced practice nurses are poised to provide guideline concordant interventions based on accurate risk stratification and patient preferences. Access to tools that stratify stroke and bleeding risk of older patients is crucial to guideline concordant prescribing, treatment and patient education.

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: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,878
Score d'incertitude au seuil0,127

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
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 Opus0,087
Tête enseignante GPT0,336
Écart entre enseignants0,249 · 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'étudeAutre devis
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
Publié2015
Routes d'admission1
Résumé présentoui

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Même revueThe Journal of Cardiovascular NursingMême sujetAtrial Fibrillation Management and OutcomesTravaux en français237 207