The nexus between cognitive function and self-care ablility in patients with chronic heart failure
Notice bibliographique
Résumé
Background: The prevalence of chronic heart failure (CHF) within in the Western World remains high and is rapidly increasing in developing nations. The clinical trajectory of CHF is often characterised by chronic symptoms with periods of acute decompensation requiring hospitalisations for treatment. Yet almost half of these readmissions are potentially preventable through better adherence with self-care practices. For patients with CHF, self-care involves a level of confidence to adhere to behaviours that maintain physiological stability as well as recognising and making pertinent decisions in response to symptom changes. These self-care skills are not readily learnt and there are many barriers that account for this. Cognitive impairment occurs frequently in adults with CHF and is hypothesised to be a barrier in the acquisition of self-care skills. Aims: The research program is a series of systematically designed studies the specific aims were to: Review the literature surrounding the management of heart failure and teaching patients self-care behaviours; Identify clinical tools that measure heart failure self-care; Identify factors that appear to hinder the practice of self-care; Develop (Phase 1) and test (Phase 2) a conceptual model of factors that predict CHF self-care; compare the Mini Mental State Exam (MMSE) with the Montreal Cognitive Assessment (MoCA) in screening for Mild Cognitive Impairment (MCI); Examine the influence experience with heart failure symptoms has on self-care behaviours. Methods: The program consisted of comprehensive reviews of the literature, identification of clinical tools to measure self-care and cognitive function and two studies using descriptive survey methodology to develop (Phase 1) and test (Phase 2) a conceptual model of variables deemed to predict self-care.;Patients were recruited for the studies during their index hospital admission patients with CHF were assessed for self-care (Self-Care of Heart Failure Index) and screened for MCI and depressive symptoms (scores Scale). In Phase 1, patients were coded as MCI by scores 2, patients were coded as MCI by scores /or scores (MoCA). Adequate self-care was indicated by scores >70 on self-care domains: maintenance, management and confidence of the SCHFI. These factors along with demographic and clinical characteristics (age, gender, social isolation, education level, new diagnosis and co-morbid illnesses) were tested in multiple regression models for self-care. Results: In Phase 1 (n=50), seven variables (cognitive function, depressive symptoms, age, gender, social isolation, self-care confidence and co-morbid illnesses) explained 39% (F (7, 42) 3.80, p=0.003) of the variance in self-care maintenance and 38% (F (7,42) 3.73 p=0.003) of the variance in self-care management. Two variables were significant in predicting self-care maintenance: Age (p2 months. Conclusion: This systematically designed research program enhances the knowledge of heart failure self-care and provides a unique contribution in understanding the relationship between this phenomena and cognitive function. Cognitive impairment is a hidden co-morbidity in patients with CHF and to reflect this, the research program has henceforth been named the 'The InCOGNITO Heart Failure Study'. This co-morbidity impacts negatively upon self-care actions and decisions, potentially increasing the risk of hospital readmissions or even premature death. Such evidence suggests that CHF patients with MCI require ongoing support in developing self-care skills and behaviours directed at reducing CHF symptoms and improving their health and quality of life.;The research program provides further insight into the patient's experience of coping and adjusting to living with CHF. A number of other factors also help to predict self-care behaviours including the presence of symptoms causing functional limitations (NYHA class III or IV), higher co-morbidity, younger age and absence of depressive symptoms. These factors are a reflection of the complex nature of this syndrome and highlight the need for an integrated multidisciplinary health team in the long-term management of CHF. In order to clearly identify and articulate effective support and educational strategies directed at patients with CHF, ongoing research is required to further explore factors that hinder the application of teaching and counselling strategies and develop programs of care to specifically address these barriers.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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 ».