Knowing Your Risk Factors for Coronary Heart Disease Improves Adherence to Advice on Lifestyle Changes and Medication
Notice bibliographique
Résumé
In Brief Implementation of guidelines for coronary heart disease prevention is less optimal in clinical practice. The aim of this study was to investigate if specific knowledge (patients' knowledge about their own coronary heart disease risk factors) would correlate to their adherence as measured by self-reported lifestyle changes, reaching defined treatment goals and adhering to treatment with prescribed drugs. The consecutive medical records of 509 men and women younger than 71 years, hospitalized for a cardiac event, were screened. Of these, 392 patients came for an interview and were subjected to a clinical examination. All patients received a questionnaire regarding their specific knowledge of risk factors and their adherence to lifestyle changes, which was completed by 347 patients. In addition, data were collected and analyzed on how their treatment goals were attained in 8 domains and their adherence to drug treatment. There were significant correlations between specific knowledge and self-reported lifestyle changes, the ability to reach treatment goals in all 8 domains, and adherence to prescribed drugs. Patients with coronary heart disease will benefit from increased specific knowledge of risk factors to adhere with lifestyle changes and prescribed medication after a cardiac event. Implementation of guidelines for coronary heart disease prevention is less optimal in clinical practice. The aim of this study was to investigate if specific knowledge (patients' knowledge about their own coronary heart disease risk factors) would correlate to their adherence as measured by self-reported lifestyle changes, reaching defined treatment goals and adhering to treatment with prescribed drugs. The consecutive medical records of 509 men and women younger than 71 years, hospitalized for a cardiac event, were screened. Of these, 392 patients came for an interview and were subjected to a clinical examination. All patients received a questionnaire regarding their specific knowledge of risk factors and their adherence to lifestyle changes, which was completed by 347 patients. In addition, data were collected and analyzed on how their treatment goals were attained in 8 domains and their adherence to drug treatment. There were significant correlations between specific knowledge and self-reported lifestyle changes, the ability to reach treatment goals in all 8 domains, and adherence to prescribed drugs. Patients with coronary heart disease will benefit from increased specific knowledge of risk factors to adhere with lifestyle changes and prescribed medication after a cardiac event. Article available at www.jcnjournal.com
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 | 0,001 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,001 | 0,001 |
| 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 ».