WHICH PATIENTS RETURN TO ANTIHYPERTENSIVE DRUG THERAPY AFTER DISCONTINUATION?
Notice bibliographique
Résumé
Objective: Using a self-administered questionnaire, the objectives of this study were: (1) to identify the predictors that discriminate between the patients who consider returning to antihypertensive therapy and those who indicate that they will not return to drug therapy; (2) to compare the predictors of returning to antihypertensive drug therapy in a North American population (United States, and Canada) with a European (France, Germany, and Italy) population. Design: Cross-sectional study. Data Collection: An existing dataset was obtained from Bristol Myers Squibb (BMS), New Jersey. BMS recruited patients with a diagnosis of hypertension from five different countries (USA, Canada, France, Germany, and Italy) (n=731). Trained interviewers administered the questionnaire in one-on-one interview sessions at a research facility, interviewer's home, or patient's home. Methodology: Required variables were extracted from the dataset using SAS (Statistical Analysis System). The patients who said that they were already taking their antihypertensive medication as directed were deleted from the study. Therefore the final sample of 439 patients was used for the analyses. Independent variables were divided into four groups and logistic regression analyses were carried out separately for each sets of variables. The significant variables from each set of variables were identified and combined to develop a final logistic regression model. Finally, the study sample was divided into North American population and European population. A final logistic regression model was developed separately for these two populations. Results: The number of physician visits for blood pressure problems, number of medication additions to the ones that patients were already taking for their blood pressure, patients' satisfaction towards the assistance they received from their health care provider in managing high blood pressure, and patients' satisfaction with the medications that were available to use to manage their blood pressure were identified as significant predictors in the final model. The European population showed two significant predictors that include number of physician visits for blood pressure problems and patients' satisfaction with the medications that were available to use in manage their blood pressure. However, North American population showed only one significant predictor that is number of medication additions to the ones that patients were already taking to manage their blood pressure. No interaction terms were found to be significant. The model worked best for the set of psychological variables. Conclusion: The treatment of hypertension remains a difficult task. A frequent reason is poor adherence to the drug regimen. The results indicate that an
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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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».