438 Patterns and appropriateness of prescribing for people with dementia in ambulatory care in Saudi Arabia: A cross-sectional study
Notice bibliographique
Résumé
Abstract Introduction People with dementia (PwD) often have several comorbidities for which medications are prescribed. Consequently, polypharmacy and potentially inappropriate prescribing (PIP) are highly prevalent amongst PwD and have been linked with negative health outcomes (1). To date, no studies have been conducted in Saudi Arabia which describe current prescribing practices, polypharmacy or appropriateness of medications prescribed for PwD. Aim To explore prescribing trends, estimate the prevalence of polypharmacy and PIP, and investigate associations between PIP and polypharmacy, age and gender among PwD in ambulatory care in Saudi Arabia. Methods A cross-sectional, retrospective study was conducted using data from electronic health records in a large tertiary hospital in Saudi Arabia. Patients were eligible to be included if they were aged ≥65 years, had a dementia diagnosis, and had visited the ambulatory care clinic during the study period 01/01/2019 – 31/12/2021. Patients who died during the study period were excluded. Polypharmacy was indicated by use of ≥5 chronic medications. Prescribing appropriateness was assessed by applying a subset of the Screening Tool of Older Persons Potentially Inappropriate Prescriptions (STOPP) criteria, comprising 78 indicators (2). Descriptive statistics were used to describe the study population. Overall prevalence of PIP and the prevalence per each STOPP criterion were calculated as a proportion of all eligible persons in the dataset. Logistic regression analysis was used to investigate associations between PIP, polypharmacy, age and gender; adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Data extraction and analysis were conducted using SPSS v27. Results The study population included 287 PwD. The majority were female (n=161, 56.0%) and the mean age was 78.8 [standard deviation (SD) ±8.0) years. The mean number of medications prescribed was 9.0 (±4.2) and polypharmacy was observed in 82.6% (n=237) of patients. The overall PIP prevalence during the study period was 61.0% (n=175). The most common instances of PIP were drugs prescribed beyond the recommended duration (n=90, 31.4%), drugs prescribed without an evidence-based clinical indication (n=78, 27.2%), proton pump inhibitors (PPIs) at full therapeutic dosage for >8 weeks (n=75, 26.0%), acetylcholinesterase inhibitors with concurrent treatment with drugs that reduce heart rate (n=60, 21.0%), and anticholinergic/antimuscarinic drug use (n=28, 9.8%). Whilst polypharmacy was found to be strongly associated with PIP (OR 21.9, 95% CI 8.3 – 57.5), no association was observed between PIP and age or gender after adjustments for polypharmacy. Conclusion To our knowledge, this is the first study to evaluate polypharmacy, prescribing appropriateness, and factors associated with PIP for PwD in Saudi Arabia. Findings have revealed a high prevalence of PIP among PwD that is strongly associated with polypharmacy. However, our focus was on PwD in one tertiary care hospital and thus findings may not be generalisable beyond this setting. Future research should involve PwD and other key stakeholders to develop practical interventions to decrease the burden of polypharmacy and PIP and optimise medication use for this vulnerable patient population. References 1. Delgado J, Jones L, Bradley MC, Allan LM, Ballard C, Clare L, Fortinsky RH, Hughes CM, Melzer D. Potentially inappropriate prescribing in dementia, multi-morbidity and incidence of adverse health outcomes. Age and Ageing. 2021;50(2): 457-464. 2. O’Mahony D, O’Sullivan D, Byrne S, O’Connor MN, Ryan C, Gallagher P. STOPP/START criteria for potentially inappropriate prescribing in older people: Version 2. Age and Ageing. 2015; 44(2): 213–218.
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 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 | 0,001 | 0,001 |
| 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 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».