PRACTICE DIFFERENCES BETWEEN THE UNITED STATES AND CANADA
Notice bibliographique
Résumé
To the Editor: Bronskill et al., in their study of a large Ontario nursing home population between April 1, 1998, and March 31, 1999, estimated a substantial incident use of neuroleptics (17%) dispensed for behavioral disorders to older adults newly admitted to nursing homes.1 They also documented more prevalent use of conventional agents than of atypical agents and the adoption of doses higher than those recommended by the U.S. Medicare State Operations Manual. A completely different picture emerges from another study on the pattern and correlates of neuroleptic use by residents of U.S. nursing homes.2 This study analyzed data from long-stay residents (living in the facility for at least 1 year) in five states (Ohio, South Dakota, Maine, Mississippi, Kansas) between January 1, 1999, and January 31, 2000. Overall, the pattern of neuroleptic use appeared to be indicative of good practice. In fact, the prescription of neuroleptics was restricted to patients with schizophrenia or other organic psychoses and to patients with cognitive impairment associated with behavioral symptoms. Among the latter (n=86,514), the prevalence of neuroleptic use was 18.2%. Atypical neuroleptics appeared to be the most widely prescribed medications (approximately 63%, vs 37% of conventional agents). This correlates with further evidence from the Systematic Assessment of Geriatric Drug Use via Epidemiology database, which shows that, over the last few years, newer atypical neuroleptics have progressively replaced conventional agents (see Figure 1 with data from Ohio between 1998 and 2000) despite unchanged overall prevalence of use. Such changes in nursing homes follow previous evidence suggesting that, in the United States, newer atypical neuroleptics have been increasingly adopted in several medical settings.3 Furthermore, we documented that the dosages for all neuroleptics appear to be in accordance with Food and Drug Administration recommendations and are lower than the recommended daily threshold according to the U.S. Medicare State Operations Manual. The differences observed between Canadian and U.S. nursing homes may be largely attributable to the effect of policy on prescribing practice in the United States. Before the 1990s, the use of neuroleptics in U.S. nursing homes was widespread and poorly regulated.4 The Omnibus Budget Reconciliation Act of 1987 guidelines, which are currently in effect, regulate the use of neuroleptics in nursing homes, restricting their prescription to patients who present definite diagnostic indication and provide specific standards for allowable dosages for individual drugs.5 Although atypical agents have been recommended as appropriate first-line pharmacological treatment for behavioral and psychotic symptoms in nursing home residents,6 doubts about their safety have been cast. Recently, the Food and Drug Administration has warned U.S. physicians about a possible cerebrovascular risk associated with risperidone and olanzapine in elderly patients with dementia.7,8 A similar warning by the manufacturer of risperidone directed to Canadian physicians was issued nearly 2 years ago.9 It would be of interest to continue to register the changes in prescribing patterns of neuroleptics in U.S. and Canadian nursing homes. Temporal trend (1998–2000) in the pattern of neuroleptic use of Ohio nursing home residents (mean number of residents per year 120,105).
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 | 0,002 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,008 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,001 |
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 ».