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Enregistrement W3087319671 · doi:10.1093/fampra/cmaa098

Reply to Potentially inappropriate medication use in older adults: a reply to Amorim <i>et al.</i>

2020· letter· en· W3087319671 sur OpenAlexaff
Barbara Roux, Caroline Sirois, Marc Simard, Marie-Ève Gagnon, Marie‐Laure Laroche

Notice bibliographique

RevueFamily Practice · 2020
Typeletter
Langueen
DomaineMedicine
ThématiquePharmaceutical Practices and Patient Outcomes
Établissements canadiensInstitut National de Santé Publique du QuébecUniversité LavalCentres Intégré Universitaires de Santé et de Services Sociaux
Organismes subventionnairesnon disponible
Mots-clésMedicine

Résumé

récupéré en direct d'OpenAlex

Dear Sir/Madam, We thank Amorim et al. for their comments and considerable interest in our article on the prevalence of potentially inappropriate medication (PIM) use among community-dwelling older adults in the province of Quebec, Canada (1). As mentioned in our study, we assessed PIM use in a large administrative database, the Quebec Integrated Chronic Disease Surveillance System (QICDSS) (2). We used the 2015 Beers criteria to identify PIMs and we specified that only the subset of PIMs that should be avoided generally in older adults was considered (3). However, for some medications of this subset, clinical conditions were required to qualify them as PIMs. Thus, as described in our study, we did not include all PIMs since the QICDSS does not contain all validated clinical data necessary for the inclusion of these drugs. As discussed in the limitations section of our study, we agree that not including some PIMs may have led to potential underestimation of PIM use. However, we submit that it is more appropriate to underestimate PIM use, knowing which medications were not considered, than to introduce potential information bias by identifying clinical conditions without a validation process, which could lead to mischaracterization of PIM use. Indeed, for example, there is no validated case definition in our database to precisely identify the cases of confirmed gastroparesis or hypogonadism, which are necessary to define potentially inappropriate prescribing of metoclopramide and androgens, respectively (3). In addition, the QICDSS does not contain laboratory results; nitrofurantoin is potentially inappropriate according to the Beers criteria if used ‘in individuals with creatinine clearance <30 ml/min or for long term use’ (3). Therefore, as with metoclopramide and androgens, we did not include this criterion to avoid mischaracterizing the use of nitrofurantoin. Regarding the comments of Amorim et al., on the definition of non-steroidal anti-inflammatory drug (NSAID) exposure used in our study, we agree that NSAIDs may be considered inappropriate for long-term use due to the associated serious adverse effects, including increased risk of dyspepsia, gastrointestinal bleeding and ulcers, perforation, acute myocardial infarction and acute renal failure (3,4). Thus, the 2015 Beers criterion states that chronic oral use of NSAIDs should be avoided in older adults, except if other alternatives are not effective and/or gastroprotective agents are taken concomitantly (3). However, in the recommendation section, it does not specify how many days the term chronic refers to. As there is no consensus definition for chronic exposure to NSAIDs, we used the 90-day cut-off in our study to define chronic exposure (i.e. continuous use >3 months), as has been done in previous research (4,5). This duration of treatment has also been used to characterize the chronic use of other PIMs such as benzodiazepines or sulfonylureas (6). We agree that the prevalence of NSAID use may have been potentially underestimated using this exposure definition in our study. However, as mentioned previously, we argue that it is more appropriate to underestimate prevalence than to overestimate it. Finally, Amorim et al. suggested to characterize the deprescribing of some frequent PIMs including proton pump inhibitors, benzodiazepines, antipsychotics and sulfonylureas. We agree that it would be interesting to identify dose reductions in order to better characterize deprescribing; however, it was not the purpose of the study. We aimed to provide a concrete picture of PIM use at the population level in order to identify the most common PIMs used, which could be targeted in further interventions, such as well-designed deprescribing interventions. Moreover, Amorim et al. have mentioned that characterizing deprescribing of PIMs may help to determine the appropriateness of these PIMs. However, a medication could have been appropriate and then deprescribed, when the circumstances justifying its use have passed. Thus, the identification of a deprescribing process alone could not validate that the medication was a PIM. To conclude, we agree that the prevalence of PIM use may have been underestimated in our study. However, we argue that the methodology used in our study is the most adequate to provide a valid population-based picture of PIM use. Funding: CS reports grants from the Fonds de recherche du Québec-Santé and from the Centre de recherche sur les soins et les service de première ligne de l’Université Laval. M-EG receives a scholarship from the Fonds de recherche du Québec-Santé. Ethical approval: not applicable. Conflict of interest: BR, MS and M-LL declare no conflict of interest.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,033
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,051
Score d'incertitude au seuil0,031

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,033
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0040,002
Communication savante0,0030,003
Science ouverte0,0020,002
Intégrité de la recherche0,0510,031
Charge utile insuffisante (le modèle a refusé de juger)0,0070,006

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.

Tête enseignante Opus0,087
Tête enseignante GPT0,371
Écart entre enseignants0,285 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission1
Résumé présentnon

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