Impact of the use of a drug-drug interaction ...
Type de document :
Article dans une revue scientifique: Article original
PMID :
URL permanente :
Titre :
Impact of the use of a drug-drug interaction checker on pharmacist interventions involving well-known strong interactors.
Auteur(s) :
Moreau, F. [Auteur]
Décaudin, Bertrand [Auteur]
Groupe de Recherche sur les formes Injectables et les Technologies Associées (GRITA) - ULR 7365
Tod, M. [Auteur]
Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 [LBBE]
Odou, Pascal [Auteur]
Groupe de Recherche sur les formes Injectables et les Technologies Associées - ULR 7365 [GRITA]
Simon, Nicolas [Auteur]
Groupe de Recherche sur les formes Injectables et les Technologies Associées - ULR 7365 [GRITA]
Décaudin, Bertrand [Auteur]

Groupe de Recherche sur les formes Injectables et les Technologies Associées (GRITA) - ULR 7365
Tod, M. [Auteur]
Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 [LBBE]
Odou, Pascal [Auteur]

Groupe de Recherche sur les formes Injectables et les Technologies Associées - ULR 7365 [GRITA]
Simon, Nicolas [Auteur]

Groupe de Recherche sur les formes Injectables et les Technologies Associées - ULR 7365 [GRITA]
Titre de la revue :
European Journal of Hospital Pharmacy
Nom court de la revue :
Eur J Hosp Pharm
Éditeur :
BMJ
Date de publication :
2024-08-18
ISSN :
2047-9956
Discipline(s) HAL :
Sciences du Vivant [q-bio]
Résumé en anglais : [en]
Abstract
Objectives Several drug–drug interaction (DDI) checkers such as DDI-Predictor have been developed to detect and grade DDIs. DDI-Predictor gives an estimate of the magnitude of an interaction based on the ratio ...
Lire la suite >Abstract Objectives Several drug–drug interaction (DDI) checkers such as DDI-Predictor have been developed to detect and grade DDIs. DDI-Predictor gives an estimate of the magnitude of an interaction based on the ratio of areas under the curve. The objective of the present study was to analyse the frequencies of DDIs involving well-known strong interactors such as rifampicin and selective serotonin reuptake inhibitors (SSRIs), as reported by a clinical pharmacy team using DDI-Predictor, and the pharmacist intervention acceptance rate. Methods The pharmacist intervention rate and the physician acceptance rate were calculated for DDIs involving rifampicin or the SSRIs fluoxetine, paroxetine, duloxetine and sertraline. The rates were compared with a bilateral χ2 test or Fisher’s exact test. Results Of the 284 DDIs recorded, 38 (13.4%) involved rifampicin and 78 (27.5%) involved SSRIs. The pharmacist intervention rate differed significantly (68.4% for rifampicin vs 48.8% for SSRIs; p=0.045) but the physician acceptance rate did not (84.6% for rifampicin vs 81.6% for SSRIs; p=1). Pharmaceutical interventions for SSRIs were more frequent when the ratio of the area under the drug concentration versus time curve in DDI-Predictor was >2. Pharmacists were more likely to issue a pharmacist intervention for DDIs involving rifampicin because of a high perceived risk of treatment failure and were less likely to issue a pharmacist intervention for DDIs involving an SSRI, except when the suspected interaction was strong. Conclusions DDI checkers can help pharmacists to manage DDIs involving strong interactors. DDIs involving strong inhibitors versus a strong inducer differ with regard to their intervention and acceptance rates, notably due to the estimation of the magnitude of the DDI.Lire moins >
Lire la suite >Abstract Objectives Several drug–drug interaction (DDI) checkers such as DDI-Predictor have been developed to detect and grade DDIs. DDI-Predictor gives an estimate of the magnitude of an interaction based on the ratio of areas under the curve. The objective of the present study was to analyse the frequencies of DDIs involving well-known strong interactors such as rifampicin and selective serotonin reuptake inhibitors (SSRIs), as reported by a clinical pharmacy team using DDI-Predictor, and the pharmacist intervention acceptance rate. Methods The pharmacist intervention rate and the physician acceptance rate were calculated for DDIs involving rifampicin or the SSRIs fluoxetine, paroxetine, duloxetine and sertraline. The rates were compared with a bilateral χ2 test or Fisher’s exact test. Results Of the 284 DDIs recorded, 38 (13.4%) involved rifampicin and 78 (27.5%) involved SSRIs. The pharmacist intervention rate differed significantly (68.4% for rifampicin vs 48.8% for SSRIs; p=0.045) but the physician acceptance rate did not (84.6% for rifampicin vs 81.6% for SSRIs; p=1). Pharmaceutical interventions for SSRIs were more frequent when the ratio of the area under the drug concentration versus time curve in DDI-Predictor was >2. Pharmacists were more likely to issue a pharmacist intervention for DDIs involving rifampicin because of a high perceived risk of treatment failure and were less likely to issue a pharmacist intervention for DDIs involving an SSRI, except when the suspected interaction was strong. Conclusions DDI checkers can help pharmacists to manage DDIs involving strong interactors. DDIs involving strong inhibitors versus a strong inducer differ with regard to their intervention and acceptance rates, notably due to the estimation of the magnitude of the DDI.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
CHU Lille
CHU Lille
Collections :
Date de dépôt :
2024-08-20T21:00:49Z
2024-09-11T07:49:06Z
2024-09-11T07:49:06Z