COVID-SAFER: Deprescribing Guidance for Nirmatrelvir-ritonavir Drug Interactions in Older Adults
Notice bibliographique
Résumé
Abstract Importance Older adults, at high-risk of developing complications from COVID-19, could benefit from nirmatrelvir-ritonavir, an oral antiviral treatment for outpatients at high risk of complications from COVID-19; however, due to its potent CYP3A4 inhibition, nirmatrelvir-ritonavir is associated with many drug-drug interactions (DDI). Objectives Identify how common DDIs are between nirmatrelvir-ritonavir, common medications, and PIMs in older adults with polypharmacy. Craft anticipatory deprescribing guidance for PIMs that interact with nirmatrelvir-ritonavir to help prioritize deprescribing resources, and increase the proportion of older adults potentially benefitting from treatment. Design In this secondary analysis, we retrospectively analyzed all patients in the MedSafer cluster randomized deprescribing trial (N=5698 participants) to investigate the proportion of older adults (age >65) with polypharmacy (≥5 usual home medications) who would be ineligible for treatment with nirmatrelvir-ritonavir due to pre-existing DDIs. Setting The setting of the primary study was in medical inpatient units at 11 Canadian acute care hospitals. Participants Hospitalized persons, age 65 years and older, on 5 or more daily home medications, with an expected survival of 3 months or longer were included in this secondary analysis. Main outcomes and measures We identified the prevalence of (PIMs), as defined by the MedSafer software. We then developed deprescribing guidance, so clinicians could proactively deprescribe in an effort to increase the proportion of older adults eligible for safe treatment with nirmatrelvir-ritonavir in the event of a SARS-CoV-2 infection. Results Of 5698 participants, a total of 3869 (68%) were taking a medication with a known nirmatrelvir-ritonavir DDI, and of these 823 (21%) had at least one PIM. Of 823 PIMs, 627 (76%) were medications with a known high risk DDI and 213 (26%) were considered moderate risk DDIs with nirmatrelvir-ritonavir. Many of the PIMs required “advanced deprescribing” and could not simply be stopped, held, or adjusted at the time of nirmatrelvir-ritonavir receipt. Conclusions and relevance Older adults are at high risk of developing severe complications from COVID-19. Deprescribing PIMs in advance of a COVID-19 infection could increase the proportion of older adults who can safely receive nirmatrelvir-ritonavir, in addition to the usual benefits observed with medication management. Impact Statement We certify that this work is novel. This timely clinical investigation explores the unforeseen consequences of polypharmacy and the use of potentially inappropriate medication in older adults during the COVID-19 pandemic. This manuscript addresses the many drug-drug interactions between nirmatrelvir-ritonavir, an antiviral treatment for COVID-19, and potentially inappropriate medications in older adults with polypharmacy from the MedSafer cluster randomized trial. Our work highlights that the pandemic has created an even greater urgency to examine the medication lists of older adults and proactively deprescribe to improve the safety and tolerability of different COVID-19 treatments. Key Points Question: How does polypharmacy affect the eligibility of older adults to receive Nirmatrelvir-ritonavir? Findings: 68% of older adults in the MedSafer cluster randomized trial had a DDI with nirmatrelvir-ritonavir, and 21% were taking at least 1 potentially inappropriate medication. Meaning: Due to its potent CYP3A4 inhibition, nirmatrelvir-ritonavir is associated with many drug-drug interactions (DDI).
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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 | 0,004 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».