Notice bibliographique
Résumé
“Be the change you wish to see in the World.” –Mahatma Gandhi Deprescribing is an essential part of good clinical practice and can be a prescription in itself. Medical training and culture teach to prescribe drugs, write prescriptions, communicate the need for medications, escalate the doses, handle the adverse effects, and so on. The curriculum hardly covers deprescription topics. This is an era of polypharmacy. It is common to see patients on a big list of drugs and many times prescribed drugs themselves cause more problems. Deprescribing is the process of tapering, stopping, discontinuing, or withdrawing drugs, with the goal of managing polypharmacy and improving outcomes.[1] Deprescribing focuses on being proactive to address medication-related problems that have not previously been identified or satisfactorily managed, recognize the poor benefit-to-risk ratio of drugs, and prevent future problems. According to Scott et al. in 2015, deprescribing is the reduction or discontinuation of medications when their current and potential risks outweigh their current or potential benefits, keeping in consideration the patient’s medical status, functioning, values, and preferences.[2] The end goal of deprescribing is not necessarily the cessation of medications but rather their over usage. Fields which deal with chronic ailments need to examine deprescribing in a deeper manner.[3] Inappropriate prescribing and polypharmacy in older persons are associated with increased risk of falls, adverse drug events, hospital admissions, and death.[4] As per one data from Canada, as the population ages, older people are living with multiple chronic conditions. In 2021, one in four seniors in Canada was prescribed 10 or more unique drug classes.[5] The concept of deprescribing started with the geriatric practice but now has influenced all other departments and all ages. A general literature search reveals that guides and algorithms for deprescribing give approaches for deprescription in general terms and focus more on when or why a medication should be stopped rather than how to stop it.[1] There can be varied reasons why deprescribing would be advised such as changing risk–benefit ratio over time, aging, general medical comorbidity, changes in patients’ choice and insight, social factors, relocation, changing financial status, and coping strategy.[3] The steps of deprescribing as per an article by Woodward are (1) reviewing all current medications, (2) identifying medications to be ceased, substituted, or reduced, (3) planning a deprescribing regimen in partnership with the patient, and (4) frequently reviewing and supporting the patient.[6] Swapnil Gupta who has done extensive research on this topic in her article in psychiatric times described in detail the steps of deprescribing with a focus on psychiatric drugs.[3] The steps are: Choose the right time Compile a list of all the patient’s medications Initiate the discussion with the patient Introduce deprescribing to the patient Identify the medication which is most beneficial to taper Develop a plan Monitor and adapt as necessary. There needs to be a detailed discussion on deprescribing by a qualified professional involving the patient with careful monitoring. The important things to consider in the process are timing, strength of treatment alliance, level of risk, past history, coping strategy, and social support.[7] The primary physician should involve other treating professionals as needed. There are tools and scales to assess and assist in deprescribing. The challenges in deprescribing can be patient unwillingness, inconsistent follow-ups, brief visits, frequent change of doctors or clinic, doctor’s fear to change the drugs, the complexity of the cases, and inconsistent guidelines. The way forward should be to improve awareness about deprescribing, include the topic in more detail in medical training and across specialties, hospitals can have deprescription committees, enhance professional discussions and research on the topic, and always look at the benefit-to-risk ratio in writing prescriptions each time. Polypharmacy should be reserved only for essential cases. The doctor’s approach should include deprescription also. There is a need for well-designed large, long-term studies on deprescribing which looks at clinical outcomes from all angles.
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 | 0,000 |
| 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 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| 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 ».