Opioid-free Anesthesia: Reply
Notice bibliographique
Résumé
We thank Forget et al.1 and Ingrande and Drummond2 for their interest in our review on perioperative opioid administration.3 Forget et al. contend that we did not distinguish between opioid-free anesthesia and opioid-free analgesia and ignored published studies and a meta-analysis.4 On the contrary, we explicitly distinguish between these two phases of care and even abbreviate them, so as to clarify our position throughout. Unfortunately, the definition of opioid-free anesthesia in literature seems to be loosely applied and consequentially misinterpreted. Whether opioid-free anesthesia means total abstinence or relative lack of intraoperative opioids is unclear. We discuss this as an important limitation of the review and meta-analysis by Frauenknecht et al.,4 in which included studies used opioids during the intraoperative period, thereby resulting in a potentially inappropriate conclusion.5 Furthermore, our statement that total avoidance of perioperative opioids has no influence on the long-term outcomes is based on evidence,6–8 contrary to the statement made by Forget et al.1 The most fundamental question is whether the goal of total opioid avoidance is really necessary and at what cost.Ingrande and Drummond2 draw attention to the fact that use of combination of medications (polypharmacy) is hazardous, which is indeed true. However, with regard to multimodal analgesia, we differ from their broad interpretation. The original definition of multimodal analgesia clarifies that the goal was to achieve sufficient analgesia due to synergistic effects between different group of analgesics, with accompanying reduction of side effects as one would be less dependent on a single analgesic modality.9 In our article, we clarify that the choice of what can be included as multimodal needs to be based on (1) intrinsic analgesic potency, (2) opioid-sparing potential, and (3) potential side effects. Bundling all modalities under nonopioid analgesics is inappropriate. We need to distinguish between adjuncts such as gabapentinoids, dexmedetomidine, lidocaine, ketamine, and magnesium versus known analgesics such as acetaminophen, nonsteroidal anti-inflammatory drugs, and cyclooxygenase-2–specific inhibitors or loco-regional techniques.10 In fact, acetaminophen and nonsteroidal anti-inflammatory drugs or cyclooxygenase-2–specific inhibitors should be administered to all surgical patients unless there are contraindications.10 Moreover, there are procedure-specific and patient-specific considerations, and a one-size-fits-all approach is not recommended. Because avoiding opioids, irrespective of the context, is seen to provide a compelling narrative in the background of the opioid crisis, analgesic practices seem to have resorted to multiple combinations of untested agents, overzealous application of drug combinations, or multiple interventions leading to toxicity and patient harms.11,12 We highlight the need for more balanced and responsible decision-making.Dr. Joshi has received honoraria from Baxter International Inc (Deerfield, Illinois) and Pacira Bioscience Inc (Parsippany, New Jersey). The other authors declare no competing interests.
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 | 0,011 | 0,077 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,005 |
| Communication savante | 0,004 | 0,013 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,031 | 0,051 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,008 |
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 ».