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Enregistrement W2977852551 · doi:10.1097/corr.0000000000000981

Cochrane in CORR®: Perioperative Intravenous Ketamine for Acute Postoperative Pain in Adults

2019· letter· en· W2977852551 sur OpenAlexaff
Seper Ekhtiari, Mohit Bhandari

Notice bibliographique

RevueClinical Orthopaedics and Related Research · 2019
Typeletter
Langueen
DomaineMedicine
ThématiqueCardiac, Anesthesia and Surgical Outcomes
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésMedicineKetamineOpioidAnalgesicPerioperativeNarcoticAnesthesiaPlaceboMedical prescriptionRandomized controlled trialSurgeryInternal medicineAlternative medicinePharmacology

Résumé

récupéré en direct d'OpenAlex

Importance of the Topic The number of deaths in the United States from opioid overdose, and the number of opioid prescriptions, both have quadrupled since 2000 [3, 4]. After family doctors and internists, orthopaedic surgeons are the third-highest prescribers of opioids among physicians in the United States [9]. The vast majority of surgical patients receive opioids in the peri-operative period, including many for the first time in their lives [4], and it is during this time when patients are at risk for developing opioid dependence. Thus, the concept of multimodal and opioid-reduced or opioid-free peri-operative pain management has gained prominence [8]. In fact, a recent editorial in Clinical Orthopaedics and Related Research® offered modest approaches to opioid-reduced pain management that orthopaedic surgeons should consider including writing smaller prescriptions for shorter periods of time, reassessing whether to use long-acting opioid medications in narcotic-naïve patients, and setting realistic expectations about pain after surgery [7]. Several potential alternatives to opioids have been proposed and investigated, such as ketamine. Ketamine is a medication that provides analgesic, amnestic, and dissociative effects in a dose-dependent manner [11]. There are, however, safety concerns with ketamine including central nervous system symptoms such as hallucinations [10]. In this Cochrane review, the authors investigate the efficacy and safety of ketamine as an adjunct for post-operative pain in adult patients. The authors included 130 blinded, randomized controlled trials (8341 participants) comparing ketamine to either placebo, an opioid medication, or a non-steroidal anti-inflammatory. Overall, the authors found that peri-operative ketamine reduces pain, nausea, vomiting, and the use of opioids after surgery. Upon Closer Inspection The results of particular interest to orthopaedic surgeons were focused mostly on patients undergoing “major orthopaedic surgery,” although arthroscopic surgeries were also included. Overall, pain and opioid consumption were lower in patients receiving ketamine compared to controls in the first 48 hours, but the effect sizes were small and unlikely to be clinically relevant. Specifically, patients had slight reductions in opioid consumption in the first 24 to 48 hours after surgery. Patients undergoing major orthopaedic surgery who received ketamine had a decrease in opioid consumption of roughly 0.5-1mg/hr over this period compared to controls. For opioid-naïve patients in the peri-operative period, each additional week of opioid use, or doses over 100 mg oral morphine equivalents (OMEs)/day are strong predictors of opioid misuse [1]. Thus, this small reduction in consumption is unlikely to have an impact on patient-important endpoints such as misuse or overdose. Similarly, pain scores on the Visual Analogue Scale (VAS) were reduced in the ketamine groups compared to controls in the first 48 hours. Effect sizes ranged from 1 mm to 7 mm on a 100 mm scale. The minimal clinically important difference (MCID) for acute post-operative pain on the VAS has been established at 10 mm to 20 mm [9]. Thus, none of the changes reached even the lower end of the MCID. These studies all had small effect sizes—so small that none could reasonably be considered clinically important differences—and the wide 95% confidence intervals (CIs), which suggest imprecision, make it even more difficult to use these data to justify the widespread use of ketamine [5]. There are a number of safety concerns with ketamine, including hallucinations, dizziness, drowsiness, nightmares, emergence phenomena, and perceptual disturbances [10]. Given the small sample sizes for the vast majority of studies (mean sample size per study = 64 patients), it is unlikely even with pooling data from such a large total pool of participants, that this meta-analysis could substantiate a claim that ketamine is safe for widespread use [6]. This is an important point when interpreting data from any meta-analysis. Even when randomized controlled trials are powered appropriately, which is not always the case, most are powered to detect a difference in the primary outcome (that generally focuses on efficacy), and adverse events are often collected as a secondary outcome. Given that most novel interventions have relatively rare adverse event rates (hence, they are ethical to study via a randomized controlled trial), few actually have an adequate sample size to detect a difference in safety between the two arms. For this reason, safety concerns often do not become apparent in drug trials until Phase 3, Phase 4 (post-approval), or post-market stages [2]. Thus, small trials are unlikely to capture adverse events, and pooling results from many small trials may provide a falsely low adverse event rate based on a large sample size. On the surface, this can provide false reassurance regarding the safety of the intervention. Finally, given the inclusion of a diverse set of surgical procedures (ranging from diagnostic laparoscopy and arthroscopy to major abdominal surgery and total joint arthroplasty), it is difficult to determine whether ketamine is safer or more effective for certain surgical procedures compared to others. Similarly, with a mean age of 48 years in patients who received ketamine, it is unclear how these findings apply to older patients given their greater predisposition towards cognitive impairment and delirium. Take-home Messages This methodologically sound review, which includes a large number of studies and participants, comes at a critical time because of the ongoing opioid crisis. Overall, the data on the use of ketamine in orthopaedic surgery presented in this review does not show a level of efficacy to support its widespread use, and its safety profile remains unclear. Ketamine may play a role in the peri-operative analgesic management of particular patient populations, such as those with or at high risk for opioid dependence. Still, it is difficult to know how to apply these findings, particularly to a specific surgical specialty such as orthopaedic surgery. Most of the pooled results from orthopaedic surgical trials reveal small effect sizes that do not reach MCID, have wide CIs, and are based on a few small studies. This review should be interpreted with caution with regards to the benefits and safety of ketamine in orthopaedic surgery. Large randomized controlled trials that are limited to similar types of surgery like total joint arthroplasty, and studies assessing special populations discussed above, are needed to determine the direction, magnitude, and clinical importance of the effect of ketamine as a peri-operative analgesic. In particular, larger data sets, such as those gleaned from Phase 3, Phase 4, and post-market trials would provide a more-comprehensive view of the risks and safety profile of ketamine in this context.

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)0,003
score de la tête « metaresearch » (Gemma)0,029
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: aucune
Score de désaccord entre enseignants0,054
Score d'incertitude au seuil0,182

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,029
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0040,003
Bibliométrie0,0060,006
Études des sciences et des technologies0,0010,001
Communication savante0,0030,003
Science ouverte0,0020,002
Intégrité de la recherche0,0040,004
Charge utile insuffisante (le modèle a refusé de juger)0,0540,009

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 Opus0,048
Tête enseignante GPT0,424
Écart entre enseignants0,376 · 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

Citations10
Publié2019
Routes d'admission1
Résumé présentoui

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