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Enregistrement W4409448989 · doi:10.1097/io9.0000000000000165

Unlocking cognitive clarity: the neuroprotective potential of low-dose S-ketamine in elderly thoracic surgery patients

2024· article· en· W4409448989 sur OpenAlexaboutno aff
Amogh Verma, Sandeep Kumar Verma, Manu Pant, Mahalaqua Nazli Khatib, Mahendra Pratap Singh, Quazi Syed Zahiruddin, Sarvesh Rustagi

Notice bibliographique

RevueInternational Journal of Surgery Open · 2024
Typearticle
Langueen
DomaineNeuroscience
ThématiqueAnesthesia and Neurotoxicity Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineNeuroprotectionKetamineCognitionCLARITYSurgeryAnesthesiaInternal medicinePsychiatry

Résumé

récupéré en direct d'OpenAlex

Postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) represent significant challenges in the management of elderly patients undergoing thoracic surgery[1]. The acute and sporadic disruptions in attention, awareness, and cognition that characterize these conditions can have a detrimental effect on a patient’s ability to recover, lengthen hospital stays, and raise the expense of healthcare[2]. Traditional approaches to mitigating these complications have had mixed results, However, the powerful N-methyl-d-aspartate (NMDA) receptor antagonist S-ketamine, when taken at low doses, may be a viable new treatment option, according to ongoing studies. Compared to racemic ketamine, S-ketamine, the S(+) enantiomer of ketamine, has a stronger anesthetic potency and a higher affinity for NMDA receptors[3]. This unique pharmacological profile suggests that S-ketamine could provide substantial neuroprotection, potentially reducing the incidence and severity of POD and POCD as seen in mice models[4]. Recent studies have highlighted S-ketamine’s role in modulating neuroinflammation, a critical factor in the pathophysiology of these postoperative neurocognitive disorders[5,6]. Following surgery, S-ketamine preserves neuronal integrity and function by preventing the activation of inflammatory cytokines and lowering neuronal apoptosis[7]. In a recent retrospective cohort study by Wang et al. involving patients aged 65 years and older who underwent elective thoracic surgery, it was found that those who received low-dose S-ketamine intraoperatively had a significantly lower incidence of POD at seven days postsurgery than those who did not receive S-ketamine (12.0% vs. 26.7%, P < 0.001)[8]. Moreover, these patients exhibited reduced POCD at one month (18.7% vs. 36.0%, P < 0.05) and 6 months (10.7% vs. 21.3%, P < 0.05) postoperatively. The S-ketamine group also had significantly higher median Montreal Cognitive Assessment scores at one month (P = 0.021) and 6 months (P = 0.007) than the control group, indicating better cognitive function recovery. The mechanism by which S-ketamine exerts its protective effects involves the modulation of glutamatergic neurotransmission[4,5]. By preferentially blocking N-methyl-D-aspartate (NMDA) receptors on inhibitory gamma-aminobutyric acid (GABAergic) interneurons, S-ketamine reduces the inhibitory control over excitatory neurons, thus enhancing neuroplasticity and synaptogenesis[9]. This process is crucial for cognitive recovery postsurgery. S-ketamine may also be useful in reducing the neuroinflammatory reaction that is frequently observed following major surgeries, as evidenced by its capacity to lower levels of pro-inflammatory cytokines like Interleutin (IL-6), Tumor necrosis factor (TNF-α), and IL-1β[10]. Despite these promising findings, the clinical application of S-ketamine remains challenging. Concerns regarding its dissociative side effects and potential for abuse have limited its widespread adoption. Moreover, evidence from randomized controlled trials (RCTs) is mixed. Ketamine does not generally significantly lower the incidence of POD, according to several studies, and may even increase the likelihood of negative side effects such as hallucinations and nightmares[7,11,12]. However, these studies often did not differentiate between racemic ketamine and S-ketamine, which may have differing efficacy and safety profiles. The variability in outcomes across studies may also be attributed to differences in dosing regimens, patient populations, and surgical procedures. For instance, a study focusing on cardiac surgery patients found no significant benefit of low-dose ketamine in preventing POD, while another study involving noncardiac thoracic surgery patients highlighted its efficacy[13,14]. This underscores the need for further research to refine dosing strategies and identify patient populations that would benefit most from S-ketamine administration. Given the aging global population and increasing number of elderly patients undergoing complex surgeries, the potential of S-ketamine to improve postoperative outcomes is of great clinical significance. Future research should aim to conduct larger multicenter RCTs to confirm these findings and establish standardized protocols for S-ketamine use. Investigations of the long-term effects of S-ketamine on cognitive function and its interactions with other anesthetics and perioperative medicines should be part of these investigations. In conclusion, although the available data indicate that older patients undergoing thoracic surgery may experience a considerable decrease in the frequency of POD and POCD when administered at low doses, caution should be exercised when using this medication. When adding S-ketamine to anesthetic procedures, clinicians should evaluate the advantages against any hazards and consider the unique circumstances of each patient. As research continues to evolve, S-ketamine holds promise as a valuable tool in enhancing postoperative recovery and quality of life for elderly surgical patients.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,547
Score d'incertitude au seuil0,425

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,093
Tête enseignante GPT0,371
Écart entre enseignants0,278 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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