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Journal of pain and symptom management · 2023

Efficacy and Safety of Ketamine to Treat Cancer Pain in Adult Patients: A Systematic Review.

Систематический обзорМетаанализСтатьяНазвание и аннотация: Перевод в очереди
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Jiao Jiao, Fan Jin, Zhang Yonggang, Chen Lingmin

Аннотация

CONTEXT: Ketamine is a well-characterized anesthetic agent, and subanesthetic ketamine possesses analgesic effects in both acute and chronic pain.

OBJECTIVES: A systematic review was performed to ascertain the efficacy and safety of ketamine in treating pain for cancer patients.

METHODS: Eight databases were searched from the inception to March 20th, 2023 to obtain randomized controlled trials (RCTs) on ketamine for treating pain in cancer patients. Two reviewers independently screened studies, extracted the data and assessed the risk of bias of included studies; then, meta-analysis was performed by using Revman 5.3 software and Stata 14.0 software.

RESULTS: Thirty-five studies were included, involving 2279 patients with cancer pain. The results of meta-analysis showed that ketamine could significantly reduce pain intensity. Subgroup analysis revealed that, when compared with control group, ketamine decreased markedly visual analogue scale (VAS) scores in two days after the end of treatment with ketamine, and ketamine administrated by patient controlled epidural analgesia (PCEA) was effective. Meanwhile, ketamine could significantly reduce the number of patient-controlled analgesia (PCA) compressions within 24 hours and morphine dosage. Ketamine could not decrease Ramsay sedation score. Additionally, the adverse events significantly decreased in the ketamine group, including nausea and vomiting, constipation, pruritus, lethargy, uroschesis, hallucination, and respiratory depression. In addition, compared with the control group, ketamine could reduce Hamilton depression scale (HAMD) score and relieve depressive symptoms.

CONCLUSION: Ketamine may be used as an effective therapy to relieve cancer pain. However, more rigorously designed RCTs with larger sample sizes are required to verify the above conclusions.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты