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Heat-sensitive moxibustion found to be the most useful therapy for allergic rhinitis

Moxibustion Moxibustion
Moxibustion Moxibustion

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People with allergic rhinitis who are susceptible to unfavorable reactions to allopathy can benefit from heat-sensitive moxibustion.

Compared to the traditional moxibustion treatment, the use of heat-sensitive moxibustion has been proven to be highly effective and improves the quality of life of patients with allergic rhinitis (AR), as described in a review issued in ‘Medicine (Baltimore)’ journal. Researchers examined the effectiveness of different types of moxibustion in the treatment of  AR in a recent systematic review and Bayesian network meta-analysis.

Eight databases were explored from starting till January 2022 to find randomized controlled trials (RCTs) for the use of moxibustion for AR therapy. The risk of bias of the included RCTs was evaluated with the help of the Cochrane Risk of Bias assessment tool. The R software GEMTC and the RJAGS package were used to perform Bayesian estimation of the incorporated RCTs. Overall, 38 RCTs were encompassed, involving 4257 volunteers and nine types of moxibustion.

Heat-sensitive moxibustion (a new type of acupuncture and moxibustion) not only exhibited the best effect regarding effective rate (odds ratio: 32.77) among the other types but also displayed a good effect in enhancing the scores of the quality of life (standard mean differences: 0.6). Numerous types of moxibustion were comparable to the efficacy of allopathic medicine concerning the improvement of immunoglobulin E (IgE) and visual analogue scale (VAS) scores.

Therefore, heat-sensitive moxibustion can be considered a supplemental and alternative therapy for AR-affected people who have experienced unsatisfactory results from conventional therapy and patients who are vulnerable to negative side effects from western medicine.

Source:

Medicine (Baltimore)

Article:

Efficacy comparison of different moxibustion treatments for allergic rhinitis: A systematic review and Bayesian network meta-analysis

Authors:

Ke Chen et al.

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