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DOI 10.1016/j.jopan.2026.03.004

Медицинская библиотека · Journal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses · 2026

Efficacy of Different Nonpharmacological Interventions as Adjunctive Treatments for Postoperative Nausea and Vomiting: A Systematic Review and Bayesian Network Meta-analysis.

Guo Yingjie, Guo Jiantao, Qiu Yi, Ren Minhua, Cao Jingfang

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Аннотация

PURPOSE: This network meta-analysis aimed to compare the efficacy of nonpharmacological adjunctive interventions for postoperative nausea and vomiting (PONV) in patients undergoing non‑gastrointestinal surgery, with formal assessment of transitivity and consistency.

DESIGN

Systematic review and NMA.

METHODS

Eight electronic databases were searched up to October 2024. Pairwise and Bayesian network meta‑analyses were performed. Transitivity, consistency, and sensitivity analyses were conducted. Evidence quality was rated using the GRADE approach.

FINDINGS: Fifty‑four randomized controlled trials involving 8275 participants and nine nonpharmacological interventions were included. For PONV incidence, preoperative carbohydrate loading ranked highest (35%); for rescue antiemetic usage, acupuncture was most effective (59%); and for PONV VAS severity, ginger was most effective (29%). Transitivity and sensitivity analyses supported the robustness of results. GRADE ratings indicated low or very low certainty of evidence for most comparisons, mainly due to risk of bias, indirectness, and imprecision.

CONCLUSION

Carbohydrate loading, acupuncture, and ginger appear beneficial as adjunctive interventions for specific PONV outcomes. However, the low evidence quality limits definitive clinical recommendations. Large, well‑designed randomized controlled trials are needed to strengthen the evidence base.

Для цитирования: Guo Yingjie, Guo Jiantao, Qiu Yi, Ren Minhua, Cao Jingfang. Efficacy of Different Nonpharmacological Interventions as Adjunctive Treatments for Postoperative Nausea and Vomiting: A Systematic Review and Bayesian Network Meta-analysis.. Journal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses. 2026. DOI: 10.1016/j.jopan.2026.03.004.
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