AAKD: A standardized and comprehensive acupuncture anesthesia knowledge platform for enhanced recovery after surgery and mechanism

Abstract Acupuncture anesthesia (AA) is an important practical application of the enhanced recovery after surgery concept, and it has demonstrated considerable potential in perioperative management by reducing anesthetic dosage, enhancing organ protection, and lowering complications. However, the field still faces challenges such as a lack of high‐quality evidence‐based medical data, the absence of standardized guidelines, and unclear acupuncture mechanisms, which hinder further advancements in clinical efficacy prediction and personalized application. To systematically integrate heterogeneous multi‐source knowledge in AA, this study proposed the first publicly available Acupuncture Anesthesia Knowledge Database (AAKD). AAKD adheres to a comprehensive development process, including public data collection, extraction, curation and evaluation, standardization, a multi‐dimensional quality control system construction, data analysis, and integration. AAKD includes 17,921 clinical data, 29,462 mechanism research data, 143 omics datasets, and 2034 articles. It covers 12 species, 1068 genes, 111 surgeries, 227 diseases/symptoms, and 260 acupoints. Taking IL1B gene as an example, it demonstrates a potential way for AAKD in integrating multi‐level data, offering knowledge support for users exploring basic research or clinical decision‐making. It also reveals cross‐module association in facilitating the discovery of new scientific questions. AAKD is a visual, systematic, and standardized platform, which has the potential to support the evidence‐based practice and mechanism research in AA, and lay the foundation for future artificial intelligence–driven analgesic strategies. AAKD is available at http://www.biomedinfo.cn/AAKD/index_en.php or http://www.bmtongji.cn/AAKD/index_en.php .

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Publication Details

Journal
Open Research (University of Surrey)
Published
2026-01-26
DOI
https://doi.org/10.1002/viw.20250196
Primary Topic
Acupuncture Treatment Research Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

AAKD: A standardized and comprehensive acupuncture anesthesia knowledge platform for enhanced recovery after surgery and mechanism

Chenchen Feng, Ying Wang, Ke Wang, Jing Li et al.
Open Research (University of Surrey)
Acupuncture Treatment Research Studies
article

AAKD: A standardized and comprehensive acupuncture anesthesia knowledge platform for enhanced recovery after surgery and mechanism

Chenchen Feng, Ying Wang, Ke Wang, Jing Li, Weiting Wang, Xintong Yu, Chunfang Gao, Ziyi Wei, Hanzhi Lu, Jia Zhou, Honglian Huang, Xueli Zhang
article en

Abstract

Abstract Acupuncture anesthesia (AA) is an important practical application of the enhanced recovery after surgery concept, and it has demonstrated considerable potential in perioperative management by reducing anesthetic dosage, enhancing organ protection, and lowering complications. However, the field still faces challenges such as a lack of high‐quality evidence‐based medical data, the absence of standardized guidelines, and unclear acupuncture mechanisms, which hinder further advancements in clinical efficacy prediction and personalized application. To systematically integrate heterogeneous multi‐source knowledge in AA, this study proposed the first publicly available Acupuncture Anesthesia Knowledge Database (AAKD). AAKD adheres to a comprehensive development process, including public data collection, extraction, curation and evaluation, standardization, a multi‐dimensional quality control system construction, data analysis, and integration. AAKD includes 17,921 clinical data, 29,462 mechanism research data, 143 omics datasets, and 2034 articles. It covers 12 species, 1068 genes, 111 surgeries, 227 diseases/symptoms, and 260 acupoints. Taking IL1B gene as an example, it demonstrates a potential way for AAKD in integrating multi‐level data, offering knowledge support for users exploring basic research or clinical decision‐making. It also reveals cross‐module association in facilitating the discovery of new scientific questions. AAKD is a visual, systematic, and standardized platform, which has the potential to support the evidence‐based practice and mechanism research in AA, and lay the foundation for future artificial intelligence–driven analgesic strategies. AAKD is available at http://www.biomedinfo.cn/AAKD/index_en.php or http://www.bmtongji.cn/AAKD/index_en.php .

Open Research (University of Surrey)
Tongji University (CN), Shanghai University of Traditional Chinese Medicine (CN), Yueyang Hospital (CN), Shenzhen Institutes of Advanced Technology (CN)
Shanghai Municipal Health Commission, National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, Shanghai University of Traditional Chinese Medicine
Peace, Justice and strong institutions
Openalex Percentile: Top 76%
Acupuncture Treatment Research Studies
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