Classification of insomnia using the traditional chinese medicine system: A systematic review

Maggie Man Ki Poon, Ka Fai Chung*, Wing Fai Yeung, Verdi Hon Kin Yau, Shi Ping ZHANG

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

29 Citations (Scopus)


A systematic review was conducted to examine traditional Chinese medicine (TCM) patterns commonly diagnosed in subjects with insomnia and clinical features associated with the TCM patterns, and an insomnia symptom checklist for TCM diagnostic purpose was developed based on the review. Two independent researchers searched the China Academic Journals Full-Text Database and 10 English databases. A total of 103 studies and 9499 subjects were analyzed. There was a wide variation in terminology relating to symptomatology and TCM pattern. We identified 69 patterns, with the top 3 patterns (i.e., deficiency of both the heart and spleen, hyperactivity of fire due to yin deficiency, and liver-qi stagnation transforming into fire) and the top 10 patterns covering 51.8 and 77.4 of the 9499 subjects, respectively. There were 19 sleep-related, 92 non-sleep-related, 14 tongue, and 7 pulse features included as diagnostic criteria of the top 10 TCM patterns for insomnia. Excessive dreaming, dizziness, red tongue, and fine pulse were the most common sleep-related, non-sleep-related, tongue, and pulse features. Overlapping symptomatology between the TCM patterns was present. A standardized symptom checklist consisted of 92 items, including 13 sleep-related, 61 non-sleep-related, 11 tongue, and 7 pulse items, holds promise as a diagnostic tool and merits further validation.

Original languageEnglish
Article number735078
JournalEvidence-based Complementary and Alternative Medicine
Publication statusPublished - 2012

Scopus Subject Areas

  • Complementary and alternative medicine


Dive into the research topics of 'Classification of insomnia using the traditional chinese medicine system: A systematic review'. Together they form a unique fingerprint.

Cite this