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Intelligent Approach to Traditional Chinese Medicine for Insomnia (TCM)

T

Taipei Veterans General Hospital

Status

Not yet enrolling

Conditions

Insomnia

Treatments

Drug: Group that is receiving treatment.

Study type

Interventional

Funder types

Other

Identifiers

NCT06997289
2024-10-005C

Details and patient eligibility

About

Insomnia is a very common health issue, affecting over 40% of the population in Chinese-speaking regions. The impact of insomnia on society, economy, mental health, and physical health is significant, with previous research indicating that insomnia is associated with an increased risk of high blood pressure, heart disease, anxiety, and depression, which can ultimately lead to a decline in quality of life. Treatment for insomnia includes non-pharmacological and pharmacological interventions, with clinical practice often utilizing sedative medications for sleep, but with side effects such as dependency, tolerance, daytime drowsiness, and withdrawal symptoms, which make it challenging for patients to find suitable medical treatment. Traditional Chinese Medicine (TCM) approaches insomnia by first conducting a thorough assessment based on individualized patterns (differentiation of body constitution) and evaluating insomnia-related symptoms, followed by an examination of tongue and pulse to determine the correct treatment plan, which may involve acupuncture, herbal medicine or a combination of both (integrative treatment). Due to the complex nature of insomnia, a definitive diagnosis requires neuroimaging and other measures during sleep studies to assess brain wave activity, if possible, to understand the cognitive impact.

Full description

In the treatment of insomnia, Chinese medicine first assesses the individual's constitution and symptoms related to insomnia, before incorporating auricular acupuncture and pulse diagnosis. Subsequently, different syndrome types are identified and treated with acupuncture or traditional Chinese medicine (dialectical treatment). Since insomnia is often subjective, a definitive diagnosis may require overnight monitoring of brain waves and other parameters in a sleep laboratory. Smart imaging methods can help detect special reaction areas of ear points, while pulse diagnosis equipment can provide objective auxiliary diagnosis and classification of insomnia through pulse wave digital conversion analysis. Previous studies have demonstrated the effectiveness of auricular point stimulation in treating insomnia, and this study aims to enhance the therapeutic outcomes for primary insomnia by combining Chinese medicine techniques.

Enrollment

120 estimated patients

Sex

All

Ages

20 to 65 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Major mental illnesses include schizophrenia, bipolar disorder, major depression, dementia, apnea, restless legs syndrome, alcohol and substance abuse, organic psychosis and those with major physiological illnesses that affect sleep.

Exclusion criteria

  • As per the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) published by the American Psychiatric Association, insomnia is characterized.

Trial design

Primary purpose

Treatment

Allocation

N/A

Interventional model

Single Group Assignment

Masking

None (Open label)

120 participants in 1 patient group

Randomized controlled cross-over experimental design
Experimental group
Description:
Struggling to fall asleep or stay asleep, experiencing frequent awakenings, or finding it challenging to return to sleep after waking up. Waking up early in the morning and being unable to go back to sleep. Sleep disturbances leading to significant distress or impairment in various aspects of life such as social, occupational, or academic functioning. Experiencing difficulty sleeping on at least three nights a week for a period of at least three months. No use of hypnotic or stable use of hypnotic and no medication adjustment in the past month
Treatment:
Drug: Group that is receiving treatment.

Trial contacts and locations

0

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Central trial contact

YEN Ying Kung

Data sourced from clinicaltrials.gov

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