Utilization of Artificial Intelligence in Supporting Physical Therapy Clinical Decision in Management of Myofascial Pain Syndrome Patients
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 70
- 试验地点
- 1
- 主要终点
- Pain Intensity changing
研究概览
简要总结
The goal of this study is to investigate the effect of AI integration into clinical physical therapy clinical decision in improving cost effectiveness and clinical outcomes purposes of the study are:
- Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on management of pain in myofascial pain syndrome.
- Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on improving joint range of motion limitations in myofascial pain syndrome.
- Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on improving muscle strength in myofascial pain syndrome.
- Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on management of functional limitation in myofascial pain syndrome.
- Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on cost-effectiveness in physical therapy management of myofascial pain syndrome.
详细描述
Evaluation of AI impact on health care processes still needs more investigation whatever the review of literature reveals, there is a great interest in developing AI tools to support clinical workflows, with increasing high-quality evidence being generated. Investigation of the impact of AI integration into the process of physical therapy clinical decision-making in management of myofascial pain syndrome still not examined or tested. The study planned to compare the efficacy using AI model to support physical therapy decision based on clinical problems solving by evaluating clinical outcomes such as pain intensity, muscular strength, joint rang motion, functional level and therapeutic cost effective compared to traditional clinical decision in patient with myofascial pain syndrome. Formulation A well-established detailed input (prompt) created to guide ChatGPT to what is requested and the proper way to process through the input to develop comprehensive, multimodal approaches (different modalities categories as therapeutic exercises, electrotherapy, complementary and manual approaches when indicated, evidence-based physiotherapy treatment protocol for and planning therapeutic interventions based on studies from PEDro, PubMed, Cochrane, Scopus, and Google Scholar. Patients will be assigned to two groups; one receives AI based clinical decision therapeutic interventions compared to the other group which will receive a traditional intervention according to published methods. Outcomes measures will be assed to compare which is more effective and result in best outcomes and less cost. Trail expected to test if it's valuable to use AI module in data analysis to support choice effective intervention and test the concept based on patient clinical problem-solving approach in physical practice against previously tested traditional methods, additional benefits may provide an assessment of a trail to formulate successful prompt to be used in other conditions. Although there are many studies in supporting clinical decision, still there are many questions concerned with the validity , methods , efficacy , cost effectiveness , scope and ethics of application
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Treatment
- 盲法
- Triple (Participant, Care Provider, Outcomes Assessor)
入排标准
- 年龄范围
- 18 Years 至 65 Years(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •A- Demographic: Adult individuals 18-65 both sex
- •B- Pain Characteristics:
- •Localized pain.
- •Intensity: baseline pain score of 4 or higher on the VAS . C- Duration: chronic pain 3-6 months
- •D- Prescence of Myofascial Trigger Points (MTrPs):
- •E- Daily Functioning limitations: moderate or severe
排除标准
- •• Severe cognitive impairment or illness.
- •Recent history of major surgery or trauma (within 3 months).
- •Other chronic conditions that could significantly interfere with the study.
- •Patients with fibromyalgia which may have the Key Diagnostic Criteria for Fibromyalgia Syndrome:
- •Widespread Pain Index (WPI) (appendix (2): Measures the number of painful areas across the body. A score of 7 or more indicates a higher likelihood of FMS (Wang et al. ,2025).
- •Symptom Severity Scale (SSS) (appendix3): Assesses the severity of symptoms such as fatigue, sleep disturbances, and cognitive difficulties. A score of 5 or more is indicative of FMS
结局指标
主要结局
Pain Intensity changing
时间窗: AI Group:12 sessions (1 every 3 days) Measures: Pre-1st, 4th,7th, 10th & post-12th session. Traditional Group:10 sessions/2weeks (5 daily, 2 days off, 5 daily)Measures: Pre-1st,4th,7th,10th & 2 days post-10th session
Pain intensity is a subjective measurement of pain level or magnitude that can be Measured using a visual analog scale (VAS) , which is a tool used for measuring intensity of pain. It consists of a 10-centimeter line with endpoints defining extremes of pain (e.g., "no pain" to "worst possible pain"). A quantitative indicator of pain intensity will be provided by participants marking their level of pain on the line.
次要结局
- Functional level Assessment(AI Group:12 sessions (1 every 3 days) Measures: Pre-1st, 4th,7th, 10th & post-12th session. Traditional Group:10 sessions/2weeks (5 daily, 2 days off, 5 daily)Measures: Pre-1st,4th,7th,10th & 2 days post-10th session)
- Assessment of Joint Range Motion changes(AI Group:12 sessions (1 every 3 days) Measures: Pre-1st, 4th,7th, 10th & post-12th session. Traditional Group:10 sessions/2weeks (5 daily, 2 days off, 5 daily)Measures: Pre-1st,4th,7th,10th & 2 days post-10th session)
研究者
Hesham Mohamed Mohamed Abousaida
Investigator
Cairo University
