Utilization of Artificial Intelligence in Supporting Physical Therapy Clinical Decision in Management of Myofascial Pain Syndrome Patients
| Registry | NCT07342790, acronym AI/CDM |
|---|---|
| Status | Not yet recruiting |
| Phase | Not applicable |
| Study type | Interventional; randomized, parallel, masking: triple, treatment |
| Enrollment | 70 (Estimated) |
| Sponsor | Cairo University (Other) |
| Conditions | Myofacial Pain Syndrome, Clinical Decision Support |
| Interventions | dry needling, neuromuscular facilitation (PNF) stretching, strengthening exercises (isometric & dynamic), Transcutaneous electrical nerve stimulation, Ultrasound, Hot pack, Stretching exercises (Procedure, other, device) |
| Dates | start 2026-02-01 (estimated), primary completion 2027-02-01 (estimated), completion 2027-04-01 (estimated), first posted 2026-01-15, last updated 2026-01-15 |
| Locations | 1 site in Egypt |
Related Papers Related Patents Related Grants Related Experts
All trials for Myofacial Pain Syndrome All trials for Clinical Decision Support All trials of dry needling All trials of neuromuscular facilitation (PNF) stretching
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:
1. Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on management of pain in myofascial pain syndrome.
2. 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.
3. Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on improving muscle strength in myofascial pain syndrome.
4. 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.
5. 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.
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
| Arm | Type | Interventions | Description |
|---|---|---|---|
| AI.Group | Experimental | Procedure: dry needling; Other: neuromuscular facilitation (PNF) stretching; Other: strengthening exercises (isometric & dynamic); Device: Transcutaneous electrical nerve stimulation | clinical decision making will depend on the integration of ChatGPT 4 into clinical decision-making process as a clinical advisor which recommends application of modalities based on clinical problems as follows dry needling for pain management, proprioceptive neuromuscular facilitation (PNF) stretching for muscle \& joint rom enhancement, strengthening exercises (isometric \& dynamic) for functional improvement and TENS (transcutaneous electrical nerve stimulation) in addition to home exercises as adjuvant therapies \& ergonomic education |
| Traditional Group | Experimental | Device: Transcutaneous electrical nerve stimulation; Device: Ultrasound; Other: Hot pack; Other: Stretching exercises | The traditional physical therapy treatment regime consists of hot pack (HP), transcutaneous electrical nerve stimulation (TENS), and ultrasound (US) for five days a week for two weeks, Application rules were: * Ultrasound (US): Continuous US at a frequency of 1 MHz was applied at a dose of 1.5 watt/cm² for six minutes daily. * Transcutaneous Electrical Nerve Stimulation (TENS): TENS was applied for 30 minutes daily. * Hot Pack (HP): HP was applied for 20 minutes daily. * In addition to these modalities, stretching exercises affected muscles |
Sex: All, ages: 18 Years to 65 Years
Inclusion Criteria:
* 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
Exclusion Criteria:
* • 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:
1. 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).
2. 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| Facility | City | Country | Status |
|---|---|---|---|
| Outpatient clinic, faculty of physical therapy, Cairo university | Giza | Egypt |