Artificial Intelligence Clinical Decision

Condition(s) studied

Investigational drug(s) / intervention(s)

dry needling: Dry needling is a physical therapy intervention. It uses thin, solid filiform needles where no medication is injected, it targeting myofascial trigger points. The needle is inserted into the muscle tissue, and a local twitch response may occur which is considered a desired effect

neuromuscular facilitation (PNF) stretching: Proprioceptive neuromuscular facilitation stretching is a therapeutic stretching technique. It is commonly used in physical therapy and rehabilitation, involves stretching a target muscle , This is followed by an isometric or isotonic contraction

strengthening exercises (isometric & dynamic): strengthening exercises are therapeutic interventions aiming to increase muscle strength and endurance. dynamic strengthening involves changes of the muscle length during contraction and isometric strengthening has no change of the muscle length

Transcutaneous electrical nerve stimulation: Transcutaneous electrical nerve stimulation is a non-invasive modality which is commonly used for pain management through delivering low-voltage electrical currents that applied through surface electrodes on the skin.

Ultrasound: Ultrasound is a therapeutic physical therapy modality which uses high frequency sound waves which are applied using coupling gel.

Hot pack: Hot pack therapy is a superficial heat modality used in physical therapy, applied for a controlled duration, 20 minutes with A protective layer (towel) is placed between the pack and skin to prevent burns

Stretching exercises: Stretching exercises are physical therapy interventions aimed at increasing muscle length and joint range of motion

Study summary

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.

Eligibility

Primary outcome measure(s)

• Pain Intensity changing — 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.

Trial sites (1)

More Cairo University trials in Egypt

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