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A human experimental bone pain model.
Trine Andresen1, Mogens Pfeiffer-Jensen, Christina Brock
1Mech-Sense, Department of Gastroenterology & Hepatology, Aalborg Hospital, Aarhus University, Aarhus, Denmark. tran@rn.dk
Basic & Clinical Pharmacology & Toxicology
|August 29, 2012
Summary
This study developed a human bone pain model using algometry. A reproducible method using a hand-held algometer and a 2-mm probe is recommended for bone pain research.
Area of Science:
- Pain research
- Experimental modeling
- Human studies
Background:
- Developing reliable human experimental bone pain models is crucial for advancing pain research.
- Existing methods may lack reproducibility or fail to accurately capture bone-associated pain sensations.
Purpose of the Study:
- To develop and validate a human experimental bone pain model.
- To assess the reproducibility and reliability of different algometry techniques for bone pain assessment.
- To compare pain experiences between healthy individuals and patients with bone conditions.
Main Methods:
- Fourteen healthy males participated in two experimental sessions.
- Pressure pain threshold (PPT) was measured using computer-controlled and hand-held algometers with various probe sizes on the medial tibia.
- Local anesthesia (LA) was applied to evaluate its effect on PPT, and the McGill pain questionnaire assessed pain quality.
Main Results:
- The hand-held algometer with a 2-mm probe demonstrated reproducible PPT measurements between sessions and was not significantly affected by local anesthesia.
- Computer-controlled algometry showed reproducibility for 6-mm and 8-mm probes but varied effects of LA.
- Both healthy volunteers and patients with vertebral fractures used similar descriptors for deep bone pain, suggesting qualitative similarities in pain experience.
Conclusions:
- A hand-held algometer with a 2-mm probe provides a reproducible and reliable method for experimentally evoking bone-associated pain in humans.
- This validated model can be utilized for further investigations into bone pain mechanisms and therapeutic interventions.
- The study highlights the importance of selecting appropriate algometry tools and parameters for accurate bone pain assessment.
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