Digital Tool for Assessing Chronic Pain Treatment Effectiveness
Author Information
Author(s): Rigoard Philippe, Ounajim Amine, Moens Maarten, Goudman Lisa, Roulaud Manuel, Naiditch Nicolas, Boukenna Raouf, Page Philippe, Bouche Bénédicte, Lorgeoux Bertille, Baron Sandrine, Nivole Kevin, Many Mathilde, Lampert Lucie, Brumauld de Montgazon Géraldine, Roy-Moreau Brigitte, David Romain, Billot Maxime
Primary Institution: CHU de Poitiers, PRISMATICS Lab
Hypothesis
Can a digital tool effectively assess and predict treatment outcomes for chronic pain management?
Conclusion
Neurostimulation significantly improves treatment outcomes for chronic pain compared to optimized medical management and reoperation.
Supporting Evidence
- Neurostimulation showed significant improvements in pain, function, and quality of life at multiple follow-ups.
- Optimized medical management and spinal reoperation did not show significant benefits.
- The study identified predictors of treatment outcomes including pain surface, BMI, and smoking status.
- The digital tool provided data-driven insights for personalized treatment recommendations.
Takeaway
This study shows that a special digital tool can help doctors find the best treatment for people with long-lasting back pain, and that a method called neurostimulation works better than other treatments.
Methodology
The study used a prospective observational design with a digital tool to assess treatment effectiveness over 12 months.
Potential Biases
Selection bias may have occurred due to the non-randomized nature of treatment allocation.
Limitations
The study was not randomized, and there was an uneven distribution of patients across treatment groups.
Participant Demographics
Patients included had persistent spinal pain syndrome type 2, with a mean age of approximately 50 years.
Statistical Information
P-Value
p<0.0001
Confidence Interval
[2.06, 3.65]
Statistical Significance
p<0.0001
Digital Object Identifier (DOI)
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