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Updated: Jun 5, 2025

Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery
Published on: April 14, 2016
Pain chronification risk assessment: advanced phenotyping and scoring for prediction and treatments tailored to
Igor Martuliak1, Olga Golubnitschaja2, Lubos Chvala3
1Department of Algesiology, Slovak Medical University Bratislava, F.D. Roosevelt University General Hospital, Banska Bystrica, Slovakia.
Abstract:
Acute pain is a physiologic, protective life-important warning neurological signal indicating multi-level tissue modulations caused by a broad spectrum of health adverse events such as stress overload, mechanical trauma, ischemia-reperfusion, sterile and infection-triggered inflammation, single- and multi-organ damage, acute and chronic wounds, tissue remodeling and degeneration, amongst others. On the other hand, pain chronification results in a pathologic transformation from the protective pain signaling into persistent debilitative medical condition with severe consequences including but not restricted to phenotype-specific behavioral patterns, reduced quality of life, and cognitive and mood disorders. Who is predisposed to an increased vs. decreased pain sensitivity and to the pain chronification? The motivation of personalized medicine that "same size does not fit all" is getting obvious also for an advanced approach in algesiology. Consequently, an in-depth patient stratification is essential for the paradigm change in overall pain management from currently applied reactive medical services to the cost-effective predictive, preventive, and personalized medicine (PPPM/3PM) in primary (reversible damage to health and targeted protection against health-to-disease transition) and secondary (personalized protection against disease progression) care. To this end, specifically innovative concepts of phenotyping elaborated in this study play a crucial role in patient stratification for predicting pain-associated outcomes, evidence-based targeted prevention of the pain chronification, and creation of treatment algorithms tailored to individualized patient profiles.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s13167-024-00383-3.
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