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Stress and Pain. Predictive (Neuro)Pattern Identification for Chronic Back Pain: A Longitudinal Observational Study
Pia-Maria Wippert1,2, Laura Puerto Valencia1, David Drießlein3
1Medical Sociology and Psychobiology, University of Potsdam, Potsdam, Germany.
Frontiers in Medicine
|May 27, 2022
Summary
Stress, particularly social and work-related factors, is linked to chronic low back pain (CLBP), fatigue, and depression. Biomarkers can predict future CLBP, aiding early diagnosis and intervention for at-risk individuals.
Area of Science:
- Psychoneuroimmunology
- Pain Medicine
- Occupational Health
Background:
- Low back pain (LBP) significantly impairs global quality of life, often co-occurring with psychosomatic symptoms.
- Understanding the interplay between stress and chronic low back pain (CLBP) is crucial for effective management.
Purpose of the Study:
- To investigate the association between various stress indicators and CLBP, fatigue, and depression.
- To identify predictive stress-related patterns for diagnosing CLBP a year in advance.
Main Methods:
- A 1-year observational study involving 140 volunteers (aged 18-45) with intermittent pain.
- Assessed stress using psychometric measures (chronic stress, perceived stress, effort-reward imbalance, life events) and physiological markers (allostatic load index, hair cortisol concentration).
- Employed multiple linear regression and least absolute shrinkage and selection operator (LASSO) for analysis, with prediction accuracy evaluated by RMSE and ROC curves.
Main Results:
- Social-related stressors showed significant associations with LBP, CLBP, fatigue, and depression.
- Work-related stress, such as excessive demands and social overload, predicted future pain disability and depressive mood.
- Developed predictive models using seven psychometric and five biomarker patterns, achieving high accuracy (AUC 0.88-0.99) for 1-year CLBP prediction.
Conclusions:
- Stress disrupts allostasis, contributing to chronic pain, fatigue, and depression, with social stressors playing a key role.
- A derived predictive pattern set, particularly biomarkers, can identify individuals at high risk for future pain disorders.
- These findings support translational medicine applications for early diagnosis and intervention in clinical practice.
