Quantitative sensory testing, psychological factors, and quality of life as predictors of current and future pain in patients with knee osteoarthritis.

ABSTRACT: Substantial interindividual variability characterizes osteoarthritis (OA) pain. Previous findings identify quantitative sensory testing (QST), psychological factors, and health-related quality of life as contributors to OA pain and predictors of treatment outcomes. This exploratory study aimed to explain baseline OA pain intensity and predict OA pain after administration of a nonsteroidal anti-inflammatory drug in combination with paracetamol for 3 weeks. The Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score was used to estimate OA pain presentation. One hundred one patients were assessed at baseline and follow-up using QST (pressure pain thresholds and temporal summation of pain [TSP]), symptoms of depression and anxiety, pain catastrophizing scales (PCSs), and health-related quality of life. Linear regression with backward selection identified that PCS significantly explained 34.2% of the variability in baseline KOOS pain, with nonsignificant contributions from TSP. Pain catastrophizing score and TSP predicted 29.3% of follow-up KOOS pain, with nonsignificant contributions from symptoms of anxiety. When assessed separately, PCS was the strongest predictor (32.2% of baseline and 24.1% of follow-up pain), but QST, symptoms of anxiety and depression, PCS, and quality of life also explained some variability in baseline and follow-up knee OA pain. Further analyses revealed that only TSP and PCS were not mediated by any other included variables, highlighting their role as unique contributors to OA pain presentation. This study emphasizes the importance of embracing a multimodal approach to OA pain and highlights PCS and TSP as major contributors to the baseline OA pain experience and the OA pain experience after OA treatment.

Quantitative sensory testing as an assessment tool to predict the response to standard pain treatment in knee osteoarthritis: a systematic review and meta-analysis.

Emerging evidence suggest that quantitative sensory testing (QST) may predict the treatment response to pain-relieving therapies. This systematic review and meta-analysis focus on the predictive value of QST for pain management of knee osteoarthritis (OA). MEDLINE and EMBASE were systematically searched for all studies from year 2000 to 2023 on pretreatment QST and treatment of OA including surgical, pharmaceutical, and nonsurgical and nonpharmaceutical therapies. Preclinical studies and reviews were excluded. The systematic review followed the PRISMA guidelines and was pre-registered on the Open Science Framework website (link: https://osf.io/4FETK/, Identifier: DOI 10.17605/OSF.IO/4FETK). Meta-analysis were conducted to demonstrate the strength of the pre-treatment QST predictions on pain outcomes after OA treatments. Sixteen surgical (all on total knee arthroplasty [TKA], N = 1967), 5 pharmaceutical (4 on non-steroidal anti-inflammatory drugs [NSAIDs], N = 271), and 4 exercise-based therapy studies (N = 232) were identified. Pretreatment QST parameters predicted pain-relieving treatment outcomes in 81% of surgical, 100% of pharmaceutical, and 50% of exercise-based therapy studies. Meta-analyses found pretreatment QST profiles to predicted pain outcomes after TKA (random effects: 0.309, 95% confidence interval [CI]: 0.206-0.405, P < 0.001), NSAIDs (random effects: 0.323, 95% CI: 0.194-0.441, P < 0.001), and exercise-based therapies (random effects: 0.417, 95% CI: 0.138-0.635, P = 0.004). The overall risk of bias for the included studies was low to moderate. This systematic review and meta-analysis demonstrate weak-to-moderate associations between pretreatment QST and pain outcomes after standard OA pain treatments. Based on this work, it is hypothesized that a subset of specific pain sensitive patients with OA exist and that these patients do not respond adequately to standard OA pain treatments.

Psychophysical predictors of experimental muscle pain intensity following fatiguing calf exercise.

Musculoskeletal pain affects approximately 20% of the population worldwide and represents one of the leading causes of global disability. As yet, precise mechanisms underlying the development of musculoskeletal pain and transition to chronicity remain unclear, though individual factors such as sleep quality, physical activity, affective state, pain catastrophizing and psychophysical pain sensitivity have all been suggested to be involved. This study aimed to investigate whether factors at baseline could predict musculoskeletal pain intensity to an experimental delayed onset of muscle soreness (DOMS) pain model. Demographics, physical activity, pain catastrophizing, affective state, sleep quality, isometric force production, temporal summation of pain, and psychophysical pain sensitivity using handheld and cuff algometry were assessed at baseline (Day-0) and two days after (Day-2) in 28 healthy participants. DOMS was induced on Day-0 by completing eccentric calf raises on the non-dominant leg to fatigue. On Day-2, participants rated pain on muscle contraction (visual analogue scale, VAS, 0-10cm) and function (Likert scale, 0-6). DOMS resulted in non-dominant calf pain at Day-2 (3.0±2.3cm), with significantly reduced isometric force production (P<0.043) and handheld pressure pain thresholds (P<0.010) at Day-2 compared to Day-0. Linear regression models using backward selection predicted from 39.3% (P<0.003) of VAS to 57.7% (P<0.001) of Likert score variation in DOMS pain intensity and consistently included cuff pressure pain tolerance threshold (P<0.01), temporal summation of pain (P<0.04), and age (P<0.02) as independent predictive factors. The findings indicate that age, psychological and central pain mechanistic factors are consistently associated with pain following acute muscle injury.