Early post-immobilization pain at rest, movement evoked pain, and their ratio as potential predictors of pain and disability at six- and 12-months after distal radius fracture
Tóm tắt
Removal of immobilization is a critical phase of distal radius fracture (DRF) rehabilitation, typically occurring by 2 months post injury. This study examined the extent to which pain at rest (PAR), movement evoked pain (MEP), or the ratio between those (MEPR) assessed at 2-months after DRF predicts the occurrence of chronic pain or disability at 6- and 12-months after the injury. This secondary analysis of a prospective cohort study was done at the Hand and Upper Limb Centre (HULC), London, Ontario, Canada. A total of 229 patients with DRF (159 (69.4%) women) were included. Scores for the pain and function subscales of the Patient-Rated Wrist Evaluation (PRWE) were extracted for 2, 6 and 12 months after DRF. Logistic as well as nonlinear quartile regression examined whether PAR and MEP predicted the severity of chronic pain and disability at 6- and 12-months after DRF. Receiver Operating Characteristics Curve were plotted, where area under the curve (AUC) examined the accuracy of the PAR and MEP scores in classifying those who experienced chronic pain and disability. Scores of ≥3 (AUC of 0.77) for PAR or ≥ 6 (AUC of 0.78) for MEP at 2 months after DRF predicted moderate to severe wrist pain at 6-months, whereas scores of ≥7 (AUC of 0.79) for MEP at 2-months predicted ongoing wrist disability at 6-months after the injury. The MEPR of 2 ≤ or ≥ 8 at 2-months was associated with adverse pain at 6-months and functional outcomes at 6- and 12-months (R-square = 0.7 and 0.04 respectively), but prediction accuracy was very poor (AUC ≤ 0.50). Chronic wrist-related pain at 6-months can be predicted by either elevated PAR ≥ 3/10) or MEP (≥ 6/10) reported at 2-months after the injury, while disability experienced at 6-months after DRF is best predicted by MEP (≥7/10) reported at 2-months. The ratio of these two pain indicators increases assessment complexity and reduces classification accuracy.
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