OBJECTIVE: To identify which generic prognostic factors, such as pain intensity, levels of disability, and psychological factors, are most strongly associated with outcome from musculoskeletal pain, regardless of the location of pain. We tested the hypothesis that pain location does not add predictive value to these generic prognostic models, and that such prognostic factors are equally important across different pain locations. METHODS: Data from a prospective observational cohort of primary care patients with acute (n = 413) and chronic (n = 414) nonspinal musculoskeletal pain were used to develop predictive models. The analysis was carried out in 3 steps: derivation of predictive models including generic factors only, investigation of the added predictive value of pain location, and investigation of effect modification by pain location. RESULTS: Generic factors predicted outcome over different time periods (3 months and 12 months) and for both acute and chronic musculoskeletal pain (area under the receiver operating characteristic curve 0.73-0.75). The most consistent predictors of poor outcome were having had the same complaint in the previous year (odds ratio range 2.03-3.46), a lower level of education, lower scores on the Short Form 36 vitality subscale, using pain medication at baseline, and being bothered by the complaint more often in the past 3 months. Pain location variables only slightly improved the predictive ability of the models over generic factors and were inconsistent across the models. CONCLUSION: Generic factors appear to play an important role in the prognosis of acute and chronic nonspinal musculoskeletal pain, regardless of the location of pain.
OBJECTIVE: To identify which generic prognostic factors, such as pain intensity, levels of disability, and psychological factors, are most strongly associated with outcome from musculoskeletal pain, regardless of the location of pain. We tested the hypothesis that pain location does not add predictive value to these generic prognostic models, and that such prognostic factors are equally important across different pain locations. METHODS: Data from a prospective observational cohort of primary care patients with acute (n = 413) and chronic (n = 414) nonspinal musculoskeletal pain were used to develop predictive models. The analysis was carried out in 3 steps: derivation of predictive models including generic factors only, investigation of the added predictive value of pain location, and investigation of effect modification by pain location. RESULTS: Generic factors predicted outcome over different time periods (3 months and 12 months) and for both acute and chronic musculoskeletal pain (area under the receiver operating characteristic curve 0.73-0.75). The most consistent predictors of poor outcome were having had the same complaint in the previous year (odds ratio range 2.03-3.46), a lower level of education, lower scores on the Short Form 36 vitality subscale, using pain medication at baseline, and being bothered by the complaint more often in the past 3 months. Pain location variables only slightly improved the predictive ability of the models over generic factors and were inconsistent across the models. CONCLUSION: Generic factors appear to play an important role in the prognosis of acute and chronic nonspinal musculoskeletal pain, regardless of the location of pain.
Authors: Lene Aasdahl; Fredrik Granviken; Ingebrigt Meisingset; Astrid Woodhouse; Kari Anne I Evensen; Ottar Vasseljen Journal: BMC Musculoskelet Disord Date: 2021-05-19 Impact factor: 2.362
Authors: Opeyemi O Babatunde; Joanne L Jordan; Danielle A Van der Windt; Jonathan C Hill; Nadine E Foster; Joanne Protheroe Journal: PLoS One Date: 2017-06-22 Impact factor: 3.240
Authors: Paul Campbell; Jonathan C Hill; Joanne Protheroe; Ebenezer K Afolabi; Martyn Lewis; Ruth Beardmore; Elaine M Hay; Christian D Mallen; Bernadette Bartlam; Benjamin Saunders; Danielle A van der Windt; Sue Jowett; Nadine E Foster; Kate M Dunn Journal: J Pain Res Date: 2016-10-14 Impact factor: 3.133
Authors: Majid Artus; Paul Campbell; Christian D Mallen; Kate M Dunn; Danielle A W van der Windt Journal: BMJ Open Date: 2017-01-17 Impact factor: 2.692
Authors: Winfried Häuser; Frederik Wolfe; Peter Henningsen; Gabriele Schmutzer; Elmar Brähler; Andreas Hinz Journal: BMC Public Health Date: 2014-04-13 Impact factor: 3.295
Authors: G Mansell; K P Jordan; G M Peat; K M Dunn; D Lasserson; T Kuijpers; I Swinkels-Meewisse; D A W M van der Windt Journal: BMC Musculoskelet Disord Date: 2017-04-04 Impact factor: 2.362