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ORIGINAL PAPER
Clinical prediction rule validity to identify individuals with recurrent low back pain
1
Motor Control and Neural Plasticity Laboratory, Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, Thailand
2
Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, Thailand
3
Physical Therapy Clinic, Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, Thailand
Submission date: 2020-03-23
Acceptance date: 2020-07-20
Publication date: 2022-03-29
Physiother Quart. 2022;30(1):27-32
KEYWORDS
clinical prediction rulelumbar instabilitylow back painpredictive validityaberrant movementpassive straight leg raising
TOPICS
ABSTRACT
Introduction:
One set of clinical prediction rules (CPR) can be used clinically to identify patients with low back pain who are likely to benefit from motor control exercise. Individuals with a history of recurrent low back pain during remission (rLBP) still have persisting impaired trunk neuromuscular control. Accordingly, CPR should detect these individuals with rLBP. This study aimed to determine the predictive validity of CPR to identify individuals with rLBP.
Methods:
Overall, 30 subjects aged less than 40 years (22 subjects with rLBP and 8 subjects without a history of low back pain) were recruited. We used the following criteria as CPR: (1) presence of aberrant movement during active forward bend and (2) passive straight leg raising result greater than 91°. Kappa statistics and the chi-square test were used to determine predictive validity. Diagnostic accuracy was also calculated.
Results:
Kappa demonstrated substantial agreement (kappa = 0.73), while the chi-square test showed significant association (χ2 = 16.28; p < 0.001) between positive CPR and rLBP. Diagnostic accuracy demonstrated positive likelihood ratio of 3.82, while accuracy equalled 90%.
Conclusions:
Our findings indicated the predictive validity of CPR to identify individuals with rLBP. The result from this study would help identify those predisposed to recurrent episodes of low back pain who would likely have a positive response to motor control exercise.
One set of clinical prediction rules (CPR) can be used clinically to identify patients with low back pain who are likely to benefit from motor control exercise. Individuals with a history of recurrent low back pain during remission (rLBP) still have persisting impaired trunk neuromuscular control. Accordingly, CPR should detect these individuals with rLBP. This study aimed to determine the predictive validity of CPR to identify individuals with rLBP.
Methods:
Overall, 30 subjects aged less than 40 years (22 subjects with rLBP and 8 subjects without a history of low back pain) were recruited. We used the following criteria as CPR: (1) presence of aberrant movement during active forward bend and (2) passive straight leg raising result greater than 91°. Kappa statistics and the chi-square test were used to determine predictive validity. Diagnostic accuracy was also calculated.
Results:
Kappa demonstrated substantial agreement (kappa = 0.73), while the chi-square test showed significant association (χ2 = 16.28; p < 0.001) between positive CPR and rLBP. Diagnostic accuracy demonstrated positive likelihood ratio of 3.82, while accuracy equalled 90%.
Conclusions:
Our findings indicated the predictive validity of CPR to identify individuals with rLBP. The result from this study would help identify those predisposed to recurrent episodes of low back pain who would likely have a positive response to motor control exercise.
REFERENCES (28)
1.
Hoy D, Brooks P, Blyth F, Buchbinder R. The epidemiology of low back pain. Best Pract Res Clin Rheumatol. 2010;24(6):769–781; doi: 10.1016/j.berh.2010.10.002.
2.
O’Sullivan P. Diagnosis and classification of chronic low back pain disorders: maladaptive movement and motor control impairments as underlying mechanism. Man Ther. 2005;10(4):242–255; doi: 10.1016/j.math.2005.07.001.
3.
Sahrmann S, Azevedo DC, Van Dillen L. Diagnosis and treatment of movement system impairment syndromes. Braz J Phys Ther. 2017;21(6):391–399; doi: 10.1016/j.bjpt.2017.08.001.
4.
Stanton TR, Fritz JM, Hancock MJ, Latimer J, Maher CG, Wand BM, et al. Evaluation of a treatment-based classification algorithm for low back pain: a cross-sectional study. Phys Ther. 2011;91(4):496–509; doi: 10.2522/ptj.20100272.
5.
Hicks GE, Fritz JM, Delitto A, McGill SM. Preliminary development of a clinical prediction rule for determining which patients with low back pain will respond to a stabilization exercise program. Arch Phys Med Rehabil. 2005;86(9):1753–1762; doi: 10.1016/j.apmr.2005.03.033.
6.
Rabin A, Shashua A, Pizem K, Dickstein R, Dar G. A clinical prediction rule to identify patients with low back pain who are likely to experience short-term success following lumbar stabilization exercises: a randomized controlled validation study. J Orthop Sports Phys Ther. 2014;44(1):6–B13; doi: 10.2519/jospt.2014.4888.
7.
Ferreira PH, Ferreira ML, Hodges PW. Changes in recruitment of the abdominal muscles in people with low back pain: ultrasound measurement of muscle activity. Spine. 2004;29(22):2560–2566; doi: 10.1097/01.brs.0000144410.89182.f9.
8.
Hodges PW, Richardson CA. Altered trunk muscle recruitment in people with low back pain with upper limb movement at different speeds. Arch Phys Med Rehabil. 1999;80(9):1005–1012; doi: 10.1016/s0003-9993(99)90052-7.
9.
MacDonald D, Moseley GL, Hodges PW. Why do some patients keep hurting their back? Evidence of ongoing back muscle dysfunction during remission from recurrent back pain. Pain. 2009;142(3):183–188; doi: 10.1016/j.pain.2008.12.002.
10.
Shafizadeh M. Movement coordination during sit-to-stand in low back pain people. Hum Mov. 2016;17(2):107–111; doi: 10.1515/humo-2016-0012.
11.
Silfies SP, Mehta R, Smith SS, Karduna AR. Differences in feedforward trunk muscle activity in subgroups of patients with mechanical low back pain. Arch Phys Med Rehabil. 2009;90(7):1159–1169; doi: 10.1016/j.apmr.2008.10.033.
12.
Panjabi MM. Clinical spinal instability and low back pain. J Electromyogr Kinesiol. 2003;13(4):371–379; doi: 10.1016/s1050-6411(03)00044-0.
13.
Van Dieën JH, Reeves NP, Kawchuk G, van Dillen LR, Hodges PW. Analysis of motor control in patients with low back pain: a key to personalized care? J Orthop Sports Phys Ther. 2019;49(6):380–388; doi: 10.2519/jospt.2019.7916.
14.
Biely SA, Silfies SP, Smith SS, Hicks GE. Clinical observation of standing trunk movements: what do the aberrant movement patterns tell us? J Orthop Sports Phys Ther. 2014;44(4):262–272; doi: 10.2519/jospt.2014.4988.
15.
D’Hooge R, Hodges P, Tsao H, Hall L, Macdonald D, Danneels L. Altered trunk muscle coordination during rapid trunk flexion in people in remission of recurrent low back pain. J Electromyogr Kinesiol. 2013;23(1):173–181; doi: 10.1016/j.jelekin.2012.09.003.
16.
Esola MA, McClure PW, Fitzgerald GK, Siegler S. Analysis of lumbar spine and hip motion during forward bending in subjects with and without a history of low back pain. Spine. 1996;21(1):71–78; doi: 10.1097/00007632-199601010-00017.
17.
Hides JA, Richardson CA, Jull GA. Multifidus muscle recovery is not automatic after resolution of acute, first-episode low back pain. Spine. 1996;21(23):2763–2769; doi: 10.1097/00007632-199612010-00011.
18.
Jacobs JV, Henry SM, Jones SL, Hitt JR, Bunn JY. A history of low back pain associates with altered electromyographic activation patterns in response to perturbations of standing balance. J Neurophysiol. 2011;106(5):2506–2514; doi: 10.1152/jn.00296.2011.
19.
Liangruenrom N, Suttikasem K, Craike M, Bennie JA, Biddle SJH, Pedisic Z. Physical activity and sedentary behaviour research in Thailand: a systematic scoping review. BMC Public Health. 2018;18(1):733; doi: 10.1186/s12889-018-5643-y.
20.
O’Sullivan PB. Lumbar segmental ‘instability’: clinical presentation and specific stabilizing exercise management. Man Ther. 2000;5(1):2–12; doi: 10.1054/math.1999.0213.
21.
Mannion AF, Käser L, Weber E, Rhyner A, Dvorak J, Müntener M. Influence of age and duration of symptoms on fibre type distribution and size of the back muscles in chronic low back pain patients. Eur Spine J. 2000;9(4):273–281; doi: 10.1007/s005860000189.
22.
Savage RA, Millerchip R, Whitehouse GH, Edwards RH. Lumbar muscularity and its relationship with age, occupation and low back pain. Eur J Appl Physiol Occup Physiol. 1991;63(3–4):265–268; doi: 10.1007/BF00233859.
23.
Kurtul Yildiz H, Ekin EE. Normal aging of the lumbar spine in women. J Back Musculoskelet Rehabil. 2017;30(5):1061–1067; doi: 10.3233/bmr-169666.
24.
Wattananon P, Ebaugh D, Biely SA, Smith SS, Hicks GE, Silfies SP. Kinematic characterization of clinically observed aberrant movement patterns in patients with non-specific low back pain: a cross-sectional study. BMC Musculoskelet Disord. 2017;18(1):455; doi: 10.1186/s12891-017-1820-x.
25.
Heuch I, Heuch I, Hagen K, Zwart J-A. Body mass index as a risk factor for developing chronic low back pain: a follow-up in the Nord-Trøndelag Health Study. Spine. 2013;38(2):133–139; doi: 10.1097/BRS.0b013e3182647af2.
26.
Su CA, Kusin DJ, Li SQ, Ahn UM, Ahn NU. The association between body mass index and the prevalence, severity, and frequency of low back pain: data from the Osteoarthritis Initiative. Spine. 2018;43(12):848–852; doi: 10.1097/brs.0000000000002601.
27.
Kahraman BO, Kahraman T, Kalemci O, Sengul YS. Gender differences in postural control in people with nonspecific chronic low back pain. Gait Posture. 2018;64:147–151; doi: 10.1016/j.gaitpost.2018.06.026.
28.
Sim J, Wright CC. The kappa statistic in reliability studies: use, interpretation, and sample size requirements. Phys Ther. 2005;85(3):257–268; doi: 10.1093/ptj/85.3.257.
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