Share this article on:

The Need for Multidimensional Stratification of Chronic Low Back Pain (LBP)

Rampersaud, Yoga Raja MD*,†; Bidos, Andrew DC‡,§; Fanti, Caroline BHSc(PT), MHM§,¶; Perruccio, Anthony V. PhD*,†,||,**

doi: 10.1097/BRS.0000000000002237
Epidemiology

Study Design. A cross-sectional study of Canadian patients suffering from low back pain (LBP) seeking primary care.

Objective. The aim of this study was to determine which existing primary care LBP stratification schema is associated with distinct subpopulations as characterized by easily identifiable primary epidemiological factors.

Summary of Background Data. LBP is among the most frequent reasons for visits to primary care physicians and a leading cause of years lived with disability. In an effort to improve treatment response/outcomes in LBP primary care, different classification systems have been proposed in an effort to provide more tailored treatment with the intent of improving outcomes. Group-specific risk factors and underlying etiology might suggest a need for, or inform, changes to treatment approaches to optimize LBP outcomes.

Methods. Stratification by dominant mechanical pain patterns; chronicity risk; disability severity. Multinomial logistic regression was used to identify the system showing greatest variability in associations with age, sex, obesity, and comorbidity. Once identified, the remaining schemas were incorporated into the model.

Results. N = 970; mean age: 50 years (range: 18–93); 56% female. Stratification by pain pattern revealed greater variability. Adjusted analysis: Increasing age was associated with greater odds of intermittent, extension-based back- or leg-dominant pain [odds ratio (OR): 1.02 and 1.06; P < 0.01]; being male with leg-dominant pain (ORs > 2; P < 0.01). Overweight/obesity was associated with extension-based leg-dominant pain (OR = 2.6; P < 0.02) and increasing comorbidity with extension-based back-dominant pain (OR = 1.3; P < 0.01). Severe disability was associated only with constant leg pain (OR = 3.9; P < 0.01), and high chronicity risk with extension-based leg-dominant pain (OR = 0.4; P = 0.03).

Conclusion. Dominant mechanical symptom stratification resulted in further discrimination of an epidemiologically distinct and a large subgroup of LBP patients not identified by disability or chronicity risk stratification alone. Findings suggest a need for primary care initiated multidimensional stratification in chronic LBP.

Level of Evidence: 3

*Division of Orthopaedic Surgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada

Arthritis Program, University Health Network, Toronto, Ontario, Canada

Health Quality Programs, University Health Network, Toronto, Ontario, Canada

§Interprofessional Spine Assessment and Education Clinics, University Health Network, Toronto, Ontario, Canada

Rehabilitation, Thunder Bay Regional Health Sciences Centre, Thunder Bay, Ontario, Canada

||Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

**Health Care & Outcomes Research, Krembil Research Institute, Toronto, Ontario, Canada.

Address correspondence and reprint requests to Yoga Raja Rampersaud, MD, Toronto Western Hospital, Orthopaedics, East Wing 1st Floor-441, 399 Bathurst St., Toronto, ON M5T 2S8, Canada; E-mail: raja.rampersaud@uhn.ca

Received 12 December, 2016

Revised 13 February, 2017

Accepted 15 February, 2017

The manuscript submitted does not contain information about medical device(s)/drug(s).

The Toronto Western/General Foundation and Ontario Ministry of Health and Long-Term Care grant funds were received in support of this work.

Relevant financial activities outside the submitted work: consultancy.

This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0

Low back pain (LBP) is currently ranked as the single leading cause of years lived with disability worldwide.1,2 Despite extensive study and numerous clinical practice guidelines, treatment costs for LBP continue to increase without improvement in functional outcomes.3,4 In the US, the annual expenditure related to LBP ($86 billion) has reached levels comparable to the care of diabetes ($98 billion), cancer ($89 billion), and nonspine arthritis ($80 billion).4

Although many acute episodes of LBP resolve,3 substantial numbers of patients suffer repeated relapses requiring treatment.5,6 A recent review reported that 75% of patients experiencing an episode of LBP continue to report pain at 6 weeks (subacute phase), and 66% continue to report pain at 3 months (chronic phase).7 Up to 25% of LBP persists in a constant, chronic state and incurs the largest costs (approximately 75%) in terms of health care utilization and loss of productivity.8,9

At the primary care level, most current clinical practice guidelines dichotomize LBP patients to those with specific LBP (a small group with easily identifiable pain source, e.g., infection) or with implied mechanical or “non-specific” LBP (a large group, >80%).3 Patients with nonspecific LBP are heterogeneous in terms of clinical characteristics and prognosis, and thus are more likely to respond favorably to specific treatment, rather than the current “one-size-fits-all” approach.8,10,11 Evidence warranting moderate to low confidence suggests that a more specific approach to management leads to tailored treatments (i.e., stratified management) and improved outcomes.10–13 Using a classification system based on mechanical patterns of symptom dominance and stratified management, Hall et al.10 found improved clinical outcomes compared with nonspecific management in an observational study. Results of a randomized control trial conducted in the UK suggests that stratified management based on psychosocial factors, using the Keele STarT Back Screening Tool (SBST) that separates LBP patients into low, moderate, and high-risk groups for persistent disabling back pain, is cost-effective compared with usual care.11 Recently, a National Institutes of Health Pain Consortium charged a Research Task Force to draft standards for research on chronic LBP.12 Their recommendations were for stratification by severity of pain and disability.

To enable stratified management, easily identifiable group-specific factors, with potentially unique underlying etiology, may inform pragmatic changes to assessment, clinical diagnosis, and treatment approaches for LBP patients in primary care.14 For example, classifications systems associated with easy to identify patient epidemiologic factors such as age, sex, body mass index, and concurrent medical and/or psychological conditions may enable or enhance subclassification of LBP patients. The primary objective of this cross-sectional study was to assess which existing simple primary care LBP stratification schema is associated with distinct subpopulations as characterized by these easily identifiable primary epidemiological factors. With a schema identified, we further investigated whether the alternative stratification systems contributed independently to grouping in this schema.

Back to Top | Article Outline

MATERIALS AND METHODS

Patients

Data derived from patients who sought care from their primary care provider (PCP) for persistent, recurrent chronic, or subacute LBP and were referred to the Inter-professional Spine Assessment and Education Clinics (ISAEC: www.isaec.org).

The purpose of ISAEC is to identify patients reporting persistent, recurrent chronic, or subacute LBP to their PCP and to use an interdisciplinary shared-care model to provide diagnosis and stratified education and self-management recommendations. Based out of three cities in Ontario, Canada (Toronto, Hamilton, and Thunder Bay), 220 PCPs participated in the program and referred patients to one of 21 ISAEC networked providers. Referred patients are evaluated by geographically linked, community-based, inter-professionally trained, advanced practice clinicians (Chiropractors and Physiotherapists) who are linked to networked specialists. Eligible patients included those aged more than 18 years and experiencing persistent LBP-related symptoms lasting from 6 weeks to 12 months or recurrent LBP. These lower and upper limits for persistent pain were established to exclude incident acute LBP episodes and chronic long-term pain disorders, respectively. Patients with a work-based insurance claim, pain related to a motor vehicle accident, established narcotic dependency, involved in active litigation, pregnant, or postpartum (<1 year), emergent spinal presentations, or an established pain disorder were excluded.

Patients were recruited from November 2012 to February 2014 and completed a health questionnaire and were given a standardized physical assessment at their initial ISAEC visit. The study was approved by the University Health Network Research Ethics Board (12-5477-BE/14-7776-BE).

Back to Top | Article Outline

ISAEC Stratification Schema (Performed Before Diagnostic Imaging)

LBP Pattern

Grounded in the work of Wilson et al.15 and Hall et al.10 patients with mechanical “non-specific” LBP symptoms were stratified into one of four clinical pain pattern subgroups. The essential elements of this system are determined by the location of the dominant symptoms and by the particular movements or postures that exacerbate or alleviate the pain, relying on patient history and physical examination. The four groups are back dominant pain aggravated by flexion (BD-F; i.e., worse with sitting or bending forward and better with standing or extending the lumbar spine), back dominant pain aggravated by extension (BD-E; i.e., worse with standing/walking and better with sitting or flexion of the lumbar spine), constant leg dominant pain (C-LD; i.e., lumbar radiculopathy), and intermittent leg dominant pain (I-LD; i.e., neurogenic intermittent claudication). Using 59 therapist examiners and 204 subjects, Wilson et al.15 reported that this system demonstrated a kappa coefficient (κ) of 0.61 (P < 0.001) and an overall agreement of 78.9%. Therapist experience level did not significantly affect reliability measures. Among experienced therapists, κ = 0.61 (P < 0.001) with 80.2% agreement. For the novice group, κ = 0.60 (P < 0.001) with 76.9% agreement. BD-F was chosen as the referent group for analytical modeling. From an etiologic aspect, ISAEC has operationalized these patterns to the most likely source of the dominant symptoms: BD-F = discogenic LBP, BD-E = facetogenic LBP, C-LD = radiculopathy due to disc herniation, and I-LD = neurogenic claudication due to spinal stenosis.

Back to Top | Article Outline

Severity of Disability (Health Questionnaire)

The Oswestry Disability Index (ODI) was used to assess level of back-related disability. It is a widely used and validated disability measure in LBP.16–19 ODI asks respondents to select one of six descriptors indicating the level of difficulty, interference, or intensity with 10 items: pain intensity, personal care, lifting, walking, sitting, standing, sleeping, employment, homemaking, social life, and travelling. Each is scored on a 0 to 5 scale, and the sum of the 10 scores reported as a percentage of the total possible score. Cutoffs have been established to stratify according to severity: 0% to 20% deemed “minimal,” 20% to 40% deemed “moderate,” and 40% or greater deemed “severe or greater” disability16; “minimal” was chosen as the referent group.

Back to Top | Article Outline

Risk of Chronicity

The Keele SBST 11,20 (https://www.keele.ac.uk/sbst/startbacktool/) is a nine-item tool designed to measure severity in nine domains: leg pain and shoulder/neck (each scaled from 0—“not at all” to 4—“extremely”), dressing, walking, fear, worry, catastrophizing and mood (each scaled from 0—“completely disagree” to 10—“strongly agree”), and bothersomeness (scaled from 0—“not at all” to 4—“extremely”). The tool can be used to group patients into three categories of risk of poor outcome (i.e., persistent disabling symptoms)—low, medium, and high risk. For analytical purposes, “low” was designated the referent group.

Back to Top | Article Outline

Additional Study Measures

In addition, the health questionnaire elicited age, sex, and height and weight, from which body mass index was calculated (BMI, kg/m2). For analysis, BMI was categorized as overweight/obese (BMI ≥ 25) versus normal (BMI < 25).

Patients were presented with a list of 14 medical conditions to which they indicated yes/no to whether they had the condition. These were summed and a count of chronic conditions was generated.

An 11-point numerical pain rating scale was used to elicit each of back and leg pain both at rest and with activity. Patients were asked to rate their average pain on a 0 to 10 scale. The scale was anchored with “No pain” (at “0”) and “Worst possible pain” (at “10”). One score for each of back and leg pain was derived on the basis of the maximum response among the two respective items.

Back to Top | Article Outline

Statistical Analyses

Descriptive statistics are presented for each study measure, overall and by clinical pain pattern subgroup (owing to subsequent findings). Statistical comparisons across pain pattern subgroups were made by way of analysis of variance or Chi-square test.

Initially, multinomial logistic regression was used to investigate the association between age, sex, overweight/obese, and comorbidity count (patient factors) with each of the classification systems (model outcomes); three separate models, one for each system. The system with the greatest variability by virtue of associations with patient factors was retained for subsequent multinomial regression modeling. In this instance, the remaining two systems were additionally entered into the model as potential correlates, along with back and leg pain intensity scores.

Back to Top | Article Outline

RESULTS

Overall Sample Characteristics

The sample included 970 patients. By dominant pain pattern, 42% were classified as BD-F, 31% BD-E, 17% CL-D, and 10% I-LD (Table 1). By chronicity risk, 24% were deemed “high,” 31% “medium,” and 45% “low” risk. Finally, by severity of disability, 39% were deemed “severe,” 40% “moderate,” and 21% “minimal.” The overall mean age of the sample was 50 years, ranging from 18 to 93 years.

TABLE 1

TABLE 1

Back to Top | Article Outline

Differentiation Between Stratification Schema

Table 2 presents the results from multinomial regression analyses. The greatest variability in associations was found for the dominant pain pattern subgroups where age, sex, BMI, and comorbidity count each were significantly associated with the subgrouping. In contrast, only BMI and comorbidity count were associated with the subgroups when considering classification by either chronicity risk or severity of disability. Given this, dominant pain pattern was retained as the schema outcome of interest for the final multinomial logistic model.

TABLE 2

TABLE 2

Back to Top | Article Outline

Sample Characteristics by Pain Pattern Subgroupings

The I-LD and BD-E groups had higher mean ages, 63 and 52 years, respectively, than the BD-F and C-LD groups at 46 and 47 years, respectively (Table 3). The proportion of females was highest in the BD-E and BD-F groups at 61% and 59% versus 46% in the C-LD and I-LD groups.

TABLE 3

TABLE 3

In the I-LD group, 76% were categorized as overweight/obese, compared with 67% in the C-LD group, 59% in the BD-E group, and 53% in the BD-F group. The I-LD and BD-E groups had higher mean comorbidity count, 1.9 and 1.4, respectively, than the BD-F and C-LD groups at a mean of 1.0.

A similar proportion of patients deemed to have severe disability was found for the BD-F and BD-E groups, ranging from 33% to 35%, compared with 42% in the I-LD and 58% in the C-LD groups. As expected, mean back pain intensity scores were higher (i.e., worse) in the back dominant pain groups, and mean leg pain intensity scores were higher (i.e., worse) in the leg dominant pain groups.

Finally, similar proportions within the BD-F, BD-E, and I-LD groups were deemed high risk for chronicity, ranging from 21% to 23%, compared with 35% in the C-LD group.

Back to Top | Article Outline

Examination of Pain Pattern Subgroupings With Multivariable Adjusted Analyses

From the adjusted model (Table 4), increasing age was significantly associated with a greater odds of being in the BD-E and I-LD groups [odds ratios (ORs): 1.02 and 1.06; P < 0.01] than the BD-F group. Men had odds more than twice that of women for being in the C-LD and I-LD groups (P < 0.01).

TABLE 4

TABLE 4

Being overweight/obese, compared with normal, was associated with a 2.5 times greater odds of being in the I-LD group (P < 0.02) than the BD-F group. Every unit increase in comorbidity count was associated with a 27% increased odds of being in the BD-E group (P < 0.01) compared with being in BD-F.

As expected, higher (worse) back pain intensity scores were associated with decreased odds of being in the leg dominant groups compared with the BD-F group, and higher (worse) leg pain scores were associated with increased odds of being in the leg dominant groups compared with BD-F.

Severe disability was only associated with an increased odds of being in the C-LD group relative to the BD-F group (OR 3.9, P < 0.01), while high chronicity risk was associated with a decreased odds of being in the I-LD group relative to BD-F (OR: 0.36; P = 0.03). The multiple degree of freedom test for the overall effect of chronicity risk was not found to be significant (P > 0.30).

Back to Top | Article Outline

DISCUSSION

Our results demonstrate significant heterogeneity in a primary care population with persistent LBP. Stratification by dominant pain pattern revealed the greatest variability in associations with common epidemiological factors. From adjusted analysis, increasing age was associated with greater odds of having back dominant extension (BD-E) and I-LD symptoms and is consistent with the most likely etiology being facetogenic LBP and spinal stenosis causing neurogenic claudication, respectively. Being male was associated with greater odds of having C-LD or I-LD, being overweight/obese with greater odds of I-LD, and increasing comorbidity count with greater odds of B-DE-based symptoms. Finally, severe disability was associated with having C-LD symptoms and high chronicity risk with decreased odds of I-LD symptoms. Disability and chronicity risk did not otherwise variably impact odds across the clinical LBP patterns. These results provide a rationale for combined use of these stratification tools in LBP models of care in that they each look at different dimensions of LBP (i.e., mechanical pain pattern, degree of disability, and psychosocial well-being) and they in-turn also serve to direct a different dimension of treatment.10–14 With each having their own merit, 12,13 the lack of highly unique subpopulations associated with any one stratification approach is consistent with the findings of Fairbank et al.13 They assessed the role of classification systems of chronic LBP that generally fell into the descriptive diagnostic systems, prognostic, or those that direct treatment, and concluded that no one classification system be adopted for all purposes.

Stratifying patients at the primary care level provides an opportunity for the development and delivery of more effective and patient-centered care to improve treatment response and where possible reduce chronicity. In addition to improving response through tailored treatment, identifying distinct “at-risk” subgroups can suggest different etiologies/disease trajectories. For example, in the current study, the mechanical stratification of LBP proposed by Hall et al. provided the most distinct clinical subgroups, particularly for those presenting with back dominant or I-LD symptoms that are typically brought on by extension activity, representing older, obese patients with greater comorbidities, but less chronicity risk from a psychosocial aspect. Although the approach from Hall et al.10 is not designed to make specific inference to a patho-anatomical source of pain, these patients present with extension dominant LBP and/or neurogenic claudication and essentially represent symptomatic facet osteoarthritis (OA).10,21–24 This group represents a growing demographic and accounted for 41% of this cohort.

Facet OA or lumbar spinal stenosis (LSS) and associated symptoms represent a significant source of health care and socioeconomic burden that warrants a significant increase in basic and clinical research.25 It is estimated that facet OA with spinal stenosis causing neurogenic claudication affects about 20% of people over 65 and about half of that group suffer serious restrictions in their daily routines.26 Battie et al.26 demonstrated that the associated health burden of LSS on health-related quality of life was significant and is about the same or greater than diabetes, heart disease, arthritis, or stroke. Clinically, our current understanding of OA necessitates the consideration of spinal OA within the broader context of the impact of OA.27–29 Consequently, recommendation of typical LBP interventions (including psychologically based interventions [11]) without consideration of the unique underlying medical comorbidity (including multisite OA) in this large subgroup of LBP patients may be inadequate. A recent review demonstrated limited and short-lived benefits of nonoperative treatment for these patients.30 In addition, data from the SPORT studies have demonstrated good comparative-effectiveness of surgical treatment for patients with LSS and in particular those with degenerative spondylolisthesis that is sustainable out to 4 years.31 Consequently, multidimensional management in this subgroup should include a focus on multi-comorbidity management, and in those failing conservative management, earlier specialist referral.

Due to the successful results demonstrated by the Start Back trial,11 there has been significant interest and implementation of the Start Back stratification tool by many groups.32,33 In the current study, we have demonstrated similar findings regarding the proportion of primary care patients presenting with a high risk of chronicity (21–34%).11 However, our study uniquely demonstrates that the proportion of high-risk patients is relatively similar across the different dominant clinical pain presentations. This suggests that the use of the Start Back stratification tool alone, although a valid prognostic tool that enables identification of patients requiring cognitive behavioral therapy (CBT) or those who are likely to succeed with simple education and self-management, would not enable further patient specific treatment regarding mechanical patterns of pain and more targeted initial medical management.10 We demonstrated an almost identical finding regarding stratification based on severity of disability. Deyo et al.12 recently recommended the stratification of chronic LBP by its impact (e.g., severity of disability) as a standard going forward for future research. On the basis of the present findings, this recommendation may be problematic from an epidemiologic perspective in that it would only serve to identify one aspect of LBP and as demonstrated not provide a useful means for identification of distinct subgroups beyond the degree of impact. As recommended by Fairbank et al.,13 we believe that a multidimensional combination of stratification tools is required to more holistically represent the complexities of chronic LBP.

Back to Top | Article Outline

Study Considerations and Limitations

This was a cross-sectional study and therefore does not provide longitudinal prognostic data regarding the effectiveness of a multidimensional stratification approach that included mechanical patterns of pain. As well, further study with a more comprehensive consideration of patient and societal factors are required to explore the distinctness of the potential subgroups we have identified. Although uncommon, in instances wherein a patient's pain pattern was potentially mixed, symptom questions were phrased in alternative ways to establish which symptom or factor was most limiting, and this determined the dominant pattern. The occurrence of this situation was not recorded, and thus potential confounding is possible. Finally, the presence of comorbidities was considered in the study as a count of conditions. The limitation of this is that some may be under treatment, while others may not, and the severities of the condition(s) were not considered. Data in this regard were not available for study.

Back to Top | Article Outline

CONCLUSION

LBP patients are very heterogeneous and require primary care initiated stratification beyond the impact of symptoms and psychosocial risk factors. In particular, the dominant mechanical patterns of pain at presentation appear to have distinct and easily identifiable epidemiological profiles that may enhance current stratification approaches and enable more targeted interventions. Interestingly, differences were identified with a backdrop of little variability in disability severity and chronicity risk across pain pattern groups, suggesting initial stratification based on the former factors may not result in distinct LBP subgroups and thus limit clinical and epidemiological research.

Back to Top | Article Outline

Key Points

  • The LBP population seeking primary health care is heterogeneous, and it appears no single stratification system readily distinguishes between subgroups.
  • Primary care stratification by dominant mechanical pain pattern appears to provide an ability to better distinguish between groups that may be epidemiologically distinct.
  • Dominant mechanical symptom stratification in LBP patients, in addition to disability and chronicity risk, is supported in both the clinical and research setting.
Back to Top | Article Outline

References

1. Hoy D, Bain C, Williams G, et al. A systematic review of the global prevalence of low back pain. Arthritis Rheum 2012; 64:2028–2037.
2. Vos T, Flaxman AD, Naghavi M, et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380:2163–2196.
3. Koes BW, van Tulder M, Lin CW, et al. An updated overview of clinical guidelines for the management of non-specific low back pain in primary care. Eur Spine J 2010; 19:2075–2094.
4. Martin BI, Deyo RA, Mirza SK, et al. Expenditures and health status among adults with back and neck problems. JAMA 2008; 299:656–664.
5. Dagenais S, Caro J, Haldeman S. A systematic review of low back pain cost of illness studies in the United States and internationally. Spine J 2008; 8:8–20.
6. Itz CJ, Geurts JW, van Kleef M, et al. Clinical course of non-specific low back pain: a systematic review of prospective cohort studies set in primary care. Eur J Pain 2013; 17:5–15.
7. Donelson R, McIntosh G, Hall H. Is it time to rethink the typical course of low back pain? PM R 2012; 4:394–401. quiz 0.
8. Keller A, Hayden J, Bombardier C, et al. Effect sizes of non-surgical treatments of non-specific low-back pain. Eur Spine J 2007; 16:1776–1788.
9. Luo X, Pietrobon R, Sun SX, et al. Estimates and patterns of direct health care expenditures among individuals with back pain in the United States. Spine (Phila Pa 1976) 2004; 29:79–86.
10. Hall H, McIntosh G, Boyle C. Effectiveness of a low back pain classification system. Spine J 2009; 9:648–657.
11. Hill JC, Whitehurst DG, Lewis M, et al. Comparison of stratified primary care management for low back pain with current best practice (STarT Back): a randomised controlled trial. Lancet 2011; 378:1560–1571.
12. Deyo RA, Dworkin SF, Amtmann D, et al. Report of the NIH Task Force on Research Standards for Chronic Low Back Pain. Spine J 2014; 14:1375–1391.
13. Fairbank J, Gwilym SE, France JC, et al. The role of classification of chronic low back pain. Spine (Phila Pa 1976) 2011; 36:S19–S42.
14. Spratt KF. Use of the assessment-diagnosis-treatment-outcomes model to improve patient care. Mil Med 2013; 178 (10 suppl):121–131.
15. Wilson L, Hall H, McIntosh G, et al. Intertester reliability of a low back pain classification system. Spine (Phila Pa 1976) 1999; 24:248–254.
16. Fairbank JC, Couper J, Davies JB, et al. The Oswestry low back pain disability questionnaire. Physiotherapy 1980; 66:271–273.
17. Fairbank JC, Pynsent PB. The Oswestry Disability Index. Spine (Phila Pa 1976) 2000; 25:2940–2952. discussion 52.
18. Gronblad M, Hupli M, Wennerstrand P, et al. Intercorrelation and test-retest reliability of the Pain Disability Index (PDI) and the Oswestry Disability Questionnaire (ODQ) and their correlation with pain intensity in low back pain patients. Clin J Pain 1993; 9:189–195.
19. Leclaire R, Blier F, Fortin L, et al. A cross-sectional study comparing the Oswestry and Roland-Morris Functional Disability scales in two populations of patients with low back pain of different levels of severity. Spine (Phila Pa 1976) 1997; 22:68–71.
20. Keele University. STarT Back Screening Tool. Available at: https://www.keele.ac.uk/sbst/startbacktool/]. Accessed April 13, 2016.
21. Gellhorn AC, Katz JN, Suri P. Osteoarthritis of the spine: the facet joints. Nat Rev Rheumatol 2013; 9:216–224.
22. Genevay S, Atlas SJ. Lumbar spinal stenosis. Best Pract Res Clin Rheumatol 2010; 24:253–265.
23. Goode AP, Carey TS, Jordan JM. Low back pain and lumbar spine osteoarthritis: how are they related? Curr Rheumatol Rep 2013; 15:305.
24. Suri P, Rainville J, Kalichman L, et al. Does this older adult with lower extremity pain have the clinical syndrome of lumbar spinal stenosis? JAMA 2010; 304:2628–2636.
25. Deyo RA, Mirza SK, Martin BI, et al. Trends, major medical complications, and charges associated with surgery for lumbar spinal stenosis in older adults. JAMA 2010; 303:1259–1265.
26. Battie MC, Jones CA, Schopflocher DP, et al. Health-related quality of life and comorbidities associated with lumbar spinal stenosis. Spine J 2012; 12:189–195.
27. Centers for Disease Control and Prevention. Arthritis as a potential barrier to physical activity among adults with heart disease—United States, 2005 and 2007. MMWR Morb Mortal Wkly Rep 2009; 58:165–169.
28. Hawker GA, Croxford R, Bierman AS, et al. All-cause mortality and serious cardiovascular events in people with hip and knee osteoarthritis: a population based cohort study. PLoS One 2014; 9:e91286.
29. Hoy DG, Smith E, Cross M, et al. The global burden of musculoskeletal conditions for 2010: an overview of methods. Ann Rheum Dis 2014; 73:982–989.
30. Ammendolia C, Stuber KJ, Rok E, et al. Nonoperative treatment for lumbar spinal stenosis with neurogenic claudication. Cochrane Database Syst Rev 2013; 8:CD010712.
31. Tosteson AN, Tosteson TD, Lurie JD, et al. Comparative effectiveness evidence from the spine patient outcomes research trial: surgical versus nonoperative care for spinal stenosis, degenerative spondylolisthesis, and intervertebral disc herniation. Spine (Phila Pa 1976) 2011; 36:2061–2068.
32. Murphy SE, Blake C, Power CK, et al. The effectiveness of a stratified group intervention using the STarTBack screening tool in patients with LBP: a non randomised controlled trial. BMC Musculoskelet Disord 2013; 14:342.
33. Rampersaud YR, Bidos A, Fanti C, et al. Best Paper Award - Preliminary Report from the Ontario Interprofessional Spine Assessment and Education Clinics (ISAEC). Spine J 2014; 14:S40.
Keywords:

cross-sectional study; epidemiology; health status; low back pain; non-surgical intervention; osteoarthritis; pain pattern; primary health care; risk assessment; severity of illness index

Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved.