CPR for Lumbar Stabilisation

(Redirected from Spinal Stabilization)



Patients presenting with low back pain are generally a heterogeneous population, and because in 85% of cases no specific diagnosis can be made for low back pain, a treatment based classification system is useful for physical therapists in developing rehabilitation programs for patients unspecified with low back pain. In this type of system, patients are categorized according to general presentation, findings from a physical examination, impairments, and functional limitations, and are grouped into one of several treatment classifications. A 2003 study done by Fritz et al [1] compared the treatment based classification (TBC) approach and current clinical practice guidelines (CPG) for treatment of patients with low back pain. The TBC system involved classifying patients into categories and matching the treatment to the category. The clinical practice guidelines included low stress aerobic exercise, general muscle re-conditioning and advice to remain active. The change was evaluated using the initial and four week Oswestry Disability Index score. Although both groups showed some improvement, the study found a 22% greater improvement for patients whose treatment was matched on the TBC as compared to those who were provided treatment based on the CPG.

In order to assist with such treatment classifications, clinical prediction rules (CPRs) are a set of criteria that a patient should meet in order to be placed into a specific treatment group. A CPR for the spinal stabilization treatment category [2] is provided below and generally includes a younger age, instability, and greater overall mobility.[3]


Hicks et al's [2] lumbar stabilization rule contains two groups: a “Success” group and an “Improvement” group. The two groups are different in the magnitude of the change in their outcome score and in the variables used to predict group assignment.[2]

The Success group changed by better than 50% on the Oswestry Disablement Scale (ODI). The Improvement group changed from 6% to 49% on the ODI. Any change less than 6% was considered a treatment failure and alternative treatments were suggested.[2]

Clinical Prediction Rule Components[2]

Use this template to test your patient for inclusion in the Success stabilization group.

Yes No Success Rule predictor variables

Age less than 40 years old

SLR greater than 91 degrees

Aberrant motion present

Positive prone instability test

Use this template to test your patient for inclusion in the Improvement stabilization group.

Yes No Improvement Rule predictor variables

FABQ physical activity scale greater than 9 points

Aberrant movements absent

No lumbar hypermobility with prone spring testing

Negative prone instability test

Decision Rule

The decision rules can be considered separately.

Success Rule
Number of variables present Likelihood ratio Probability shift Group assignment
>1 1.3 No shift Group assignment unlikely
> 2 1.9 Negligible shift Group assignment unlikely
>3 4.0 34% upward shift 67% chance the patient is in the success group

The “Improvement Rule” defines the amount or improvement each group achieved. The Success Group had better than a 50% improvement in the Oswestry while the Improvement Group had between 6 and 49% improvement in the Oswestry.

Improvement Rule
Number of variables present Positive likelihood ratio Negative likelihood ratio Probability shift Group assignment
One or more 1.1 0.20 no shift / -50% Group assignment unlikely
Two or more 6.3 0.18 no shift / -50% 94% likely to be in the improvement group
Three or more 18.8 0.43 +22% / - 50% 97% likely to be in the improvement group
Four 6.0 0.84 +27% / negligible 94% likely to be in the improvement group

Prevalence of the group

Three sub-groups exhibited different responses to lumbar stabilization training.

Number of subjects Prevalence Sub-group Oswestry change score at 8 weeks
18/54 33% Success group >50%
21/54 39% Improvement group 6 – 49%
15/54 28% Failure group >6%

Test Description[2]


Historical and self-report findings are the following: 

  • Age less than 40 years old
  • Fear Avoidance Beliefs Questionnaire physical activity scale greater than nine

Physical exam findings are described as follows:

  • SLR greater than 91 degrees: The patient is supine. An inclinometer or a goniometer may be used. The inclinometer is calibrated placed on the tibial tubercle with the patient’s leg resting on the table. The stationary arm of the goniometer is placed alongside the patient’s trunk with the axis centered over the greater trochanter. The therapist raises the leg passively with the knee fully extended.
  • Aberrant motion present with trunk forward bending: In standing, the patient is asked to bend forward while keeping the knees straight. Total spine flexion is encouraged although touching the toes is not emphasized. The patient is encouraged to relax in the fully flexed position for 2-5 seconds. Then, the patient is asked to straighten up. A positive test is an “instability catch”, painful arc of motion, thigh climbing (Gowers’ sign)or a reversal of the lumbo-pelvic motion.
  • Positive prone instability test, Part 1: The patient lies on the exam table with the trunk, head and arms while the feet are on the floor. The therapist applies posterior-to-anterior pressure (P/A) to the spinous processes of the lumbar spine. Any painful provocation is recorded. Part 2: The therapist then asks the patient to raise one leg up off of the floor and P/A pressure is again applied to the spine. A reduction in pain while the leg is raised is a positive test.
  • No lumbar hypermobility with spring testing: In prone, P/A pressure is applied to the lumbar spinous processes with the therapist’s thenar eminence. Segmental spinal mobility at each level is judged hypomobile (stiff), normal or hypermobile (lax).


Hicks et al's rule is a Level 4 derivation rule.

Hicks et l examined 54 people with non-radicular lower back pain in three outpatient clinics in Pennsylvania and Mississippi over eight weeks using a prospective, single-arm study design. This study design is capable of deriving prognostic factors but not treatment effect modifiers.

Prognostic factors are patient characteristics that estimate a patients' likely outcome irrespective of the chosen management.[5]

Treatment effect modifiers are factors measured at baseline that influence the relationship between a specific intervention and an outcome.[5]

The research subjects were an average of 42.4 years old, had an average NPRS (pain) score of 4.5 and average FABQ physical activities score of 14.6. Baseline Oswestry Disability Index (ODI) score was 30 points.

Change in the ODI score was calculated with this formula: Change score=[(baseline ODI score – 8 week ODI score)/(baseline ODI score)] x 100

Any three variables present for the Improvement group predicted group assignment better than any other combination (97%). Four positive test variables for the Improvement group did not improve the accuracy of the rule for physical therapist decision making (94%).

Hicks et al checked 26 physical examination variables, six self-report variables and eight demographic/historical variables for association with either success or failure. The association accepted a liberal error rate of 10% to avoid filtering potentially useful predictor variables. Four test variables for success and nine test variables for failure were then entered into a second filter, the logistic regression equation, which resulted in the tests above.


There is much debate with regards to their validity and clinical applicability and taking in to consideration results from contemporary research, we should caution clinicians in using them[6][7][8]. The results from the available data do not support the use of clinical prediction rules in the management of non-specific low back pain[6].  The current body of evidence does not enable confident direct clinical application of any of the identified CPRs[7].  There is, at present, little evidence that CPRs can be used to predict effects of treatment for musculoskeletal conditions. The principal problem is that most studies use designs that cannot differentiate between predictors of response to treatment and general predictors of outcome[8].  Currently only 1 CPR, the one classifying patients in a group likely to benefit from spinal manipulation, is at the validation stage of development within an RCT designed to predict response to treatment[9][10][11][12].  All other CPRs are still at a derivation level. Validation of these rules is imperative to allow clinical application.

Read more about the validity and applicability of CPRs on the main Clinical Prediction Rules page

So what can I do with this information?

Although this CPR has not been validated to date, physiotherapists may still use the information to inform their practice. As sentient, autonomous practitioners, physiotherapists use all the subjective and objective information at their disposal throughout the clinical reasoning process, not one single piece of evidence such as a CPR. Thus, we may still determine, based on our clinical reasoning, that stabilisation exercises are an appropriate treatment component for the individual in front of us.

Recent Related Research (from Pubmed)


  1. Fritz JM, Delitto A, Erhard DC. (2003) Comparison of Classification-Based Physical Therapy with Therapy Based on Clinical Practice Guidelines for Patients with Acute Low Back Pain. SPINE. 28 (13) 1363-1372.
  2. 2.0 2.1 2.2 2.3 2.4 2.5 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 Sep;86(9):1753-62.
  3. Fritz JM, Cleland JA, Childs JD. (2007) Subgrouping Patients with Low Back Pain: Evolution of a Classification Approach to Physical Therapy. Journal of Orthopaedic and Sports Physical Therapy, 37 (6), 290-302
  4. Physiotutors. Hicks Clinical Prediction Rule for Lumbar Spine Stabilization. Available from: https://www.youtube.com/watch?v=qWigT_By10E
  5. 5.0 5.1 Hill JC, Fritz JM. Psychosocial Influences on Low Back Pain, Disability and Response to Treatment. Phys Ther. 2011;91(5):pp.712-721.
  6. 6.0 6.1 Patel S, Friede T, Froud R, Evans DW, Underwood M. Systematic review of randomised controlled trials of clinical prediction rules for physical therapy in low back pain. Spine (Phila Pa 1976). 2012 Dec 11.
  7. 7.0 7.1 Haskins R, Rivett DA, Osmotherly PG. Clinical prediction rules in the physiotherapy management of low back pain: a systematic review. Man Ther. 2012 Feb;17(1):9-21
  8. 8.0 8.1 Stanton TR, Hancock MJ, Maher CG, Koes BW. Critical appraisal of clinical prediction rules that aim to optimize treatment selection for musculoskeletal conditions. Phys Ther. 2010 Jun;90(6):843-54.
  9. Childs J, Fritz J, Flynn T, et al. A clinical prediction rule to identify patients with low back pain most likely to benefit from spinal manipulation: a validation study. Ann Intern Med. 2004;141:920–928
  10. Cleland JA, Fritz JM, Whitman JM, et al. The use of a lumbar spine manipulation technique by physical therapists in patients who satisfy a clinical prediction rule: a case series. J Orthop Sports Phys Ther. 2006;36:209–214.
  11. Flynn T, Fritz J, Whitman J,et al. A clinical prediction rule for classifying patients with low back pain who demonstrate short-term improvement with spinal manipulation. Spine (Phila Pa 1976). 2002;27:2835–2843
  12. Hancock MJ, Maher CG, Latimer J, et al. Independent evaluation of a clinical prediction rule for spinal manipulative therapy: a randomised controlled trial. Eur Spine J. 2008;17:936–943.