FROM:
Spine (Phila Pa 1976). 2002 (Dec 15); 27 (24): 28352843 ~ FULL TEXT
Timothy Flynn, PT, PhD, Julie Fritz, PT, PhD, Julie Whitman, PT, DSc,
Robert Wainner, PT, PhD, Jake Magel, PT, DSc, Daniel Rendeiro, PT, DSc,
Barbara Butler, PT, Matthew Garber, PT, DSc, and Stephen Allison, PT, PhD
U.S. Army-Baylor University Graduate Program in Physical Therapy,
San Antonio, Texas, USA.
timothy.flynn@cen.amedd.army.mil
STUDY DESIGN: A prospective, cohort study of patients with nonradicular low back pain referred to physical therapy.
OBJECTIVE: Develop a clinical prediction rule for identifying patients with low back pain who improve with spinal manipulation.
SUMMARY OF BACKGROUND DATA: Development of clinical prediction rules for classifying patients with low back pain who are likely to respond to a particular intervention, such as manipulation, would improve clinical decision-making and research.
METHODS: Patients with nonradicular low back pain underwent a standardized examination and then underwent a standardized spinal manipulation treatment program. Success with treatment was determined using percent change in disability scores over three sessions and served as the reference standard for determining the accuracy of examination variables. Examination variables were first analyzed for univariate accuracy in predicting success and then combined into a multivariate clinical prediction rule.
RESULTS: Seventy-one patients participated. Thirty-two had success with the manipulation intervention. A clinical prediction rule with five variables (symptom duration, fear-avoidance beliefs, lumbar hypomobility, hip internal rotation range of motion, and no symptoms distal to the knee) was identified. The presence of four of five of these variables (positive likelihood ratio = 24.38) increased the probability of success with manipulation from 45% to 95%.
CONCLUSION: It appears that patients with low back pain likely to respond to manipulation can be accurately identified before treatment.
From the Full-Text Article:
Introduction
Attempts to identify effective interventions for patients
with low back pain (LBP) have been largely unsuccessful. [65, 66]
One explanation offered for the lack of evidence
is the inability to define subgroups of patients most likely
to respond to a particular intervention. [8, 39] Without the
ability to match patients to specific interventions, clinicians
are left without evidence or guidance for their decision-making.
Because of the difficulty in subgrouping
patients with LBP based on pathoanatomy, [67] attempts
have been made to classify patients based on findings
from the history and physical examination. [17, 49, 60, 64] Developing
effective, clinically applicable methods for classifying
patients with LBP could improve decisionmaking
and outcomes by matching interventions to the
patients they are most likely to benefit. Classification
methods would also enhance the power of clinical research
by permitting researchers to study more homogeneous
groups of patients. [56] Identifying methods for classifying
patients with LBP has been identified as an
important research priority. [1, 6, 66]
Manipulation is an intervention commonly used in
the treatment of individuals with LBP. Several randomized
trials have found manipulation to be more effective
than placebo [52, 54, 71] or other interventions. [16, 22, 36, 63]
However, other studies have not shown any benefits for
manipulation versus other interventions. [10, 2628] The disparity
may be partly attributable to the admission of a
heterogeneous group of patients with LBP without an
attempt to identify a priori those likely to benefit from
the intervention. Other randomized trials have found
manipulation to be more beneficial for a subgroup of
patients with more acute symptoms [30, 42] or more limited
straight-leg raise range of motion. [47] No previous studies
have sought to develop a multifactorial classification rule
that would maximize the prediction of success with manipulation
before the intervention.
One subgroup of patients for whom manipulation is
proposed to be effective comprises individuals with sacroiliac
(SI) region dysfunction. [16, 19, 22, 29, 62, 71] Numerous
clinical findings have been promoted as capable of identifying
patients with SI dysfunction; however, previous
studies have questioned the reliability and validity of
many of these tests. [4, 9, 20, 21, 37, 40, 41, 44, 45, 50, 53, 61] Previous
studies have generally examined individual tests for SI
dysfunction in isolation and typically have not included
other potentially important factors from the history or
examination. An exception is the work published by Cibulka
et al, who described a cluster of movement and
provocative tests purported to identify SI joint dysfunction. [1214]
However, this test cluster was chosen based on
the authors clinical experience, and the predictive validity
is unknown. [12] Furthermore, most studies have used
short-term pain relief with an injection of an anesthetic
agent into the SI joint as the reference standard against
which validity has been judged. [9, 21, 32, 44] The validity of
using anesthetic joint blocks as a reference standard for
diagnostic studies has not been demonstrated. [3, 32, 59] The
reference standard should represent the condition of interest
that the diagnostic test is attempting to identify. [55]
If the goal of a test is to identify patients likely to respond
to an intervention directed toward the SI region (e.g.,
manipulation), then the use of a criterion standard of
short-term pain relief with an injection is questionable. A
more viable alternative may be a longer duration response
to the intervention in question. A study using a
more therapeutic reference standard, which considers
a broader variety of clinical findings and attempts to
combine clinical findings, will be more useful in identifying
a subgroup of patients with SI dysfunction who are
likely to respond to spinal manipulation. The purpose of
this study was to develop a clinical prediction rule for
identifying patients with LBP likely to respond favorably
to a specific manipulation technique. A variety of findings
were considered against a reference standard of
change in disability.
Methods
A prospective cohort study of patients with LBP was conducted
at two outpatient facilities: Brooke Army Medical Center and
Wilford Hall Air Force Medical Center. Patients were between
the ages of 18 and 60 years, referred to physical therapy with a
diagnosis related to the lumbosacral spine, and had a chief
complaint of pain and/or numbness in the lumbar spine, buttock,
and/or lower extremity. The baseline Oswestry disability
score had to be at least 30%. Exclusion criteria were current pregnancy,
signs consistent with nerve root compression (positive
straight-leg raise at <45°, or diminished lower extremity strength,
sensation, or reflexes), prior lumbar spine surgery, or a history of
osteoporosis or spinal fracture. All patients were briefed on the
purpose of the study and signed an informed consent approved by
the Brooke Army Medical Center and Wilford Hall Air Force
Medical Center Institutional Review Boards.
Therapists. Eight licensed physical therapists participated.
Four were residents in the U.S. Army-Baylor Post-Professional
Doctoral Program in Orthopedic and Manual Physical Therapy,
and four were instructors in the program. This program is
designed to provide physical therapists serving in the U.S. Military with advanced training in orthopedic and manual physical therapy. A 1-day training session was conducted for participating therapists to standardize examination and treatment techniques.
Examination Procedures. Patients completed a baseline examination
including demographic information and a pain rating
using an 11-point scale. [34] A pain diagram [46] was used to
categorize symptoms as low back, buttock/thigh, or distal to
the knee based on the distal-most extent of symptoms. [70] The
Modified Oswestry Disability Questionnaire (OSW) assessed
disability related to LBP. [25] The Fear-Avoidance Beliefs Questionnaire
(FABQ) was used to assess the patients beliefs about
the influence of activity on LBP. [69] The FABQ contains two
subscales: one is related to general physical activity and the
other to work. [69]
Patients underwent a standardized history and physical examination. History included mechanism of injury, nature of
current symptoms, and prior episodes of LBP. Patients were
asked to rank sitting, standing, and walking as to which was
best and worst with respect to symptoms. The examination
included Waddells nonorganic signs. [68] Range of motion and
status change [49] in symptoms with single lumbar movements
were recorded. Supine straight-leg raise and prone hip rotation
range of motion were measured. Posteroanterior spring testing [43]
was performed for pain provocation and mobility at each
lumbar level. Mobility was judged as normal, hypomobile, or
hypermobile. Numerous special tests proposed to be diagnostic
of SI dysfunction were performed (see Appendix). The tests
were divided into three categories: position (tests assessing
symmetry of bony landmarks), provocation (tests to reproduce
symptoms), and mobility (tests assessing symmetry of pelvic
motion). [37] The examination was repeated on the first 55 subjects
by a second therapist blinded to the results of the first
examiner to determine the reliability of the physical examination
variables.
Figure 1
|
Treatment. Because response to treatment served as the reference
standard, all patients were treated with the same protocol
for two sessions. At the first session, the therapist performed a
manipulation technique with the patient supine. The therapist
stood opposite the side to be manipulated. The patient was
passively side-bent away from the therapist. The therapist passively
rotated the patient and then delivered a quick posterior
and inferior thrust through the anterior superior iliac spine
(Figure 1). The side to be manipulated was determined with the
following algorithm: first, the side of the positive standing flexion
test; if this test was negative, the side of tenderness during
sacral sulcus palpation was manipulated. If neither side was
tender, the side reported by the patient to be more symptomatic
was manipulated. If the patient was unable to identify a more
symptomatic side, the therapist flipped a coin to determine the
side. Although the manipulation was performed on one side
only, Cibulka et al [12] found changes in innominate tilt on both
sides of the pelvis after applying this technique. Therefore,
whereas the algorithm provided a consistent approach, it is
likely the manipulation affected bilateral SI regions.
After the manipulation, the therapist noted whether a cavitation
was heard or felt by the therapist or patient. If a cavitation
was experienced, the therapist proceeded to the other
treatment components. If no cavitation was produced, the patient
was repositioned, and the manipulation was attempted
again. If no cavitation was experienced again, the therapist
attempted to manipulate the opposite side. A maximum of two
attempts per side was permitted. If no cavitation was produced
after the fourth attempt, the therapist proceeded to the other
treatment components. Two additional treatment components
were included:
1) instruction in a supine pelvic tilt range of
motion exercise (the patient was instructed to perform 10 repetitions,
34 times daily; and
2) instruction to maintain usual
activity level within the limits of pain. [5]
The second treatment session occurred 24 days after the
first. Before the second session, each patient completed an
OSW questionnaire. Percentage improvement in OSW was calculated
(initial score final score)/initial score X 100). If improvement
was >50%, the patient was categorized as a success,
and study participation ended. If the patient showed
<50% improvement, the therapist repeated the examination
and the manipulation procedures. The third session occurred
24 days after the second. The patient again completed the
OSW, and the percentage improvement from the initial score
was calculated. If >50% improvement was noted, the patient
was categorized as a success. If improvement was ≤50%, the
patient was categorized as a nonsuccess. At this point, the patients
study participation ended, and further treatment was
administered as needed.
Data Analysis. Kappa coefficients were calculated to determine
the interrater reliability of the special tests for SI dysfunction.
Patients were dichotomized based on success or nonsuccess
with respect to the treatment. Success or nonsuccess was
then used as the reference standard. Individual variables from
the self-reports, history, and physical examination were tested
for their univariate association with the reference standard using
independent sample t tests for continuous variables and
χ2
tests for categorical variables. Variables with a significance
level of P < 0.15 were retained as potential prediction variables;
a more liberal significance level was chosen at this stage
to avoid excluding potential predictive variables. For continuous
variables with a significant univariate association, sensitivity
and specificity values were calculated for all possible cut-off
points and then plotted as a receiver operator characteristic
(ROC) curve. [31] The point on the curve nearest the upper lefthand
corner represents the value with the best diagnostic accuracy,
and this point was selected as the cut-off defining a positive
test. [18] Sensitivity, specificity, and positive likelihood ratios
(PLR) were calculated for all potential prediction variables. [57]
The PLR is calculated as sensitivity/(1 specificity) and indicates
the increase in the probability of success given a positive
test result. [58] A PLR of 1 indicates the test does nothing to alter
the probability of success, whereas PLR values >1 increase the
probability of success given a positive test result. According to
Jaeschke et al,
33 PLR values between 2.0 and 5.0 generate small
shifts in probability, values between 5.0 and 10.0 generate
moderate shifts, and values >10.0 generate large and often
conclusive shifts in probability. We chose to focus on the PLR
as opposed to the negative LR because we were attempting to
predict success with manipulation based on positive test results.
Potential prediction variables were entered into a stepwise
logistic regression equation to determine the most parsimonious
set of predictors for success using a multivariate
model. A significance of 0.05 was required to enter a variable
into the model and a significance of 0.10 was required to remove
it. Variables retained in the regression model were used to
develop a multivariate clinical prediction rule for classifying
patients as likely responders to manipulation.
Results
Figure 2
Table 1
Table 2
Table 3
Table 4
Table 5
Table 6
Table 7
|
Seventy-five patients entered the study. Four subjects
(5%) did not return after the first session and were not
included in the analysis. Two subjects left the study because
of personal or work-related circumstances. One
subject dropped out because of complications from an
ongoing episode of gastrointestinal distress, and one subject
failed to return for his final visit. Of the 71 patients
completing the study, 29 (41%) were female and 59
(83%) had a prior history of LBP. The mean age was
37.6 ± 10.6 years (range 1859 years). The mean OSW
score at baseline was 42.4 ± 11.7, and at study conclusion
25.1 ± 13.9. The mean percent improvement in
OSW over the study period was 41.0 ± 33.9% (range
-29.0100%). Thirty-two patients (45%) were classi-
fied as treatment successes, and 39 (55%) were nonsuccesses.
Twenty patients were successes after one manipulation
session, 12 after two sessions. The mean improvement
in OSW in the success group over the study period was 32.5
± 12.6 points, with a mean percent improvement of 73.2 ±
15.8%. In the nonsuccess group, the mean OSW improvement
was 6.2 ± 7.8 points, with a mean percent improvement
of 14.6 ± 18.2% (Figure 2).
Among self-reported variables (Table 1), the FABQ
work subscale, the presence of symptoms in the back
only, and symptoms distal to the knee were retained as
potential prediction variables. From the history (Table
2), duration of symptoms, increasing episode frequency,
and ranking standing as the worst position were retained.
Five variables were retained from the clinical examination
(Table 3): left and right hip internal rotation,
hypomobility and pain with lumbar spring testing, and
peripheralization with single lumbar movement testing.
The special tests for SI dysfunction along with the reliability
coefficients are presented in Table 4. As a group,
the provocation tests were more reliable with values
ranging from fair to substantial agreement. The Gillet
test was the only motion test to demonstrate at least
moderate agreement. The anterior superior iliac spine
and iliac crest in standing and the posterior superior iliac
spine symmetry in sitting were the only symmetry tests to
have at least fair agreement. Among the special tests for
SI dysfunction (Table 5), only the compression
distraction test was retained in the predictive model, although
positive findings were more common in the nonsuccess
group. Cut-off values for retained continuous
variables (duration of symptoms, FABQ work subscale,
left and right hip internal rotation) were obtained from
receiver operator characteristic curve analyses. Because
of their similarity, left and right hip internal rotations
were combined into a single variable. Cut-off scores and
accuracy statistics for retained variables were calculated
(Table 5). Among historical variables, duration of symptoms
<16 days was most predictive of success (PLR = 4.39).
The 11 potential prediction variables were entered
into the logistic regression. Five were retained in the final
model: duration of symptoms <16 days, at least one hip
with >35° of internal rotation, hypomobility with lumbar
spring testing, FABQ work subscale score <19, and
no symptoms distal to the knee (model χ2 = 48.5, df = 5, P < 0.001, Nagelkerke R2 = 0.67). These five variables were used to form the clinical prediction rule. Only six subjects (all in the success group) were positive for all five retained prediction variables at baseline (Table 6). Fourteen of 15 subjects with 4 of 5 variables present were in
the success group. Of subjects with two or fewer variables
present, 25 of 27 were in the nonsuccess group.
Accuracy statistics were calculated for each level of the
clinical prediction rule (Table 7). Based on the pretest
probability of success with manipulation found in this
study (45%), and the PLR values calculated, a subject
with four or more variables present at baseline increases
his or her probability of success with manipulation from
45% to 95%. If the criteria were changed to three or
more variables present, the probability of success was
only increased to 68%. If two or fewer variables were
present, the probability of success was virtually
unchanged.
Discussion
Clinicians who routinely use spinal manipulation have
encountered patients who experience a rapid, even dramatic
improvement as a result of one or two treatments,
whereas others change very little. The ability to accurately predict which patients will have which response a
priori would be immensely beneficial for clinical decision-making.
Similar to other studies, [21, 40, 41, 44] we were
unable to show acceptable accuracy for any individual
tests proposed to identify SI dysfunction. Furthermore,
we found that the reliability of these tests in a population
of individuals with LBP is less than optimal. As noted by
previous researchers, provocation tests as a whole are
more reliable tests than motion or symmetry tests. [9, 37]
However, by considering other variables and combining
findings, we were able to develop a clinical prediction
rule that may be useful for assisting clinicians in classifying
patients as likely to respond to this manipulation
technique.
The developed clinical prediction rule contains five
variables: duration of symptoms <16 days, at least one
hip with >35° of internal rotation, lumbar hypomobility,
no symptoms distal to the knee, and an FABQ work
score <19. These findings are generally consistent with
previous theories and research. Randomized trials have
suggested that patients with more acute symptoms respond
better to manipulation. [30, 42] Our results support
this hypothesis. Hip rotation range of motion discrepancies
have been reported in patients with LBP. [2, 14, 51] Previous
studies in patients with nonspecific LBP have
found greater external rotation than internal rotation. [2, 11, 51]
As a whole, patients in this study had greater
external than internal rotation; however, increased internal
rotation was associated with manipulation success. Manipulation is thought to be indicated in the presence
of hypomobility. Interestingly, although the technique
used in this study is described as affecting the SI region, it
was lumbar hypomobility that entered the prediction
model. This finding reinforces the idea that the manipulation
technique is not specific to the SI region but impacts
the lumbar spine as well. [7, 17, 29] Manipulation is
generally thought to be contraindicated in patients with
radiculopathy. [5] We excluded patients with signs of nerve
root compression. However, some patients with symptoms
distal to the knee were included, and these patients
tended not to succeed. Finally, the FABQ quantifies a
patients fear of pain and subsequent avoidance of activity. [69]
The FABQ work subscale has been previously correlated
with work loss and disability in patients with
chronic and acute LBP. [24, 35, 69] Our results suggest that
patients with high levels of fear-avoidance beliefs about
work activities are unlikely to respond to manipulation.
These individuals likely require an alternative treatment
approach. [15]
The usefulness of a clinical prediction rule for classifying
patients is best expressed using likelihood ratio
statistics. The PLR expresses the change in odds favoring
the outcome when the patient meets the prediction rules
criteria. [57] In our sample, 45% of subjects were successful
without any attempt at prediction. In other words, randomly
manipulating individuals with nonradicular LBP
may result in success about 45% of the time. Using a
criterion of at least 4 of 5 variables present at baseline
(PLR = 24.38), the probability of success is raised to
95%; therefore, these individuals should be manipulated.
If only three variables are present, the probability
increased to 68%, which is likely sufficient to warrant an
attempt at manipulation in these patients. When two or
fewer variables are present, the probability of success
changes little, and clinicians should consider alternative
treatments if such can be identified that may have a probability
of success >%45%.
An important consideration in the examination of diagnostic
tests is the reference standard against which
tests are judged. Previous studies of tests for SI dysfunction
have generally used immediate pain relief with SI
joint anesthetic injection. In our opinion, clinicians performing
these tests are not as interested in pathoanatomic
speculations (i.e., is the SI joint generating the
pain?) as they are in determining if the patient will respond
to a particular intervention. We therefore used a
reference standard representative of the desired outcome
of the tests (i.e., responding to manipulation). The use of
50% improvement on the OSW as the reference standard
was based on previous research involving the intervention
used in this study. In three previous studies, patients
thought to be matched to this intervention experienced
mean improvements in OSW scores from 57% to 83%,
whereas patients receiving unmatched interventions experienced
mean improvements ranging from 20% to
38% over a 14-week period. [16, 22, 23] We therefore
thought that requiring 50% improvement in the OSW
over a 24-day period would provide adequate distinction
between patients responding to the intervention and
those simply benefiting from the favorable natural history
of LBP.
The patients participating in this study should be representative
of patients seeking physical therapy services
in large metropolitan areas. The eight physical therapists
involved in the study had varying degrees of skills in
spinal manipulative therapy. However, the manipulation
technique employed is a standard technique used in
physical therapist education programs. Therefore, the
results should be generalizable to outpatient clinics treating
individuals with LBP.
A three-step process for developing and testing a clinical
prediction rule is recommended. [48] The first step is
developing the rule, the second step is validation, and the
third step is an assessment of the impact of the rule on
clinical behavior. The purpose of the present study was
to develop a clinical prediction rule that would identify
individuals with LBP who respond favorably to a specific
spinal manipulation. In the present study, only one manipulation
technique was used, and it is unknown
whether other techniques would provide similar results.
Validation of the proposed clinical prediction rule is the
purpose of an ongoing randomized controlled trial where
subjects meeting the prediction criteria receive either the
spinal manipulation technique or a competing therapy. Ultimately,
any clinical prediction rule must be shown to improve
outcomes and clinical decision-making before it can
be advocated for widespread use. [38, 48]
Key Points
Special tests purported to identify patients with low back pain who will respond
to manipulation
were largely unsuccessful in doing so.
The best univariate predictor of success with manipulation was the duration
of the current symptoms; more acute symptoms were more likely to
respond favorably.
Five variables were identified to form a clinical prediction rule for patients with
low back pain likely to respond favorably to spinal manipulation:
duration of symptoms <16 days,
FABQ work subscale score <19,
at least one hip with >35° of internal rotation range of motion,
hypomobility in the lumbar spine, and
no symptoms distal to the knee.
The presence of four of five variables in the prediction rule increased the
likelihood of success with manipulation from 45% to 95%.
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