With Conventional Physical Therapy for. Upper-Extremity Function in Patients Following. Stroke: A Research Overview and Meta-analysis. Background and ...
Research Report
Efficacy of Electromyographic Biofeedback Compared With Conventional Physical Therapy for Upper-Extremity Function in Patients Following Stroke: A Research Overview and Meta-analysis
Background and Purpose. The purpose of this study was to examine the eficacy of electmmyographic biofeedback compared with conventional pbsical therapyfor improving upper-extremityfunction in patients following a stmke. Subjects and Methods. A literature search was donefor the years 1976 to 1992. The selection criteria included single-blinded randomized control trials. Study quality was assessedjor nine criteria. For functional (disability index or stage of recovery) and impaimmt outcomes, meta-analyses were p e r j o m d o n o d d ratiosfor improvement versus n o improvement. Mann-Whitney U-Testprobability values were combined across studies. Results. Six studies were selected, and outcome data were obtained forfive studies. The common o d d ratio was 2.2for function and 1.1for impaimztmts in favor of biofeedback. The estimate of the number needed to treat to prevent a' nonresponder was 11for function and 22for impaimzents.None of the metaanalyses were statistically sign@cant. Conclustm and D&&on. The results dc) not conclusively indicate superiority of eitherform of therapy. Although there is a chance of Type I1 m r , the estimated size of the efict is small. Given this estimate of little or no dflerence, therapists need to consider cost, ease of application, and patient pr@erence when selecting these therapies. [MorelandJ Thomson M A E@acy of electmmyographic biofeedback compared with conventional physical therapyJi3r upper-extremityfunction in patients following stroke: a research overview and meta-analysis. Pbs Ther. 1994;74:534-547.1
Julie Moreland Mary Ann Thomson
Key Words: Cerebrovascular disorders;Electromyograpb; Feedback; Metaanalysis; Upper extremity, general.
Rehabilitation of the upper extremity in patients who have sustained a
stroke poses a major challenge to physical therapists. In a review of
J Moreland, BHSc(PT), is Research Coordinator, St Joseph's Hospital, and Clinical Lecturer. School of Occupational Therapy and Physiotherapy, McMaster University, Hamilton, Ontario, Canada. Address correspondence to Ms Moreland at Physiotherapy Depanment, St Joseph's Hospital, 50 Charlton Ave E, Hamilton, Ontario, Canada L8N 446. MA Thomson, BHSc(PT), is Education Manager, Chedoke-McMaster Hospitals, and Clinical Lecturer, School of Occupational Therapy and Physiotherapy, McMaster University. This research was supponed by a grant from the Hamilton District of the Ontario Physiotherapy as so cia ti or^
This overview was presenred in pan at the Canadian Physiotherapy Association Congress, June 1332
studies on upper-extremity recovery, Gowlandl stated that only 4% to 9% of patients regained normal function, 23% to 43% regained some useful function, and 16% to 28% did not have return of any voluntary movement in the upper limb. One technique used to improve upperextremity movement following stroke is electromyographic (EMG) biofeedback. Knowledge of its efficacy is important for decisions related to patient care and the utilization of limited rehabilitation resources.
This attick was submitted April 19, 1993, and was accepted December 7, 1993
Physical Therapy /Volume 74, Number 6/June 1994
534 / 23
Table 1. Critical Appraisal of Ret~iewArticles o n the Effectiveness of Electrom.yographic Feedback for Stroke Rehabilitation
Mar~uk,~
De Weerdt and Harrison,'
Marcer,=
lnce et al,a
1983
lnce et al," 1985
1985
1986
1986
1987
Review
Review
Position
Review
Textbook
Review
Search methods reported
No
No
No
Partially
No
No
Search comprehensive
Cannot tell
No
Cannot tell
Cannot tell
Wolf,3
Type of article
No
Cannot tell
Inclusion cr~teria reported
No
No
No
No
No
No
Bias avoided
Cannot tell
Cannot tell
Cannot tell
Cannot tell
Cannot tell
Cannot tell
Validity criteria reported
Yes
No
No
Yes
No
No
Validity assessed appropriately
Yes
No
No
Yes
Partially
Partially
No
No
No
No
Yes
No
No
Yes
Partially
Partially
Methods to combine studies Findings combined appropriately Conclusions supported by data
Partially
The following question was addressed in this research overview: In patients following a stroke, is EMG biofeedback efficacious for improving upperextremity function compared with conventional physical therapy? In this context, electromyographic biofeedback was defined as the use of instrumentation applied to the patient's muscle(s) with external electrodes to capture motor unit electrical potentials. The patient is asked to activate or lessen the activity of the muscle(s). The instrumentation converts the potentials into visual or audio information for the patient and the therapist. It is usually used to augment desired muscle action or to decrease unwanted muscle activity. There is no standardized approach. The question was focused on functional outcomes and the comparison with conventional therapy in order to provide information relevant to clinical decision making. For the purposes of this study, functional outcomes was defined as outcomes related to movement as opposed to physiological variables.
Ratlonale for This Overview The investigation of EMG biofeedback therapy for patients following stroke has progressed from case studies to case series to comparison group studies. Interspersed with these studies, literature reviews have been published. A systematic search for reviews of EMG biofeedback for patients following stroke was done from 1981 forward. Six relevant review articles were located. To evaluate these reviews, the criteria developed by Oxman and Guyatt2 were applied. The results are summarized in Table 1. Wolf-?reviewed biofeedback studies using validity criteria. He concluded that the majority of studies supported the use of EMG biofeedback in addition to exercise. Ince et a14 primarily discussed early case studies in their review. The authors concluded that the early studies demonstrated that EMG biofeedback is superior to "physical therapy" and that the later comparison studies have not concurred with this finding. The possibility of Type I1 error in the comparison studies was not discussed. In a position paper, Marzuk5 summarized the
methodologic difficulties in assessing the efficacy of EMG biofeedback. Studies were reported but not appraised, nor was the rationale for their inclusion explained. The possibility of Type I1 error was not discussed for the control studies with nonsignificant findings. Marce6 critically appraised the methodology and analysis of EMG biofeedback trials. He concluded that all trials demonstrated clinically significant gains in patients with chronic conditions who would be least likely to improve but that the methodology was inadequate for demonstrating a specific effect of biofeedback. De Weerdt and Harrison7 conducted an extensive review with critical appraisal of the included studies. selected validity criteria for the studies were assessed, and they concluded that the evidence was insufficient to answer the question of efficacy. They noted that in the more scientifically rigorous studies, the small sample sizes increased the risk of Type I1 error. In a review by Ince et al,%o studies were found to be definitive due to various problems with study design, presentation, and analysis. The
Physical Therapy /Volume 74, Number 6/June 1994
authors suggested that future research should concentrate on functional activities in more basic wellcontrolled studies. Among the review papers, some consistencies were evident. Generally, it was concluded that the early uncontrolled studies supported the finding of efficacy and that the later group studies did not. In none of the reviews were selection criteria provided or a quantitative analysis conducted. The possibility of Type I1 error also was not evaluated. We therefore conducted a systematic research overview and meta-analysis.With respect to Type I1 error, meta-analysis is useful when individual sample sizes are too small to detect a statistically significant effect.
Methods Identification of Relevant Studies Because the first controlled study identified by De Weerdt and Harrison7 was published in 1976, we confined our search to the period 1976 to 1992. AlEDLINE was searched using the key words "electromyography," "biofeedback," and "cerebrovascular disorders." The key words "biofeedback" and "cerebral vascular accident" were used to search the CINAHL database. The Dissertation Abstracts International database was explored using the search words "electromyography" and "biofeedback." EXCERPTA MEDICA was reviewed manually, and a follow-up of key references was done via SCISEARCH. In an attempt to identify any unpublished studies, the authors of relevant articles were contacted by mail. The search was limited to English-language publications. Each investigator reviewed all located references (titles and abstracts, if available) independently for relevance using four criteria. The reference lists within these reports and review articles were also evaluated in the same way. Any study deemed to be relevant by either author was included at this stage.
Selection of Studies
4. Random allocation of therapists to patients.
Relevant studies were assessed independently by each author for the following selection criteria: 1. Population: Adults poststroke. 2. Intervention: Treatment g r o u p EMG biofeedback alone or with conventional physical therapy; control group-conventional physical therapy (exclusion of feedback devices or functional electrical stimulation).
3. Outcomes: Any functional measure of the upper extremity, including upper-extremity function testing, stage of motor recovery, range of motion, and muscle strength.
4. Methodology: Randomized control trials with blinded outcome assessment. Interobserver reliability of these criteria was determined using the weighted Kappa statistic. Disagreements were resolved by consensus. Bias was minimized by the fact that one investigator does not treat patients who have had strokes and had no previous knowledge of the literature.
Validity Assessment of the Selected Studies To judge the degree of confidence that can be placed on the conclusions and to identify possible explanations for differences in study results, the selected studies were evaluated using nine methodologic indicators: 1. Follow-up of 95% (excluding deaths). 2. Treatment and control group comparability (within 10% for age, time poststroke, receptive communication, sensation, and baseline measures of outcome variables).
5. Monitoring of treatment protocols to prevent bias. 6. Provision of placebo biofeedback to the control group. 7. Avoidance of contamination and cointervention. 8. Use of reliable and valid outcome measures. 9. Analysis of withdrawals in the group to which they were randomly allocated. Both investigators independently applied these criteria, and the interobserver agreement for each criterion was determined using the Kappa statistic. Disagreements were resolved by discussion.
Data Ortraction Information was abstracted from each study regarding the patients and facilities, the interventions, the sample size, the number of dropouts, and the results. Authors of the studies were contacted to obtain missing information.
Data Analysis The goal of the data analysis was to integrate the results of the studies to obtain a representative estimate of the magnitude of the effect of EMG biofeedback and to explore the influence of mediating factors. In order to compare studies and combine the results of studies, several options exist. If the data are normally distributed, an effect size (difference between the means divided by the pooled standard deviation) can be calculated for each study.9 Alternatively, an odds ratiolo can be calculated if the data are available and if a reasonable cutoff point for success and failure can be defined.
3. Provision of equal time and attention to both groups.
Physical Therapy/Volume 74, Number 6/June 1994
The odds ratio is formed from nominal data (eg, improved versus not improved, EMG biofeedback versus
conventional therapy). It estimates the strength of association between the treatment condition and the response to treatment. If the odds ratio is greater than 1.00,this indicates a more favorable response to EMG biofeedback than to conventional therapy. For example, the patients are "x" times more likely to improve. Although dichotomizing the data results in a loss of information, such dichotomization is a valuable alternative when data cannot be analyzed with parametric statistics. It also simplifies the results and conclusions to a clinical level when differences in measurement points lack clear meaning. Plots of the data revealed that some distributions were highly skewed. We therefore decided to use odds ratios to describe each study and to combine the results. Because some of the outcome measures were imbalanced at baseline, the change score (posttreatment score minus pretreatment score) was used. Before any analyses were performed, improvement versus no improvement was selected as the cutoff point for success o r failure. Analyses were done using the OR2 x 2 x K programll to obtain the individual odds ratios and their 95% confidence intervals and the MantelHaenszel common odds ratios and their 95% confidence intervals (Cornfield method).12,13To test for homogeneity of the odds ratios, the Breslow-Day methodl2J3 was selected. To obtain an indication of the magnitude of the effect and its clinical significance, the odds ratios were used to estimate the proportion of failures (no improvement) expected in the treatment group (PJ . Using the proportion of failures in the control group from representative studies (PJ, the number needed to treat to prevent a failure was calculated from the equation IF',-P,.14 An example of an odds ratio calculation and number needed to treat is provided in the Appendix.
done for each study. The one-tailed probability values were then combined using the Stouffer method15 on Meta-analysis Programs, Version 5.1.16 These analyses were done for two outcome constructs: upper-extremity function and upper-extremity impairment. Outcomes measuring upperextremity function and stage of motor recovery as delineated by Brunnstrom17were used to define the function construct. Impairment outcome measures were deemed to represent the impairment construct. Impairments were those outcomes that are substrates used to form movements such as muscle strength o r range of motion. In cases where two outcomes were present from one study for a construct, the outcomes were combined to provide one input into the common odds ratio. For the combination of probability values, one outcome was randomly selected to represent that study in the meta-analysis.
A Priori Hypotheses Regarding Sources of Heterogeneity Before analyzing the results, we constructed a list of possible sources of heterogeneity. We hypothesized that differences in odds ratios may be due to the methodology, which included treatment monitoring versus no monitoring; treatment consisting of biofeedback combined with conventional therapy versus biofeedback alone; placebo feedback in the control maneuver versus no placebo; and acute (95% assessed for outcome measurcs.
one-tailed probability values are also given in Tables 4 and 5. None of the
two-tailed Mann-Whitney tests were significant at the .05 level.
TBble 4. Function Outcomes: Sample Size
(w, Odds Ratios, and Mann-Wbilney
U-Test One-tailed Probability Values
Study and Outcomes
N
Odds Ratlos (95% Contldence Intervals)
P
Crow et al,le 1989 Action Research Arm Test
40
3.50 (0.79-1 6.26)
.05
1.89 (0.31-1 2.33)
.09
29
4.66 (0.1S999.99)
.62
18
1.OO (0.09-10.67)
.27
37
2.13 (0.27-20.05)
.36
11
1.25 (0.02-69.48)
.21
Brunnstrom-Fugl-Meyer Test Basmajian et al,19 1987 Upper-Extremity Function Test Prevo et al,zo 1982 Brunnstrom-Fugl-Meyer synergies Basmajian et al,zl 1982 Upper-Extremity Function Test Smith,Zs 1979 Brunnstrom assessment Mantel-Haenszel common odds ratio
135
2.16 (0.82-5.79)
I l e meta-analysis results for the function and impairment constructs are also summarized in Tables 4 and 5. For both constructs, the statistical tests of association were not significant (P>.05). The meta-analyses for probabilities were also not significant. Functional outcome measures included the UEFT, the Action Research Arm Test, and Brunnstrom staging. The common odds ratio was 2.16 (0.82-5.79). Given the proportion of responders in the control group (0.21) in the study by Basmajian et al,*l the number of patients needed to treat with biofeedback to prevent one nonresponder is 10. Grip strength, elbow flexion force, and finger oscillation formed the impairment construct, and the common odds ratio was 1.29 (range=0.43-3.99). Using the proportion of nonresponders (0.26) for grip strength,lHthe number of patients needed to treat would be 22.
Test of significance (P=.09) Test for homogeneity (P=.80) Meta-analys~s for probabilities
135
.12
The tests for homogeneity for each meta-analysis were not significant, indicating that the variability in odds
Physical Therapy /Volume 74, Number 6/June 1994
Table 5. Impairment Outcomes: Sample Size
(w, Odds Ratios, and Mann-Whitney
U-Test One-tailed Probability Values
Study and Outcomes
N
Odds Ratios (95% Confldence Intervals)
P
29
0.53 (0.08-3.38)
.64
18
2.67 (0.13-97.19)
.37
1.79 (0.29-1 1.90)
.40
2.92 (0.51-18.44)
.54
Basmajian et aI,l9 1987 Finger oscillation test Prevo et aLZo1982 Elbow flexion force Basmajian et aLnl 1982 Grip strength
37
Pinch strength Mantel-Haenszel common odds ratio
84
1.29 (0.43-3.99)
Test of significance (P=.62) Test for homogeneity (P=.73) Meta-analysis for probabilities
84
ratios among the studies was not greater than what was expected by chance. With a small number of studies, however, the power of this test is low.14We therefore performed sensitivity analyses as per the a priori hypotheses. The results of these analyses are presented in Table 6. None were statistically significant. The study by Basmajian et all9 was classified as an acute study because only 3 of the 29 patients were more than 6 months poststroke. For the functional outcomes, the common odds ratio for the studies with patients less than 6 months poststroke was 2.9.
0.01
0.1
.46
To determine the magnitude of response for these subgroups (sensitivity analyses), the number of patients needed to treat was calculated as shown in the Appendix. The study by Crow et a1,18 in which patients were less than 8 weeks poststroke, was used to estimate the proportion of patients whose functional status did not change with conventional therapy (0.70). Given this estimate, the number of patients needed to treat with biofeedback to prevent one nonresponder is four. For the studies in which biofeedback was combined with conventional therapy, the odds ratio was 2.5 and the number of patients needed to treat is nine, given a
0.5
1
2
10
100
Crow et al," 1989 Basmajian et a1,19 1987 Prevo et alFO1982 Basmajian et a1," 1982
nonresponder proportion of 0.21. For the impairment outcome in patients with long-standing stroke,20the number needed to treat is seven for elbow flexion force. One studyz1measured hand impairments and combined conventional therapy with biofeedback. In this study, the estimated number of patients needed to treat is eight to prevent a nonresponder for grip strength.
Discussion A number of methodologic issues exist when conducting meta-analyses. These issues include agreement on the predefined criteria, statistical analysis, and the nature of the variables that are being pooled in the analysis. Agreement on the selection criteria was high, but interobserver agreement for the validity criteria ranged from poor to good. Disagreement primarily occurred where judgment was required to decide whether a criterion was not met or was possibly done but not reported. To resolve this problem, we decided to score these criteria as possibly achieved. The disagreements we noted point out the importance of having more than one evaluator assess the internal validity of studies that are included in a research overview. A common criticism of meta-analysis is that studies are combined in which different populations, interventions, and outcomes are represented. Because efficacy may be related to these characteristics, combining all trials may underestimate or overestimate the intervention effect for certain groups. Among the studies, the biofeedback protocols we considered were similar for duration and frequency. There were differences in the control treatments; however, randomized trials comparing different forms of conventional physical therapy have not demonstrated any clinically important differences.3031
Smith,231979 Common odds ratio
Figure I. Line graph of odds ratios with 95% confidence internal (log scale) for function outcomes. Physical 'Therapy/Volume 74, Number 6/June 1994
For the upper-extremity function meta-analysis, the outcomes of upperextremity function testing were combined with those of Brunnstrom staging. We believe this approach is
yield interval scales and surveys to determine clinically significant differences.
Basmajian et a1,19 1987 Basmajian et aI,*' 1982 Prevo et alFO1982 Common odds ratio
4:-
Figure 2. Line graph of odds ratios with 95% confidence interval (log scale) for impairment outcomes. justified based on the study of De Weerdt et al,32in which a correlation of .91 was found between the Action Research Arm Test and the Brunnstrom-Fugl-Meyer evaluation. Furthermore, the Action Research Arm Test was developed directly from the UEFT,26thus making these two tests comparable. The measurements that formed the impairment construct are not directly comparable. Two represent force measurements, and one is a coordination measure. The results shown in Table 5 suggest that EMG biofeedback may b e more effective for strengthening than coordination.
-
The nature of the data distributions determined the choice of statistical analysis. Because effect sizes based on standard deviation units would not be meaningful for highly skewed data, a nonparametric measure was chosen. The choice of improvement versus no improvement as a cutoff point has clinical relevance, although it is not ideal because it disregards the amount of change that occurred. Choosing clinically important values is difficult because conceptualizing the performance of ordinal measures is a challenge (when ordinal scores are added, similar resulting scores d o not imply the same amount of change). In the future, those who develop measures should consider techniques that
Table 6. Sensitivip Analyses Mantel-Haenszel Common Odds Ratios (OR) and Tests of Significance
Study Subgroups
Functlon Construct (Flve Studles)
lmpalrment Construct (Three Studles)
Patients 6 months poststroke20,23 Biofeedback combined with conventional therapy18,Zl Biofeedback alonel9.20.23
OR=0.8
Placebo in control groupla
None of the studies included placebo intervention
P=.80
No placebo in control gr0up~~-21.23 Treatment monitored19-21
Treatment not monitoredl8,23
30 / 541
All studies had treatment monitoring
The purpose of this overview was to obtain an estimate of the effect of EMG biofeedback compared with conventional therapy in order to guide clinical decision making. Generalization of the findings is limited to biofeedback training using recruitment and inhibition strategies for the upper extremity. Because all of the analyses were statistically nonsignificant, the studies to date d o not conclusively demonstrate that EMG bio-
Physical Therapy /Volume 74, Number 6Aune 1994
feedback is superior to conventional therapy. Although there is a possibility of Type 11 error, we are unaware of any method to calculate power for a meta-analysis to confirm the presence of Type I1 error. Overall, the size of the effect, as indicated by the number of patients needed to treat, is small. This interpretation is limited because it assumes that change versus no change is the only outcome of interest without consideration of the magnitude of improvement. Two factors, however, support the conclusion of a small effect. One is that the results of the meta-analyses for probability values (based on the Mann-Whitney test, which uses the magnitudes of the data) were greater than those of the significance tests for the common odds ratios. This finding indicates that the odds ratio analyses were anticonservative (more in favor of biofeedback than warranted by the magnitude of the change scores). A second factor is that a post hoc parametric meta-analysis of the functional data for those who did change showed an effect size of -0.02 standard deviation. This value corresponds to one point on the UEFT in favor of conventional therapy and suggests that those patients who respond to treatment d o equally well in either group. Our findings should not be extrapolated, however, to other forms of biofeedback (eg, positional) or to the lower extremity. The sensitivity analysis of studies that examined patients who were less than 6 months poststroke suggests that EMG biofeedback may be worthwhile in this group. The sensitivity analyses should be viewed as exploratory because the factors are confounded within the studies and because there was multiple significance testing on each construct. All of the sensitivity analyses had wide and overlapping confidence intervals, which precluded any definitive conclusions. The seemingly anomalous finding of an odds ratio of 2.7 for impairment in the chronic subgroup occurred because this finding represented one studyz0 with a sample size of 17. There was one nonresponder in the experimen-
Physical Therapy /Volume 74, Number
tal group, and there were two nonresponders in the control group. How do these results compare with the conclusions of the individual studies? With respect to functional outcomes, two of the selected studies concluded that biofeedback was superior to conventional therapy. Smith23 reached this conclusion based on the differences between groups; however, a statistical analysis was not done. Crow et all8 based their conclusions on posttreatment scores without adjustment for baseline differences. In their study, one-tailed tests were significant for the Action Research Arm Test and the Brunnstrom-Fugl-Meyer Test, although the authors did not comment on the clinical importance of the differences. A follow-up done 6 weeks later showed no statistically significant differences. Basmajian et all9 also performed follow-up measures at 9 months and found no statistically significant difference between the groups. In this study, the mean UEFT scores were higher for the conventional group at both posttest and follow-up. In view of the findings, further research needs to be done. Motor learning research in nondisabled subjects indicates that constant, precise feedback is inferior to less frequent, delayed or bandwidth feedback.34 This is compelling evidence that the scheduling of EMG biofeedback training needs to be studied in patient populations. Another area for study at a basic level is the relative effectiveness of biofeedback (motor unit potentials) compared with overt feedback or knowledge of results. Interestingly, two studies that compared simulated feedback with actual feedback concluded that biofeedback was nonspe~ i f i c . ~ ~Once , j 5 these issues are sorted out, clinical studies that examine functional outcomes in homogeneous groups would be appropriate. Our findings suggest that studies should evaluate acute and chronic groups separately. For clinical studies, measures need to be selected or developed such that the clinical importance of differences can be readily evaluated.
Conclusions The purpose of this overview and meta-analysis was to determine whether there is conclusive evidence regarding the use of EMG biofeedback for improving upper-extremity function in adults who have had a stroke. Evidence was sought that compared EMG feedback alone or combined with conventional therapy with conventional treatment. Despite examining a group of rigorous studies using techniques that incorporate the total number of subjects, statistically significant differences were not found. The estimated size of the effect was small; therefore, we recommend that therapists consider factors such as cost, ease of application, and patient preference when deciding between the two forms of treatment. Therapists may wish to reserve this technique for those patients who do not respond to conventional therapy. Acknowledgments
We thank the investigators, who responded to our requests for information. In particular, we thank Dr N Lincoln, Professor Carolyn Gowland, Ms Janina John, and Dr A Prevo for graciously providing us with their data. References 1 Gowland C. Management of hemiplegic upper limb. In: Brandstater ME, Basmajian y, eds. Stroke Rehabilitation. Baltimore, Md: Williams & Wilkins; 1987:217-245. 2 Oxman AD, Guyatt GH. Guidelines for reading literature reviews. Can Med &ocJ 1988; 138:697-703. 3 Wolf SL. Electromyographic biofeedback applications to stroke patients: a critical review. Phys Ther 1983;63:1448-1455. 4 Ince LP, Leon MS, Christidis D. EMG biofeedback for improvement of upper extremity function: a critical review of the literature. Physiotherapy Canada. 1985;37:12-17. 5 Marzuk PM. Biofeedback for neuromuscular disorders. Health and Public Policy Committee, American College of Physicians. Ann Intern Med 1985;102:854858. 6 Marcer D. Biofeedback and Related Therapies in Clinical Practice. London, England: Croom Helm; 1986:145-159. 7 De Weerdt WJG, Harrison MA The efficacy of electromyographic feedback for stroke patients: a critical review of the main literature. Physiotherapy. 1986;72:108-1 18.
Appendix. Example of Odds Ratio Calculation and Number of Patients Needed to Treat The odds ratio is calculated from a 2 x 2 table. The following are some sample data: Treatment group change scores for each subject: -1,0,0,0,2,2,4,4,5,6,10,15
Control group change scores for each subject: -1,-1,0,0,0,0,0,3,3,4,8,19 For a given cutoff point, counts are placed in the table. In the example below, the cutoff point is improved versus not improved. From the data above, the following table is constructed:
Improved
Not Improved
Treatment group
8 (a)
4 (b)
Control group
5 (c)
7 (d)
The odds ratio is calculated as: (a)(d)/(b)(c)=2.8 To determine the number of patients needed to treat to prevent a nonresponder, the following equation is used: n=l/proportion control-proportion treatment In this example, the proportion of nonresponders in the control group is 7/12=0.58 If one believes that the best estimate of the odds ratio is, for example. 2.2, and because we know the number in cell d is 0.58 or 58 of 100 cases, the corresponding proportion of nonresponders in the treatment group can be calculated in the following way:
Improved
Not Improved
Treatment group Control group There are two unknowns and two equations: 58 (a)/42 (b)=2.2 and a+b=100 Solving for both: a=61.4 b=38.6 Therefore, the proportion of nonresponders in the treatment group is 0.386. Substituting this into the equation above for n: The number needed to treat=1/(0.58-0.386)=5.
8 Ince LP, Leon MS, Christidis D. EMG biofeedback with the upper extremity: a critical review of experimental foundation of clinical treatment with the disabled. Rehabilitation Pychology. 1987;32:77-91. 9 Hedges I.V, Olkin I. Statistical Methods for .Vela-analysis. Orlando, Fla: Academic Press Inc, 1985. 1 0 Boisscl JP, Blanchard J, Panak E, et al. Considerations for the meta-analysis of randomized clinical trials: summary of a panel discussion. Controlled Clin Trials. 1989;10:254-281. 11 Julian JA. OR2x2xK Version 1.0. Hamilton, Ontario, Canada: McMaster University; 1988. 12 Julian JA. Guide to OR2x2xy Version 1.0. Hamilton, Ontario, Canada: McMaster University; 1988.
1 3 Oxman AD. Meta-analysis in primary care: theory and practice. In: Tudiver F, Bass MJ, Dunn EV, et al, eds. Asseming Interventions: Traditional and Innovative Methods. Newbury Park, Calif: Sage Publications Inc; 1992:191-207. 1 4 L'Abbe KA, Detsky AS, O'Rourke K. Metaanalysis in clinical research. Ann Intern Med. 1987;107:224-233. 1 5 Rosenthal R. Meta-analytical Procedures for Social Research. Newbury Park, Calif: Sage Publications Inc; 1984. 1 6 Schwarzer R. Meta-analysis Program, Version 5.1. Berlin, Federal Republic of Germany: Free University of Berlin; 1989. 17 Brunnstriim S. Movement Therapy in Hemiplegia. New York, NY: Harper & Row; 1970. 18 Crow JL, Lincoln NB, Nouri FM, De Weerdt WJG. The effectiveness of EMG biofeedback in
the treatment of arm function after stroke. Int Disabil Studies. 1989;11:155-160. 19 Basmajian JV, Gowland CA, Finlayson AJ, et al. Stroke treatment: comparison of integrated behavioral-physical therapy vs traditional physical therapy programs. Arch Phvs .Wed Rehabil. 1987;68:267-272, 20 Prevo AJH, Visser SL, Vogelaar TW. Effect of EMG feedback o n paretic muscles and abnormal co-contraction in the hemiplegic arm, compared with conventional physical therapy. Scand J Rehabil Med. 1982;14:121-131. 21 Basmajian JV, Gowland CA, Brandstater ME, et al. EMG feedback treatment of upper limb in hemiplegic stroke patients: a pilot study. Arch Phys Med Rehabil. 1982;63:613-616. 22 Hurd WW, Pegram V, Nepomuceno C. Comparison of actual and simulated EMG biofeedback in the treatment of hemiplegic patients. Am JPhys Med. 1980;59:73432. 2 3 Smith KN. Biofeedback in strokes. Australian Journal of Physiotherapy. 1979;25:155161. 2 4 Mroczek N, Halpern D, McIlugh R. Electromyographic feedback and physical therapy for neuromuscular retraining in hemiplegia. Arch Phys Med Rehabil. 1978;59:25%267. 25 John J. Failure of electrical myofeedback to augment the effects of physiotherapy in stroke. Int J Rehabil Res. 1986;9:3545. 26 Lyle RC. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. In! J Rehabil Res. 1981;4:483-492. 27 Fugl-Meyer AR, Jaasko L, Leymann I, et al. The post-stroke hemiplegic patient, I: a method for evaluation of physical performance. Scand J Rehabil Med 1975;7:13-31. 2 8 Carroll D. Quantitative test of upper extremity function. J Chronic Dis. 1965;18:479491. 2 9 Reitan RM, Davison LA. Clinical Neuropqchology: Current Status and Applications. Washington, DC: Winston; 1974. 3 0 Wagenaar RC, Meijer OG, van Wieringen PCW, e t al. The functional recovery of stroke: a comparison between neuro-developmental treatment and the BrunnstrOm method. Scand J Rehabil Med. 1990;22:1-8. 3 1 Ernst E. A review of stroke rehabilitation and physiotherapy. Stroke. 1990;21:1081-1085. 32 De Weerdt WJG, Harrison MA. Measuring recovery of arm-hand function in stroke patients: a comparison of the BrunnstrBm-Fuglhleyer test and Action Research Arm Test. Physiotherapy Canada. 1985;37:65-70. 3 3 Wolf SL, Baker MP, Kelly JL. EMG biofeedback in stroke: effect of patient characteristics. Arch Phys Med Rehabil 1979;60:96-102. 34 Winstein CJ. Knowledge of results and motor learning: implications for physical therapy. Phys Ther. 1991;71:140-149. 3 5 Lee KH, Hill E, Johnston R, Smiehorowski T. Myofeedback for muscle retraining in hemiplegic patients. Arch Phys Med Rehabil. 1976; 57:58%591.
Physical 'I'herapy /Volume 74, Number @June 1994
