Predicting prosthetic rehabilitation outcome in lower limb amputee patients with the functional independence measure

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Predicting Prosthetic Rehabilitation Outcome in Lower Limb Amputee Patients With the Functional Independence Measure Eric Chung-Ching Leung, MBBS, Perry Joel Rush, MD, Michael Devlin, MD ABSTRACT. Leung EC-C, Rush PJ, Devlin M. Predicting prosthetic rehabilitation outcome in lower limb amputee patients with the Functional Independence Measure. Arch Phys Med Rehabi! 1996;77:605-8. Objective: To determine the value of the Functional Independence Measure (FIM) score as a prognostic indicator for prosthetic use in the lower limb amputee patient. Design: Cohort study of 41 patients with lower limb amputations. Setting: University hospital rehabilitation unit. Main Outcome Measures: FIM motor subscore and Houghton Scale for prosthetic use. Results: FIM score on admission did not correlate with prosthetic use as measured by the Houghton Scale; however, FIM motor subscore at discharge did. Conclusion: The admission FIM score is not useful in predicting successful prosthetic rehabilitation in lower extremity amputee patients. Only the motor subscore at discharge correlates with the use of prosthesis.

© 1996 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation EDICAL CARE required by people with chronic disabilities is a major component of health care expenditures. With the issue of resource allocation an ongoing concern in medicine, subsets of patients who will benefit most from medical intervention should be identified. With regard to the rehabilitation of amputee patients, it is desirable to predict which patients will benefit from prosthetic fitting. The major goal of rehabilitation is to improve functional ability, and it is important to be able to measure this. However, there is no universally agreed-upon quantitative measurement tool. Forty varieties of such tools have been reported as having been used or still in use today, 2 including the Functional Independent Measure (FIM). 3 The FIM was developed in 1983 as part of the Uniform Data System. Only two studies have reported on the use of the FIM as a prognostic tool in the rehabilitation of amputee patients.4'5 These two studies reported only the general rehabilitation outcome in terms of gain of FIM score and length of stay. Neither, however, specifically addressed the prosthetic use by the patients. This study was undertaken to

M

From the Division of Physiatry, Department of Medicine, University of Toronto, and the Department of Rehabilitation Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada. Submitted for publication August 31, 1995. Accepted in revised form November 30, 1995. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors or upon any organization with which the authors are affiliated. Reprint requests to Michael Devlin, MD, Assistant Professor, Department of Rehabilitation Medicine, Mount Sinai Hospital, Suite 1160, 600 University Avenue, Toronto, Ontario M5G 1X5 Canada. © 1996 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation 0003-9993/96/7706-366753.00/0

determine the FIM's effectiveness as a prognostic indicator of prosthetic use in amputee patients. The FIM is reliable and valid, and has low interobserver variability.3'~ It has 18 items grouped into 6 main areas: self care, sphincter control, mobility, locomotion, communication and social cognition. Each item is rated on a 7-point scale, representing major changes in the level of care, with " 1 " being completely dependent and " 7 " being completely independent in performing the activity in question. The FIM has been used in our institution to objectively monitor outcome of patients admitted to a 40-bed general rehabilitation unit. Admission and discharge FIM data have been gathered on all patients.

METHODS From March 1993 to June 1994, we assessed 41 consecutive admissions of amputee patients to our rehabilitation unit. The pattern of practice in our community is that all amputee patients are admitted for preprosthetic and prosthetic rehabilitation. The FIlM was administered to each patient within 48 hours of admission, and was also administered on discharge. Descriptive statistics of all patients were then collected, using the 18 items on the Uniform Data Entry for Medical Rehabilitation (UDS) form. The data were entered on a Microsoft Excel template and analyzed using the SAS Statistic package version 6.04. Our study assessed the FIM score only on the first admission and last discharge during the inpatient hospitalization period. Patients with more than one admission during the study period were assessed using their initial F1M score on admission and their latest FIM scores before discharge. The difference in the two FIM scores (AFIM), served as an analysis parameter in our study. In the most recent version of FIM, 3 the 18 items that make up the whole FIM score have been subdivided into a motor snbscore and a cognitive subscore. To evaluate the particular skill measured by the FIM that specifically related directly to ambulation, we took the motor subscore as another analysis parameter. We hypothesized that for nontranmatic lower limb amputation, the degree of impairment, as well as the subsequent improvement, would be uniformly greater in all patients in the area of functionality measured by the motor subseore. To assess the prosthetic use by the patients, we used the Houghton Scale7 (Appendix 1), which measures the daily use of the prosthesis by patients. A score of 9 or more is defined as successful prosthetic rehabilitation. Patients were divided into 2 groups according to the Houghton score, one group with a Houghton score of ->9 (defined as success of prosthetic rehabilitation) and a second group with a score of < 9 (defined as failure of prosthetic rehabilitation). The Houghton score was administered to the patient after discharge by telephone interview. The time from discharge to telephone interview varied from 3 months to 1 year.

Analysis The Houghton score served as the final outcome measure in our study. The following variables were examined for any

Arch Phys Med Rehabil Vo! 77, June 1996

PREDICTING PROSTHETIC OUTCOME, Leung

606

Table 1: Characteristic of 41 Patients With Lower Limb Amputation Total (Total = 33)

Houghton Scale ->9 (T = 21)

7 26

3 18

4 8

O 8

6 6 12 4 5

4 3 9 2 3

2 3 3 2 2

2 O 2 4 0

8 24 1

4 16 1

4 8 0

2 3 3 1

Women Men Age < 5Oyr 50 to 59yr 60 to 69yr 70 to 79yr 80 to 89yr Amputation Above-knee Below-knee Bilateral Comorbidity g

1 2 ->3 Average motor FIM Admission Discharge Average total FIM Admission Discharge Length of stay (days)

5

5

O

6

1

1

13 8

8 2

5 6

3 3

72 81

74 84

70 78

60 69

107 116 45

109 119 39

104 113 50

95 104 53

RESULTS Demographics Characteristics of the patient population are described in table 1. Of the 41 patients admitted, 2 were lost at follow-up and 6 had died by the time of telephone interview; all 8 were excluded from the study. Four patients were not fitted with a prosthesis on discharge and were included in the failure group (Houghton score of <9). Medical Condition Variables Lower extremity amputations in 23 patients were due to peripheral vascular disease; neoplasms resulted in amputations in 10 patients. Six of the 8 patients lost to follow-up had peripheral vascular disease and 2 had neoplasms. Comorbidities were common in these patients, with 26 having at least one additional chronic disease, including diabetes mellims, hypertension, coronary artery disease, and degenerative joint disease (table 2). Thirty-two patients had one admission and 1 had 2 admissions. The mean length of stay was 45 days.

2 -->3

Patients (n)

Mean LOS (days)

5 7 13 8

36 38 46 62

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Functional Outcome The mean admission FIM score for all patients was 107. The difference between admission and discharge FIM score was 9 (p < .0001). Patients were divided into 2 groups according to the Houghton score (table 2). For the motor F1M subscores, there was a significant difference in the discharge motor subscore between the successful and failed group (p = .0015). There was, however, no difference in the admission motor subscore (p = .42) and the gain in the motor subscore between the 2 groups (p = .18) (fig 1). There was no correlation between the Amotor subscore and the Houghton score (r = .18, p = .29). The Dmotor subscore, however, correlated with the Houghton score (r = .58, p = .0022). Level of amputation appears to play a significant role in determining prosthetic outcome. Thirty-three percent of patients in the failure group had above-knee amputations, compared to 20% of patients in the successful group. Patients with aboveknee amputation were hospitalized longer than below-knee amputee patients by a mean of 10 days. Age does not appear to be a significant factor between the 2 groups (p > .05). 84 85 8O o

75 70

E 65

Table 2: Comorbidities in Total 33 Patients

0 1

Missing/Dead (Total = 8)

7

significant differences between the two groups: Admission FIM score, admission motor subscore (Amotor), discharge Motor subscore (Dmotor) and the difference in the motor subscore (Amotor). Given the nature of the functional assessment scale (both F1M and Houghton scale), it was decided to use nonparametric statistic tests when appropriate, in accordance with recent recommendations.8j° The Wilcoxon rank sum test and the Wilcoxon signed rank tests were used. ~ In addition, Spearman correlation coefficients were calculated for the Houghton scale, Amotor score, Dmotor score, and Amotor score using all patients as a whole.

Comorbidity (n)

Houghton Scale <9 (T = 21)

60 successful

failed

Fig 1. Amotor ( I ) and Dmotor (D) subscores of the successful and failed groups of prosthetic user,

PREDICTING PROSTHETIC OUTCOME, Leung

u) O /

Table 3: Studies on Success of Prosthetic Rehabilitation

62

70

607

Criteria for Success of Prosthesis Rehabilitation

60

Author

50

Weiss 13

Ambulation for 20 feet

Moore TM

Ambulation on a daily basis with/without support Unclear, classified by interview into nonwearer, partial wearer, and fulltime wearer Independent ambulation at least 100 feet with/ without a cane Ambulation at least 100 yards

40 30 20

Deluccia ~s

10 0 No. o f c o m o r b i d i t y Dove TM

Fig 2. LOS versus no. of comorbidity.

In correlating the number of comorbidities with length of stay, we found that length of stay varied directly with number of comorbidities in the study group as a whole (fig 2). W e also stratified the Houghton scale with the time of interview and found that the Houghton scale has been stable after discharge from 3 months (fig 3). DISCUSSION There has recently been much in the literature about methods to predict rehabilitation outcome. The FIM score is advocated as the one of the most suitable methods. 4'~2 Two articles 4'~2 on the use of the FIM score in amputee patients used methodology that differed from our method in several ways. Rehabilitation outcome can be defined in many ways. In this cost containment era, many facilities use the functional status at discharge and the length of stay as outcome measures. Heinemann and coworkers 4 used both criteria as measures of rehabilitation success. Their reason was that patients with an improved functional status will have a shorter hospital stay. They found that the Amotor subscore was the most powerful predictor of the general discharge functional status in amputee patients (sample = 1,400, standardized regression coefficient >0.5). Level of amputation was unrelated to motor function. The motor subscore was also an important predictor of the length of stay in all impairment groups. Muecke and colleagues 5 studied the use of the FIM score as a predictor of the rehabilitation outcome in amputee patients. They used the difference in FIM score as the outcome measure. They found that the admission FIM score was a poor predictor of improvement of general functional status in patients with low initial FIM score, but the admission FIM score was highly predictive of the general functional outcome in patients in the top 2 quartiles of the FIM score on admission. In both studies, ~2 I 10 I

¢

8

¢

#

#

e

2 0

A 0

2

4

A 6

8

10

t~ne Fig 3. Houghton score versus time of interview (0, Q).

12

Kerstein ~7

Significant Predictors

Multiple disease and extensive atherosclerosis (negative predictor) Level of amputation (proximal -* worse) Level of amputation

Age and level of amputation

Age (older -, worse)

general functional status of the patient was used as the outcome measure. Neither study assessed the prosthetic use by the patient or used it as a outcome measure. Various patient variables (other than the FIM score) with regard to prosthetic fitting of lower limb amputee individuals have been suggested by several authors as being significant predictors./3-~7 Age, final level of amputation, and number of comorbidities were found to be significant correlating factors in the use of prosthesis (table 3). Our study confirmed that level of amputation and comorbidity correlate with the use of a prosthesis. Our failed group consisted of more above-knee amputee patients (33% vs 20%) and more comorbidities than the successful group. Our studies failed to show that age was a significant predictor in prosthetic outcome. We used the Houghton scale, ie, use of the prosthesis, as the outcome measure. We found that in both successful and unsuccessful prosthetic users, the difference in the discharge motor score was the only score that predicted successful prosthetic use. Moreover, only the Dmotor subscore correlated with the Houghton score in our amputee patients as a whole. W e found that neither the admission FIM, Amotor subscore, nor the change in FIM score could help differentiate between those who achieved our rehabilitation end point (ie, Houghton score of > 9 ) and those who did not (Houghton score of <9). Although the Dmotor score did differentiate between successful and unsuccessful prosthetic users, this is of no value in deciding prior to rehabilitation which patient should be fitted with a prosthesis. References

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8. Merbitz C, Morris J, Grip JC. Ordinal scales and foundations of misinference. Arch Phys Med Rehabil 1989;70:308-12. 9. Wright BD, Linacre JM. Observations are always ordinal; measurement, however, must be interval. Arch Phys Med Rehabil 1989;70: 857-65. 10. Johnson MV. Letter to the editor. Arch Phys Med Rehabil 1989; 70:861. 11. Scholtzhauer SD, Littel RC. SAS System for elementary statistical analysis. Cary, NC: SAS Institute Inc, 1987. 12. Heinemann AW, Linacre JM, Wright BD. Relationship between impairment and physical disability as measured by the Functional Independence Measurement. Arch Phys Med Rehahil 1993; 74:56673.

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13. Weiss GN, Gorton A, Read RC. Outcome of lower extremity amputations. J Am Geriatr Soc 1990;38:877-83. 14. Moore TJ, Barron J, Hutchinson F. Prosthetic usage following major lower extremity amputation. Clin Orthop 1989;238:21924. 15. Deluccia N, Pinto M, Guedes J. Rehabilitation after amputation for vascular disease: a follow up study. Prosthet Orthot Int 1992; 16: 124-8. 16. Dove HG, Schneider KC, Richardson F. Rehabilitation of patients following lower extremity amputation: an analysis of baseline, process and outcome. Am Corr Ther J 1982;36:94-102. 17. Kerstein MD, Zimmer H, Dugdale FE. What influence does age have on rehabilitation of amputee. Geriatrics 1975;30:67-71.