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The relationship between the School Function Assessment (SFA) and the Gross Motor Function Classification System (GMFCS) in ambulatory patients with cerebral palsy.

Periodic evaluation of neuromuscular function and determination for the need of multidisciplinary interventions are crucial in the care of patients with CP. In 2002, the World Health Organization (WHO) developed the International Classification of Functioning, Disability, and Health (ICF), calling for a common language and universal standard to help implement planning and intervention programs for individuals with disabilities. (1-4) Subsequently, there has been a paradigm shift and the use of outcomes tools now focuses both on clinical and functional results. (5-9)

There are many types of assessment tools for patients with cerebral palsy involving approaches from the standpoint of gross motor function, gait analysis, and energy utilization. (5,10-12) The Gross Motor Function Classification System (GMFCS) is valuable in the clinical assessment of patients with CP, providing a reliable severity scale. Another tool, the SFA, has received less attention. Although the SFA has been analyzed in the context of other CP assessments, an analysis in the perspective of gross motor function may potentially help elucidate relationships between a rating of apparent motor function level and actual performance. (13) Such a relationship could be examined in the scope of the GMFCS and the SFA.

The SFA is comprised of three categories in a "top-down" approach, from global to specific: Participation (Part I), Task Supports (Part II), and Activity Performance (Part III). It provides separate measures of the student's level of participation in school settings, performance of functional activities, and associated support components. It is important to not only measure a child's capacity for function but also to assess the community performance of that function. This assessment is important because a child's motor capability may be different in the social setting when compared to the clinical setting. (14) During standardization of the SFA, internal consistency was measured using the coefficient alpha procedure and results were uniformly high (.92 to .98). Test-retest reliability was also examined during development of the SFA resulting in coefficients ranging between .82 and .98. (15)

The GMFCS is a standardized system that classifies the degree of gross motor function impairment into five levels, I to V, in increasing order of severity and has been used to stratify patients with CP. The GMFCS has been found to be valid and reliable. Wood and Rosenbaum calculated interrater reliability using a generalizability (G) coefficient and found high interrater reliability (G = 0.93). (1-4) The aims of this study were: 1. to assess the relationship between the severity level of gross motor function impairment in ambulatory patients with CP, as defined by the GMFCS and data obtained from the SFA; and 2. to investigate whether the relationship between the SFA and GMFCS can be utilized to create a reliable model to predict GMFCS levels based on SFA data. If GMFCS levels can be derived from SFA data, these predicted GMFCS levels can be compared to clinically diagnosed GMFCS levels, and if a difference exists, the role for further intervention can be investigated.

Materials and Methods

This cross-sectional, multicenter study investigated the relationship between functional activity and participation outcomes (SFA) and in-clinic ratings of gross motor functional impairment (GMFCS). Centers were located in Louisiana, Mississippi, Oklahoma, Arkansas, California, and Mexico. The Institutional Review Board (IRB) at each of the participating institutions approved the study.

Patient Population

One hundred and three subjects were included between 6 to 18 years of age. Subjects included both native English and Spanish-speakers. Inclusion criteria were: 1. clinical diagnosis of cerebral palsy, 2. motor pattern consistent with spastic diplegia, and 3. IRB-approved consent forms either by the child or their parent. Non-ambulatory children with CP (GMFCS level V) were not included in the study. Of the 140 subjects originally recruited, 103 were actually enrolled because the remaining 37 subjects had missing SFA data. The missing data consisted of a significant portion of unanswered components of the SFA. Ninety-five children had clinically evaluated GMFCS levels, and all 103 had SFA data. Medical doctors at each study site determined the GMFCS rating. Table 1 describes the contextual factors of our study subjects.

SFA Data

The SFA was completed by in-school personnel (school therapists and schoolteachers) who were familiar with the subjects and extent of participation in school and community activities. The in-school personnel completed a total of 385 questions assessing body function and participation. Table 2 shows the organization and sections of the SFA with the abbreviations used for each subscale in this study. As shown in Table 2, Special Education Classroom and Level II components of UDStairs, WritWork, and CompEqui were not included in this study. This was because special attention was given to those components of the SFA that correspond to motor function.

Statistical Analysis

Statistical analysis was completed using STATA version 8.0 and SPSS version 12.0 (StataCorp, College Station, TX, and IBM, Armonk, New York, respectively). Correlation analysis was undertaken to assess the relationship between the composite SFA and SFA subscale scores and GMFCS level. The correlation analysis involved Spearman's rank correlation between SFA scores and GMFCS levels. Subsequently, a regression model was developed to observe whether the SFA scores predicted GMFCS levels, setting the GMFCS level as the dependent variable. The SFA subscales used to generate the regression model were those that had a significant correlation to GMFCS levels. Using the regression equation, GMFCS scores were predicted and then compared to the actual clinically diagnosed GMFCS scores using both student's t-test and correlation analysis. One-way ANOVA was used to detect differences in SFA scores among GMFCS levels. The ANOVA testing was performed in two sets, the first involving GMFCS levels I to IV and those SFA subscales that had significant correlations to GMFCS, and the second involving the same SFA subscales but only GMFCS levels I to III. For all statistical tests, p-values were set at p < 0.05 as a threshold for significance, and confidence intervals were set at 95% for all numerical ranges.

Results

The 103 pediatric patients in the study had an average age of 11.75 years (range 6 to 18 years, SD 3.25 years). Ninety-five subjects, composed of 56 males and 39 females, had completed GMFCS evaluations. Age and gender did not have any significant impact on any of the measures. GMFCS levels of the 95 subjects were as follows: 14 GMFCS I (15%), 47 GMFCS II (49%), 33 GMFS III (35%), and 1 GMFCS IV (1%). SFA information was obtained for all 103 subjects, of which 69 (67%) were in a regular classroom setting, and 36 (33%) were in a special education classroom setting. The mean SFA score for Part I (School Participation) was 82.1 [+ or -] 1.7, with no significant effect from being in either classroom setting. The mean SFA score for Part II (Task Support) was 76.67 [+ or -] 2.4. The mean score for Part III (Task Performance) was 84.8 [+ or -] 1.6 for physical tasks, 93.3 [+ or -] 0.9 for cognitive-behavioral tasks, and 89.1 [+ or -] 1.3 combined.

Spearman's rank correlation comparing SFA to GMFCS showed a significant correlation between the composite SFA criterion score and GMFCS class (r = -0.847, p < 0.02). The negative correlation value is a result of the GMFCS being a measurement of severity, with a higher level indicating a more severe disability, while high SFA scores indicated better performance. Analysis between the mean score of each SFA subscale and respective GMFCS levels exhibited statistically significant correlations for many of the subscales. The remainder of the scales had non-significant r-values all below r = 0.5 and p > 0.05. Of the significantly correlated SFA subscales, ManMvmt correlated most strongly with GMFCS (r = -0.494, p < 0.0001). Other SFA subscales that significantly correlated with GMFCS include RecMvmt (r = -0.387, p < 0.0001), Phys1 and Phys2 (both r = -0.340, p < 0.001), Position (r = -0.338, p < 0.001), RegClass (r = -0.281, p < 0.01), SetClean (r = -0.227, p < 0.03), ClothMgt (r = -0.211, p < 0.05), and UDStairs (r = -0.453, p < 0.0001). Figure 1 shows the Spearman's rank correlation plots for each of the significant subscales.

[FIGURE 1 OMITTED]

Using STATA and SPSS, the SFA data was examined in the context of the ordinal GMFCS levels. This was used to generate a regression function in which the GMFCS level was the dependent variable, while the SFA subscales (as listed in Table 1) were the independent variables. The regression model was generated using only the statistically significant subscales (independent variables) in the context of GMFCS (dependent variable). The following equation was the model generated:

GMFCS = 4.07 + 0.0278(RegClass) + 0.0217(Phys1) 0.0244(Phys2) + 0.0009(Position) - 0.0336(UDStairs) + 0.0040(RecMvmt) - 0.0304(ManMvmt) - 0.0310(SetClean) + 0.0201(ClothMgt).

The regression equation was also used to predict GMFCS for all 95 subjects that had complete SFA data. Student's t-test analysis between predicted GMFCS levels and the actual clinically diagnosed GMFCS levels demonstrated no significant difference (p = ns); additionally, there was a significant correlation between the two sets of GMFCS data (r = 0.584, p < 0.001).

One-way ANOVA was used to detect differences among SFA subscale scores for each of the GMFCS levels. Several SFA subscales exhibited significant differences between their average subscale score at each level of the GMFCS. The scales that exhibited these significant differences include Physl (F = 5.32, p < 0.002), Phys2 (F = 4.54, p < 0.005), Position (F = 4.63, p < 0.004), RecMvmt (F = 7.92, p < 0.001), ManMvmt (F = 13.50, p < 0.001), UDStairs (F = 6.18, p < 0.001), and CompEqui (F = 3.18, p < 0.028). Since the GMFCS is highly dependent on a subject's motor ability, a separate one-way ANOVA analysis that included only motor-heavy SFA subscales (Phys1, Position, RecMvmt, ManMvmt, and ClothMgt) was performed. This separate analysis only examined these motor-heavy subscales in the context of GMFCS levels I to III since these levels require a degree of intrinsic walking ability, a major motor function. Statistical significance was also seen in the context of GMFCS Levels I to III, Phys1 (F = 7.89, p < 0.001), Position (F = 6.85, p < 0.002), RecMvmt (F = 11.17, p < 0.0001), ManMvt (F = 16.44, p < 0.0001), UDStairs (F = 8.36, p < 0.001).

Discussion

Accurately assessing motor function is crucial in the evaluation and guidance of patients with cerebral palsy. Use of appropriate outcome tools to assess children with cerebral palsy can lead to best practices and reduced costs in both clinical and non-clinical settings. (16) Additionally, before any intervention is initiated, an accurate measurement of gross motor dysfunction as well as the functional and psychosocial well-being of the patient must be attained. Understanding relative functional levels potentially provides insight into the benefits and liabilities of specific treatment. (17) Numerous studies have been published assessing various functional outcome tools and their relationship with the severity of gross motor impairment in children with CP. Less focus has been attributed to the School Function Assessment (SFA) and its relationship with the level of gross motor dysfunction. The relatively little focus on the SFA in the context of gross motor function led us to investigate the relationship between the SFA and the GMFCS.

In our analysis of the relationship between the SFA and GMFCS, special attention was given to particular subscales of the SFA. The broad range of locations was chosen so that the study population could be more reflective of the generalized population of patients with CP. Aside from the composite SFA score's statistically significant correlation with GMFCS, many of the individual SFA scales correlated with the GMFCS. The majority of these scales were within the Task Supports (II) and Activity Performance (III) categories. In addition to the significant correlations between the SFA and GMFCS, one-way ANOVA analysis determined that many of the SFA scales demonstrated significant differences in their mean criterion score among the GMFCS levels. Thus, these results suggested that the GMFCS levels were distinct and that they may be successfully used to assess differences in social functional abilities. Although SFA scales, such as "Using Materials," "Eating and Drinking," "Hygiene," "Written Work," and "Computer and Equipment Use," are measures of motor function and are expected to correlate well with GMFCS levels, they exhibited weak correlations (r < 0.5) and were not statistically significant. This may be due to the fact that these scales relate more to intricate and finely coordinated motor function rather than gross motor function, as assessed by the GMFCS guidelines. The lack of a correlation for the SFA scales "CogBeh1 and 2," "Functional Communication," "Following Social Conventions," "Compliance with Adult Directives and Following School Rules," "Memory and Understanding," "Task Behavior," "Positive Interaction," Behavior Regulation," "Personal Care Awareness," and "Safety" (all p > 0.05) can be explained by the fact that these scales are not intended to measure motor function. In addition to the correlation results, regression analysis demonstrated that the generated equation has value in approximating GMFCS levels.

The finding of correlation between SFA scores and GMFCS levels indicates that the SFA may be used to approximate the corresponding level of the GMFCS for a given SFA data set. However, the investigators would like to explicitly state that the approximation of the GMFCS through the SFA is not intended to replace the GMFCS in anyway. Instead, we suggest that a comparison can be made between the clinically determined GMFCS level and the GMFCS level approximated by the SFA. This comparison may prove useful in determining if a child's SFA performance parallels their clinically diagnosed GMFCS level. If there is any discrepancy, there may be an indication for further intervention.

Since the SFA involves many individual components of function, treatment planning can emphasize strategies to focus on a specified area. (11) Since the SFA consists of separate scales, the student's functional profile can be described relative to specific performance areas that are of strength or limitation. This ultimately allows for development of a better, more individualized treatment plan. If, for example, a child's clinically diagnosed GMFCS level is I but his or her SFA approximates that function is at a level III, there may be potential for improvement and further evaluation of individual skills should be attempted. Similarly, a child with clinically diagnosed GMFCS level III with an SFA-predicted GMFCS level II may not need as aggressive of an interventional approach. Thus, community performance exceeds that to what was measured by an in-clinic assessment.

The primary limitation of this study was the assumption that all tests were administrated in a standardized manner. There is the possibility that observer bias may have affected the SFA data or GMFCS evaluations. However, we believe that these limitations were controlled by the simple nature of the assessments. Multiple studies have confirmed the reliability and validity of the SFA. (18)

Our study only observed patients at GMFCS levels I to III, with one at level IV The single GMFCS IV subject is not sufficient to support that the relationships found would extend to GMFCS level IV. Of question is whether the SFA scores in the very low range also approximated GMFCS level V. This cannot be explained because non-ambulatory level V patients were not included in this study. Further studies with possible age and gender stratification may be of interest. Although statistically significant, the correlation coefficient for clinical and SFA-approximated GMFCS was r = 0.584. Additional studies with a larger cohort and balanced representation of GMFCS levels in the study population may reveal a better correlation.

Conclusions

In line with the framework of the WHO ICF, this study supports that correlations of SFA components and the GMFCS may be utilized in the clinical setting by allowing for a comparison between the approximated GMFCS (via the SFA) and the clinically diagnosed GMFCS. This comparison can be of use in deciding if additional intervention is needed to meet certain functional goals. Further, the identification of discrepancies between clinically measured and social motor function may greatly improve decisions on treatment and interpretation of intervention outcomes.

Disclosure Statement

None of the authors have a financial or proprietary interest in the subject matter or materials discussed, including, but not limited to, employment, consultancies, stock ownership, honoraria, and paid expert testimony.

Remy V. Rabinovich, M.D., Nitesh V. Patel, M.D., Philip E. Gates, M.D., and Norman Y. Otsuka, M.D.

Remy V Rabinovich, M.D., Nitesh V Patel, M.D., and Norman Y. Otsuka, M.D., New York University School of Medicine, Hospital for Joint Diseases, Center for Children, New York, New York. Philip E. Gates, M.D., Children's Clinical Research Center (CCRC), Shriners Hospitals for Children, Shreveport, Louisiana.

Correspondence: Remy V. Rabinovich, M.D., NYU Hospital for Joint Diseases, NYU Langone Medical Center, 301 East 17th Street, New York, New York, 10003; remyrabinovich@gmail.com.

References

(1.) WHO. International Classification of Functioning, Disability, and Health (ICF). Geneva, Switzerland: World Health Organization, 2001.

(2.) Perenboom RJ, Chorus AM. Measuring participation according to the International Classification of Functioning, Disability and Health (ICF). Disabil Rehabil. 2003; Jun 3-17; 25(11-12):577-87.

(3.) Rosenbaum P, Stewart D. The World Health Organization International Classification of Functioning, Disability, and Health: a model to guide clinical thinking, practice and research in the field of cerebral palsy. Semin Pediatr Neurol. 2004 Mar; 11(1):5-10.

(4.) Simeonsson RJ, Leonardi M, Lollar D, et al. Applying the International Classification of Functioning, Disability and Health (ICF) to measure childhood disability. Disabil Rehabil. 2003 Jun 3-17; 25(11-12):602-10.

(5.) Nordmark E, Hagglund G, Jarnlo GB. Reliability of the gross motor function measure in cerebral palsy. Scand J Rehabil Med. 1997 Mar; 29(1):25-8.

(6.) Abel MF, Damiano D, Blanco J, et al. Relationships among musculoskeletal impairments and functional health status in ambulatory cerebral palsy. J Pediatr Orthop. 2003 Jul-Aug; 23(4):535-41.

(7.) Majnemer A, Mazer B. New directions in the outcome evaluation of children with cerebral palsy. Semin Pediatr Neurol. 2004 Mar; 11(1):11-7.

(8.) Sakzewski L, Boyd R, Ziviani J. Clinimetric properties of participation measures for 5- to 13-year-old children with cerebral palsy: a systematic review. Dev Med Child Neurol. 2007 Mar; 49(3):232-40.

(9.) Schwartz MH, Viehweger E, Stout J, et al. Comprehensive treatment of ambulatory children with cerebral palsy: an outcome assessment. J Pediatr Orthop. 2004 Jan-Feb; 24(1):45-53.

(10.) Palisano R, Rosenbaum P, Walter S, et al. Development and reliability of a system to classify gross motor function in children with cerebral palsy. Dev Med Child Neurol. 1997 Apr; 39(4):214-23.

(11.) Russell DJ, Avery LM, Rosenbaum PL, et al. Improved scaling of the gross motor function measure for children with cerebral palsy: evidence of reliability and validity. Phys Ther. 2000 Sep; 80(9):873-85.

(12.) Wood E, Rosenbaum P. The gross motor function classification system for cerebral palsy: a study of reliability and stability over time. Dev Med Child Neurol. 2000 May; 42(5):292-6.

(13.) Gates PE, Otsuka NY, Sanders JO, Mcgee-Brown J. Relationship between parental PODCI questionnaire and School Function Assessment in measuring performance in children with CP. Dev Med Child Neurol. 2008 Sep; 50(9):690-5.

(14.) Novacheck TF, Stout JL, Tervo R. Reliability and validity of the Gillette Functional Assessment Questionnaire as an outcome measure in children with walking disabilities. J Pediatr Orthop. 2000 Jan-Feb; 20(1):75-81.

(15.) Davies PL, Soon PL, Young M, Clausen-Yamaki A. Validity and reliability of the school function assessment in elementary school students with disabilities. Phys Occup Ther Pediatr. 2004; 24(3):23-43.

(16.) Daltroy LH, Liang MH, Fossel AH, et al. The POSNA pediatric musculoskeletal functional health questionnaire: report on reliability, validity, and sensitivity to change. Pediatric Outcomes Instrument Development Group. Pediatric Orthopaedic Society of North America. J Pediatr Orthop. 1998 Sep-Oct; 18(5):561-71.

(17.) Barnes D, Linton JL, Sullivan E, et al. Pediatric outcomes data collection instrument scores in ambulatory children with cerebral palsy: an analysis by age groups and severity level. J Pediatr Orthop. 2008 Jan-Feb; 28(1):97-102.

(18.) Coster W, Deeney T, Haltiwanger J, Haley S. School Function Assessment Technical Report. Pearson Education, Inc., 2008.

Caption: Figure 1: Spearman's rank correlation based trend plots. Shown are plots for the SFA sub-scales that correlated significantly to GMFCS levels for the 95 subjects with diagnosed GMFCS levels. The X-Axis lists GMFCS levels I to VI, while the Y-Axis lists SFA subscale scores--each subscale has a different maximum score, and the Y-Axis range is variable among the plots. Since Spearman's rank correlation was used, the X-axis has rank values, and thus Y-values are grouped among each rank. A trend line is shown for each graph.
Table 1 Contextual Criteria of 103 Children Assessed in
This Study

Average Age              11.75 years (range: 6 to 18;
                         SD [+ or -] 3.25 years)

Gross Motor Functional   GMFCS Level I--13.7%
Classification System
(GMFCS) Level:           GMFCS Level II--50%

                         GMFCS Level III--35.3%

                         GMFCS Level IV--1%

School Setting:          73% in a Regular Classroom
                         Setting

                         27% in a Special Education
                         Classroom Setting

Ambulatory Status:       59% walked Independently

                         41% used an Assistive Device

Additional Services      81% utilized school services,
Utilized:                such as occupational or
                         physical therapy, speech
                         therapy, or academic aide

Table 2 School Function Assessment (SFA) Components

                         SFA Category                    Abbreviation

Level I     Standard     Regular Classroom + 5           RegClass
                           Settings
                         * Special Education             --
                           Classroom + 5 Settings
Level II    Standard     Physical Tasks--Assistance      Phys1
                         Physical Tasks--Adaptations     Phys2
                         Cognitive/Behavioral            CogBeh1
                           Tasks--Assistance
                         Cognitive/Behavioral            CogBeh2
                           Tasks--Adaptations
            Optional     * Up/Down Stairs--Assistance    --
                         * Up/Down Stairs--              --
                           Adaptations
                         * Written Work--Assistance      --
                         * Written Work--Adaptations     --
                         * Computer/Equipment            --
                           Use--Assistance
                         * Computer/Equipment            --
                           Use--Adaptations
Level III   Physical     Travel                          Travel
              Tasks      Maintaining/Changing            Position
                           Positions
                         Recreational Movement           RecMvmt
                         Manipulation with Movement      ManMvmt
                         Using Materials                 Material
                         Setup/Clean-Up                  SetClean
                         Eating/Drinking                 EatDrink
                         Hygiene                         Hygiene
                         Clothing Management             ClothMgt
                         Up/Down Stairs                  UDStairs
                         Written Work                    WritWork
                         Computer/Equipment Use          CompEqui
            Cognitive/   Functional Communication        FuncComm
            Behavioral   Memory/Understanding            MemUnder
              Tasks      Following Social Conventions    SocConve
                         Compliance With Adult           Complian
                           Directives/Rules
                         Task Behavior/Completion        TaskBeh
                         Positive Interaction            PosInter
                         Behavior Regulation             BehReg
                         Personal Care Awareness         PersCare
                         Safety                          Safety
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Author:Rabinovich, Remy V.; Patel, Nitesh V.; Gates, Philip E.; Otsuka, Norman Y.
Publication:Bulletin of the NYU Hospital for Joint Diseases
Article Type:Report
Date:Jul 1, 2015
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