GAIT ANALYSIS MEDICAL POLICY. Policy Number: 2014T0506I Effective Date: June 1, Page. Table of Contents. Related Policies: None

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1 MEDICAL POLICY GAIT ANALYSIS Policy Number: 2014T0506I Effective Date: June 1, 2014 Table of Contents COVERAGE RATIONALE APPLICABLE CODES.. DESCRIPTION OF SERVICES... CLINICAL EVIDENCE.. U.S. FOOD AND DRUG ADMINISTRATION CENTERS FOR MEDICARE AND MEDICAID SERVICES (CMS). REFERENCES.. POLICY HISTORY/REVISION INFORMATION.. Policy History Revision Information INSTRUCTIONS FOR USE This Medical Policy provides assistance in interpreting UnitedHealthcare benefit plans. When deciding coverage, the enrollee specific document must be referenced. The terms of an enrollee's document (e.g., Certificate of Coverage (COC) or Summary Plan Description (SPD) and Medicaid State Contracts) may differ greatly from the standard benefit plans upon which this Medical Policy is based. In the event of a conflict, the enrollee's specific benefit document supersedes this Medical Policy. All reviewers must first identify enrollee eligibility, any federal or state regulatory requirements and the enrollee specific plan benefit coverage prior to use of this Medical Policy. Other Policies and Coverage Determination Guidelines may apply. UnitedHealthcare reserves the right, in its sole discretion, to modify its Policies and Guidelines as necessary. This Medical Policy is provided for informational purposes. It does not constitute medical advice. UnitedHealthcare may also use tools developed by third parties, such as the MCG Care Guidelines, to assist us in administering health benefits. The MCG Care Guidelines are intended to be used in connection with the independent professional medical judgment of a qualified health care provider and do not constitute the practice of medicine or medical advice. COVERAGE RATIONALE Gait analysis for surgical or clinical decision-making is unproven and not medically necessary. The available clinical evidence does not establish that gait analysis benefits health outcomes. The evidence is too limited to draw definitive conclusions regarding the role of gait analysis in the continuum of care. Evidence that includes clinical outcome results from randomized controlled trials is needed. APPLICABLE CODES Page Related Policies: None The Current Procedural Terminology (CPT ) codes and Healthcare Common Procedure Coding System (HCPCS) codes listed in this policy are for reference purposes only. Listing of a service code in this policy does not imply that the service described by this code is a covered or noncovered health service. Coverage is determined by the enrollee specific benefit document and applicable laws that may require coverage for a specific service. The inclusion of a code does not

2 imply any right to reimbursement or guarantee claims payment. Other policies and coverage determination guidelines may apply. This list of codes may not be all inclusive. CPT Code Description Comprehensive computer-based motion analysis by video-taping and 3D kinematics; Comprehensive computer-based motion analysis by video-taping and 3D kinematics; with dynamic plantar pressure measurements during walking Dynamic surface electromyography, during walking or other functional activities, 1-12 muscles Dynamic fine wire electromyography, during walking or other functional activities, 1 muscle Review and interpretation by physician or other qualified health care professional of comprehensive computer-based motion analysis, dynamic plantar pressure measurements, dynamic surface electromyography during walking or other functional activities, and dynamic fine wire electromyography, with written report CPT is a registered trademark of the American Medical Association. DESCRIPTION OF SERVICES Gait analysis is a process of measuring and evaluating the walking patterns of patients with specific gait-related problems. Gait analysis is also referred to as motion analysis. Observational gait analysis, the standard method of evaluating gait, refers to the visual assessment of a patient's gait, with specific attention to hips, knees and ankles. Gait analysis by observer assessment does not use any specialized equipment, and is used to note gross abnormalities in gait. Gait analysis may also be performed in a gait analysis laboratory using specialized technology. This is also referred to as computerized gait analysis, quantitative gait analysis or clinical gait analysis. This procedure has been used to understand the etiology of gait abnormalities and as part of the treatment decision-making in patients with complex walking problems. Surface or fine wire electromyography (EMG) data and force platform data may complement computerized gait analysis (Sutherland, 2001; Sutherland, 2005). CLINICAL EVIDENCE Computerized Gait Analysis for Cerebral Palsy Cerebral Palsy Classification Davids et al. (1999) conducted a prospective controlled study that investigated whether computerized gait analysis could differentiate patients with dyskinetic cerebral palsy (CP) from those with spastic CP and those with normal gait. Three-dimensional gait analysis was performed on 18 normal children, 17 children with principally spastic cerebral palsy, and 23 children with significantly dyskinetic cerebral palsy. Children were assigned to the spastic or dyskinetic groups prospectively, based on clinical analysis by an experienced physician and physical therapist. The children with dyskinesia were found to have a significantly wider, and more variable normalized dynamic base of support, a smaller step profile (step length divided by step width), and a greater and more variable maximal lateral acceleration than the spastic and normal groups. A predictive model of dyskinesia, using these gait parameters, exhibited excellent sensitivity, correctly classifying 20 (87%) of 23 children as dyskinetic. According to the investigators, this study shows that children with dyskinetic cerebral palsy have distinct gait parameters and that objective 2

3 assessment of dyskinesia in children with cerebral palsy is possible with computer-based analysis of gait. Study limitations include lack of rater blinding and a small sample size. Two prospective controlled or comparative studies (Steinwender et al., 2000; Rodda et al., 2004), one uncontrolled prospective study (Desloovere et al., 2006), and one retrospective study (Kawamura et al., 2006) evaluated gait analysis for the classification of spastic CP. Steinwender et al. (2000) documented reproducibility was higher in the sagittal plane, followed by the frontal and transverse planes. The Rodda study found that inter-rater repeatability ranged from 0.66 to 1.00 for gait classification; e.g., true equines, jump gait, apparent equinus, crouch gait, and symmetrical gait. Findings of the Desloovere study concluded that computerized gait analysis for CP did not always correlate with clinical assessment; correlation ranged from low to moderate. The Kawamura study showed poor to excellent correlation between computerized gait analysis and observational gait analysis, depending on the gait parameters. Domagalska et al. (2013) assessed the relationship between the spasticity of lower extremity muscles and deviations from the normal gait pattern in children with cerebral palsy (CP) by using gait analysis and clinical measurements. Thirty-six children with spastic CP (18 with spastic hemiplegia [HS] and 18 with spastic diplegia [DS]), ranging in age from 7 to 12 years, participated in the study. The children were classified as level I (n=24) or level II (n=12) according to the Gross Motor Function Classification System. Spasticity levels were evaluated with the Dynamic Evaluation of Range of Motion (DAROM) using the accelerometer-based system, and gait patterns were evaluated with a three dimensional gait analysis using the Zebris system. The Gillette Gait Index (GGI) was calculated from the gait data. The results show that gait pathology in children with CP does not depend on the static and dynamic contractures of hip and knee flexors. Although significant correlations were observed for a few clinical measures with the gait data (GGI), the correlation coefficients were low. Only the spasticity of rectus femoris showed a fair to moderate correlation with GGI. The authors concluded that the results indicate the independence of the clinical evaluation and gait pattern and support the view that both factors provide important information about the functional problems of children with CP. This study is limited by small sample size. In addition, further research is needed to determine the clinical relevance of these findings. Overall, computerized gait analysis can distinguish between normal and spastic or dyskinetic gait. It is also a promising tool for gait classification. Gait analysis does not necessarily correlate with clinical assessment. At this time, exact technical parameters and gait analysis models have not been established. Cerebral Palsy Treatment Planning Wren et al. (2013a) conducted a randomized controlled trial to determine if gait analysis improves correction of excessive hip internal rotation in ambulatory children with spastic cerebral palsy (CP). Children undergoing orthopedic surgery were randomized to receive or not receive a preoperative gait analysis report. This secondary analysis included all participants whose gait report recommended external femoral derotation osteotomy (FDRO). One-year postoperative, and pre- to postoperative change in femoral anteversion, mean hip rotation in stance, and mean foot progression in stance were compared between groups and in subgroups based on whether the recommendation for FDRO was followed. Outcomes did not differ between the group which received a gait report (n=39; 19 males, 20 females; mean age 10y 4mo) and the control group (n=26; 14 males, 12 females; mean age 9y 5mo), but improved more in the gait report subgroup in which the FDRO recommendation was followed (seven limbs; change in anteversion -32.9, hip rotation -25.5, foot progression ) than in the control group (anteversion -12.2, hip rotation -7.6, foot progression ) and the gait report subgroup in which FDRO was not performed (32 limbs; anteversion -1.0, hip rotation 0.5, foot progression -8.0 ). Postoperative measures became normal only in the gait report subgroup in which the recommended FDRO was performed. The authors concluded that gait analysis can improve outcomes when its recommendations are incorporated in the treatment plan. According to the authors, the major limitation of this study is that only seven of the 39 of the recommended FDROs were performed in 3

4 the gait report group, indicating poor compliance with the gait analysis recommendations. This practice pattern may limit generalizability of the study findings since other surgeons may be more likely to implement the gait analysis recommendations. In a randomized controlled trial, Wren et al. (2013b) examined the impact of gait analysis on surgical outcomes in ambulatory children with cerebral palsy (CP). A total of 156 children with CP (94 male; age 10.2±3.7 years) underwent gait analysis and were randomized to two groups: Gait Report group (N=83), where the referring surgeon received the patient's gait analysis report, and Control group (N=73), where the surgeon did not receive the gait report. Outcomes were assessed pre- and 1.3±0.5 years post-operatively. An intent-to-treat analysis compared outcomes between the two groups. Outcome measures included the Gillette Functional Activity Questionnaire (FAQ), Gait Deviation Index (GDI), oxygen cost, gross motor function measure, Child Health Questionnaire (CHQ), Pediatric Outcomes Data Collection Instrument (PODCI), and Pediatric Evaluation and Disability Inventory. The outcomes that differed significantly between groups were change in health from the CHQ, which was rated as much better for 56% (46/82) of children in the Gait Report group compared with 38% (28/73) in the Control group, and upper extremity physical function from the PODCI. Gait outcomes (FAQ and GDI) improved more when over half of the recommendations for a patient were followed or the recommended extent of surgery (none, single, or multi-level) was done. However, less than half (42%) of the gait analysis recommendations were followed in the Gait Report group. Since 35% were implemented in the Control group where the gait analysis recommendations were not known, the relative difference was only 7%. According to the authors, this is much less than the >85% reported in previous studies and may account for the lack of differences between groups for some of the outcome measures. Several study limitations were noted by the authors including relatively short length of follow-up, the small number of surgeons involved, and relatively small sample size and heterogenous patient population which may limit the generalizability of the study results. According to the authors, future research should investigate why gait analysis recommendations are not always followed. Wren et al. (2013c) examined the extent to which gait analysis recommendations are followed by orthopedic surgeons with varying degrees of affiliation with the gait laboratory. Surgical data were retrospectively examined for 95 patients with cerebral palsy who underwent lower extremity orthopedic surgery following gait analysis. Thirty-three patients were referred by two surgeons directly affiliated with the gait laboratory (direct affiliation), 44 were referred by five surgeons from the same institution but not directly affiliated with the gait laboratory (institutional affiliation), and 18 were referred by 10 surgeons from other institutions (no affiliation). Data on specific surgeries were collected from the gait analysis referral, gait analysis report, and operative notes. Adherence with the gait analysis recommendations was 97%, 94%, and 77% for the direct, institutional, and no affiliation groups, respectively. Procedures recommended for additions to the surgical plan were added 98%, 87%, and 77% of the time. Procedures recommended for elimination were dropped 100%, 89%, and 88% of the time. Of 81 patients who had specific surgical plans prior to gait analysis, changes were implemented in 84% (68/81) following gait analysis recommendations. According to the authors, gait analysis influences the treatment decisions of surgeons regardless of affiliation with the gait laboratory, although the influence is stronger for surgeons who practice within the same institution as the gait laboratory. Wren et al. (2011a) used data from a randomized controlled trial to determine the effects of gait analysis on surgical decision-making in children with cerebral palsy (CP). A total of 178 ambulatory children with CP (110 male; age 10.3±3.8 years) being considered for lower extremity orthopaedic surgery underwent gait analysis and were randomized into one of two groups: gait report group (N=90), where the orthopaedic surgeon received the gait analysis report, and control group (N=88), where the surgeon did not receive the gait report. Data regarding specific surgeries were recorded by the treating surgeon before gait analysis, by the gait laboratory surgeon after gait analysis, and after surgery. Agreement between the treatment done and the gait analysis recommendations was compared between groups using the 2-sided Fisher's Exact test. When a procedure was planned initially and also recommended by gait analysis, it was performed more 4

5 often in the gait report group (91% vs. 70%). When the gait laboratory recommended against a planned procedure, the plan was changed more frequently in the gait report group (48% vs. 27%). When the gait laboratory recommended adding a procedure, it was added more frequently in the gait report group (12% vs. 7%). According to the authors, these results provide a stronger level of evidence demonstrating that gait analysis changes treatment decision-making and also reinforces decision-making when it agrees with the surgeon's original plan. The study examined only the baseline data and the decision-making effects of gait analysis. The authors stated that future research will address the effects of gait analysis on patient outcomes. The primary limitations of this study are the small number of surgeons involved and the absence of outcome data. This study involved a single gait laboratory and gait laboratory surgeon and four referring surgeons from another institution. Larger multicenter studies are needed to obtain more generalizable results. Wren et al. (2011b) conducted a systematic review to evaluate and summarize the current evidence base related to the clinical efficacy of gait analysis including the use of gait analysis in patients with cerebral palsy. Identified references were assessed independently by four reviewers using a hierarchical model of efficacy adapted for gait analysis, and final scores were agreed upon by at least three of the four reviewers. A total of 1528 references were identified relating to human instrumented gait analysis. Of these, 116 original articles addressed technical accuracy efficacy, 89 addressed diagnostic accuracy efficacy, 11 addressed diagnostic thinking and treatment efficacy, seven addressed patient outcomes efficacy, and one addressed societal efficacy, with some of the articles addressing multiple levels of efficacy. According to the authors, this body of literature provides strong evidence for the technical, diagnostic accuracy, diagnostic thinking and treatment efficacy of gait analysis. The existing evidence also indicates efficacy at the higher levels of patient outcomes, but this evidence is more sparse and does not include any randomized controlled trials. The authors stated that the current evidence supports the clinical efficacy of gait analysis, particularly at the lower levels of efficacy, but additional research is needed to strengthen the evidence base at the higher levels of efficacy. This additional evidence should come from randomized controlled trials. In a prospective study, Lofterod et al. (2007) evaluated to what extent 3-D gait analysis changes preoperative surgical planning. Before gait analysis, 60 ambulatory children (age range 4 to 18 years) with spastic cerebral palsy had a specific surgical plan outlined, based on clinical examination by orthopedic surgeons. After gait analysis, the proposed surgical procedures were reviewed to determine the frequency with which the treatment plans changed. Treatment plans for 42 of the 60 patients were altered after gait analysis. Surgical treatment was recommended for 49 patients whereas 11 were recommended non-surgical treatment. Of the 253 specific surgical procedures proposed, 97 procedures were not recommended after gait analysis and 65 additional procedures were recommended after the analysis. Thus, the number of procedures proposed was reduced by 13%. There was good accord between gait analysis recommendations and the surgery performed subsequently (92%). According to the investigators, gait analysis provided important additional information that modified preoperative surgical planning to a high degree. The high accordance between recommendations and surgery performed suggests that surgeons seriously consider the gait data and treatment recommendations. Study limitations include small sample size and the study did not evaluate how computerized gait analysis affects patient outcomes. In a follow-up report, Lofterod and Terjesen (2008) assessed the outcome of orthopaedic surgery in ambulatory children with cerebral palsy, when the orthopaedic surgeons followed the recommendations from preoperative three-dimensional gait analysis. Fifty-five children were clinically evaluated by orthopaedic surgeons who proposed a surgical treatment plan. After gait analysis and subsequent surgery, three groups were defined. In group A, there was agreement between clinical proposals, gait-analysis recommendations, and subsequent surgery in 128 specific surgical procedures. In group B, 54 procedures were performed based on gait analysis, although these procedures had not been proposed at the clinical examination. In group C, 55 surgical procedures that had been proposed after clinical evaluation were not performed because 5

6 of the gait-analysis recommendations. The children underwent follow-up gait analysis 1 to 2 years after the initial analysis. Overall, at follow-up, there was improvement in kinematic parameters for children in groups A and B. The investigators concluded that gait analysis was useful in confirming clinical indications for surgery, in defining indications for surgery that had not been clinically proposed, and for excluding or delaying surgery that was clinically proposed. This study suggests that change in treatment planning due to gait analysis may be beneficial, but it is not known whether the outcome would be different if the original treatment plan had been followed. Radler et al. (2010) conducted a prospective study to investigate the correlation of femoral torsion and tibial torsion as measured by using computed tomography with transverse plane gait data for patients with rotational malalignment. Twenty-six lower limbs from 26 patients with cerebral palsy who were selected for surgery based on gait analysis were evaluated. The investigators concluded that there is a considerable dynamic influence of mechanisms of compensation, especially in the hip, that should be considered when evaluating the torsional profile. The investigators recommended that three-dimensional instrumented gait analysis be conducted for patients undergoing surgical correction of rotational malalignment. However, this study did not evaluate how computerized gait analysis improves patient outcomes. Benedetti et al. (2011) conducted a study to define equinus foot types in cerebral palsy (CP) patients according to the Ferrari classification, integrating clinical and instrumental assessments. The hypothesis was that clinical differentiation of equinus foot can be evidenced by recurrent anomalies identifiable through gait analysis (GA), which can make the assessment, usually based only on clinician semeiotics, more objective. Clinical and instrumental assessments were performed separately by a senior CP physiatrist and a senior GA physiatrist, the latter was blind to the clinical diagnosis of equinus type. The study included 20 patients, 16 diplegics and 4 hemiplegics (mean age 11 years, SD 4 years 11 months). Substantial agreement was found between clinical and gait analysis equinus assignment matched in 50 out of 61 types. In some cases only gait analysis was able to identify the equinus type, while in others it did not confirm clinical assignment. The authors concluded that gait analysis is able to distinguish different equinus types according to Ferrari classification, making the clinical decision less arbitrary. According to the authors, correct objective diagnosis of equinus foot in CP patients is of paramount importance when choosing suitable interventions. This study is limited by small sample size and did not evaluate whether gait analysis has an impact on clinical outcomes. Filho et al. (2008) performed a study to determine if recommendations based on threedimensional gait analysis (3DGA) are associated with better postoperative outcomes in patients with cerebral palsy (CP). Thirty-eight patients who underwent orthopedic surgery and assessment at the Gait Analysis Laboratory were evaluated retrospectively. The patients were divided into four groups according to the agreement between the recommendations from gait analysis and the procedures actually carried out. Fifteen patients with diplegic spastic cerebral palsy and indication for orthopedic surgery to improve walking and whose surgical intervention was postponed were also included in the study as a control group. Fourteen gait parameters recorded before and after treatment, were included in the statistical analysis. No gait improvement was noted in the control group or in patients on whom no procedures recommended by the gait exam were performed (agreement of 0%). In the other groups, agreements averaged 46.71%, 72.2%, and 100%, respectively. Improvement of gait parameters after treatment was observed in these groups, with more significant values directly related to increased agreement percentage. According to the investigators, the patients whose treatment matched the recommendations from threedimensional gait analysis showed a more significant improvement in walking. These findings require confirmation in a larger study. Lee et al. (1992) assessed 23 ambulatory children with cerebral palsy preoperatively by a detailed clinical examination and by gait analysis using a video-based gait analysis system (VICON). Surgery was then performed based on either the clinical assessment alone or a combination of clinical evaluation and gait analysis. About one year after surgery, a postoperative clinical and gait analysis assessment was performed. Sixteen children had improved and seven 6

7 children had not improved after surgery. Most of the children who had not improved were found to have had operations that differed from those recommended by gait analysis. Dynamic EMG studies were found to be useful in preoperative planning but did not show any consistent improvement even in the children with good results. According to the investigators, the combination of a careful clinical assessment and gait analysis can produce better results in surgery for children with cerebral palsy. This study is limited by small sample size and nonrandomization of study participants. Deluca et al. (1997) conducted a prospective comparative study to evaluate the impact of 3D gait analysis on surgical decisions in 91 patients with CP. Gait analysis affected surgical decision making in 52% of patients. Based on the gait analysis results, the physicians recommended additional surgery in 23% of patients and less surgery in 26% of patients. In a prospective, intraindividual comparative study to evaluate the impact of 3D gait analysis on the clinical management of 102 CP patients, Cook et al. (2003) found that the overall agreement between clinical assessment and gait analysis was 60%; better agreement was achieved for osteotomy (77%) than for soft-tissue surgery (55%). This study did not evaluate if gait analysis had an impact on clinical outcomes. Dobson et al. (2007) conducted a systematic review of the literature to evaluate the validity of existing classifications of gait deviations in children with cerebral palsy (CP). Numerous efforts have been made to develop classification systems for gait in CP to assist in diagnosis, clinical decision-making and communication. The internal and external validity of gait classifications in 18 studies were examined, including their sampling methods, content validity, construct validity, reliability and clinical utility. Half of the studies used qualitative pattern recognition to construct the gait classification and the remainder used statistical techniques such as cluster analysis. Few adequately defined their samples or sampling methods. Most classifications were constructed using only sagittal plane gait data. Many did not provide adequate guidelines or evidence of reliability and validity of the classification system. No single classification addressed the full magnitude or range of gait deviations in children with CP. The authors concluded that although gait classification in CP may be useful in clinical and research settings, the methodological limitations of many classifications restrict their clinical and research applicability. Narayanan (2007) reviewed the scientific literature to describe the role of gait analysis in the orthopaedic management of ambulatory children with CP and to examine the current best evidence to support these roles. The author stated that although gait analysis has been shown to alter decision making, there is little evidence that the decisions based on gait analysis lead to better outcomes. Consequently, clinical gait analysis remains controversial, with wide variation in the rates of utilization of gait analysis in the management of children with ambulatory CP. The author concluded that clinical trials and cohort studies are needed to provide the evidence to establish the appropriate utilization of this technology. In a retrospective review, Wren et al. (2009) evaluated the effects of clinical gait analysis (GA) and the amount of surgery that ambulatory children with cerebral palsy (CP) undergo. The patients were grouped into those who had undergone GA before their index surgery (GA group, N=313) and those who had not (NGA group, N=149). Patients in the GA group were significantly older and less functionally involved, had their first surgery in later years, and had a shorter followup than patients in the NGA group. Adjusting for these differences, patients in the GA group had more procedures and higher cost during index surgery, but less subsequent surgery. A higher proportion of patients went on to additional surgery in the NGA group with more additional surgeries per person-year. The total number of procedures (GA: 2.6/person-year, NGA: 2.3/person-year; P=0.22) and cost (GA: $20,448/person-year, NGA: $19,535/person-year; P=0.58) did not differ significantly between the 2 groups. The investigators concluded that clinical GA is associated with a lower incidence of additional surgery, resulting in lesser disruption to patients' lives. This study was retrospective, did not specifically evaluate health outcomes, and patients were not randomized to a treatment group. 7

8 Molenaers et al. (2006) performed a retrospective comparative study to evaluate the impact of computerized gait analysis and botulinum toxin A injections on orthopedic surgery in children with CP. The investigators found that gait analysis delayed the need for surgical intervention from a mean 6.8 years to 9.8 years for children aged 3 to 9. The retrospective nature of this study limits its validity. One small retrospective study evaluated the impact of computerized gait analysis on clinical outcomes (Chang et al., 2006). The study included 10 patients with CP and 10 age- and sexmatched controls. Children in the control group chose not to follow the gait analysis recommendation and chose a nonsurgical treatment approach, whereas children in the gait analysis group followed a physician's recommendation for gait analysis. The results documented that 74% of patients in the control group had no change or a negative outcome, 26% in the control group had a positive outcome. Of the gait analysis group 61% had no change or a negative outcome, while 44% of this group had a positive outcome. While the results of this study suggest that gait analysis recommendations may improve clinical outcomes, the control group did not undergo surgery, whereas those in the gait analysis group did. Therefore, it is not possible to determine the relative contributions of gait analysis and surgery. Based on these studies, the addition of gait analysis data to clinical assessment may delay or avoid surgery or result in additional surgery. However, it is not clear whether decisions that were based on gait analysis data improved patient outcomes. Further studies, including results of randomized controlled clinical trials documenting clinical outcomes, are needed to determine the future role of gait analysis. In guidance on the spasticity in children and young people with non-progressive brain disorders, the National Institute for Health and Care Excellence (NICE) states that the decision to perform orthopaedic surgery to improve gait should be informed by a thorough pre-operative functional assessment, preferably including gait analysis (NICE 2012). The National Institute of Neurological Disorders and Stroke (NINDS) Web information for Cerebral Palsy Hope through Research states that surgery for cerebral palsy may not be indicated for all gait abnormalities and the surgeon may request a quantitative gait analysis before surgery (NINDS, updated 2013). A registered trial relevant to gait analysis was identified on ClinicalTrials.gov. This ongoing multicenter randomized trial will provide evidence to support or refute the need for gait laboratory analysis for surgical decision-making for children with cerebral palsy. The estimated study completion date is March See the following Web site for more information: Accessed February Computerized Gait Analysis for Patient Management and Treatment Planning of Other Conditions A systematic literature search was performed in PUBMED and the Cochrane database by selecting manuscripts assessing any psychometric property of gait analysis in knee or hip osteoarthritis (OA). Among the 252 articles identified, the final analysis included 30 reports (781 knee OA patients and 343 hip OA patients). Gait analysis presents various feasibility issues and there was limited evidence regarding reliability (three studies, 67 patients). Discriminant capacity showed significant reduction of gait speed, stride length and knee flexion in OA patients compared to healthy subjects. Few data were available concerning construct validity (three studies, 79 patients). Responsiveness of gait speed was moderate to large with effect size ranging respectively from 0.33 to 0.89 for total knee replacement, and from 0.50 to 1.41 for total hip replacement. The reviewers concluded that available data concerning validity and reliability of kinematic gait analysis are insufficient to date to consider kinematic parameters as valuable outcome measures in OA. Further studies evaluating a large number of patients are needed (Ornetti et al. 2010). 8

9 Holly et al. (2009) conducted a systematic review of published evidence to identify valid, reliable, and responsive measures of functional outcome after treatment for cervical degenerative disease. The authors identified 11 studies of cervical degenerative disease and functional outcome that were included in an evidentiary table summarizing the quality of evidence (Classes I-III). Disagreements regarding the level of evidence were resolved through an expert consensus conference. The group formulated recommendations that contained the degree of strength based on the Scottish Intercollegiate Guidelines network. Validation was done through peer review by the Joint Guidelines Committee of the American Association of Neurological Surgeons/Congress of Neurological Surgeons. Gait analysis was found to be valid and reliable measures (Class II) for assessing cervical spondylotic myelopathy. The studies analyzed for gait analysis included nonrandomized trials by Singh and Crockard (1999) (41 patients), Moorthy et al. (2005) (6 patients) and Kuhtz-Buschbeck et al. (1999) (12 patients). Benedetti et al. (2013) evaluated gait analysis as a clinical assessment tool to determine if the results are consistent, irrespective of the laboratory. A baseline assessment between site consistency of one healthy subject was examined at 7 different laboratories. Anthropometric and spatio-temporal parameters, pelvis and lower limb joint rotations, joint sagittal moments and powers, and ground reaction forces were compared. The consistency between laboratories for single parameters was assessed by the median absolute deviation and maximum difference, for curves by linear regression. Twenty-one lab-to-lab comparisons were performed and averaged. Large differences were found between the characteristics of the laboratories (i.e. motion capture systems and protocols). Different values for the anthropometric parameters were found, with the largest variability for a pelvis measurement. The spatio-temporal parameters were in general consistent. Segment and joint kinematics consistency was in general high, except for hip and knee joint rotations. The main difference among curves was a vertical shift associated to the corresponding value in the static position. The consistency between joint sagittal moments ranged from R2=0.90 at the ankle to R2=0.66 at the hip, the latter was increasing when comparing separately laboratories using the same protocol. Pattern similarity was good for ankle power but not satisfactory for knee and hip power. The force was found the most consistent, as expected. According to the authors, the differences found were in general lower than the established minimum detectable changes for gait kinematics and kinetics for healthy adults. Li et al. (2012) assessed the accuracy of surface-measured tibiofemoral kinematics in functional activities in 10 subjects with unilateral, isolated grade II posterior cruciate ligament (PCL) deficiency. A dynamic stereo radiography (DSX) system and a Vicon motion capture system simultaneously measured knee or lower extremity movement during level running and stair ascent. Surface marker motion data from the Vicon system were used to create subject-specific models in OpenSim and derive the tibiofemoral kinematics. The surface-measured model-derived tibiofemoral kinematics in all six degrees of freedom (DOFs) were compared with those measured by the DSX as the benchmarks. The authors found that surface-based measures significantly underestimated the mean as well as inter-subject variability of the differences between PCLinjured and intact knees in abduction-adduction, internal-external rotations, and anterior-posterior translation. Gait abnormalities are an early clinical symptom in normal pressure hydrocephalus (NPH), and subjective improvement in gait after temporary removal of cerebral spinal fluid (CSF) has been used to decide to perform shunt surgery. Williams et al. (2008) investigated objective measures to compare gait before and after CSF drainage and shunt surgery. Twenty patients and nine controls were studied. Quantitative gait measures were obtained at baseline, after 3 days of controlled CSF drainage, and after shunt surgery. Decision to perform surgery was based on response to drainage, and patients were assigned to shunted or unshunted groups for comparison. There was no improvement after CSF drainage in the unshunted group (n = 4). In the shunted group (n = 15) velocity, double-support time, and cadence improved significantly after drainage, and improved further after shunt surgery. The degree of improvement after drainage significantly correlated to the degree of improvement postshunt for velocity, doublesupport time, cadence, and stride length. The investigators concluded that there are significant, 9

10 quantifiable changes in gait after CSF drainage that correspond to improvement after shunt surgery for patients with NPH. Use of objective gait assessment may improve the process of identifying these candidates when response to CSF removal is used as a supplemental prognostic test for shunt surgery. However, these findings require confirmation in a larger study. Fuller et al. (2002) assessed the influence of gait analysis with dynamic electromyography upon surgical planning in patients with upper motor neuron syndrome and gait dysfunction. Two surgeons prospectively evaluated 36 consecutive adult patients with a spastic equinovarus deformity of the foot and ankle. After the initial clinical evaluation and surgical planning, all patients underwent instrumented gait analysis collecting kinetic, kinematic and poly-emg data using a standard protocol by a single experienced physiatrist. Each surgeon reviewed the gait studies and patients independently and again formulated a surgical plan. Overall a change was made in 64% of the surgical plans after the gait study. The investigators concluded that instrumented gait analysis alters surgical planning for patients with equinovarus deformity of the foot and ankle and can produce higher agreement between surgeons in surgical planning. These findings require confirmation in a larger study. Sankar et al. (2009) evaluated 35 patients (56 feet) with recurrent clubfoot in an uncontrolled study. According to the investigators, quantitative gait analysis resulted in 28 changed procedures in 19 of 30 patients (63%) compared to pre-study surgical plans. Study limitations include small sample size and the study did not evaluate how computerized gait analysis affects patient outcomes. Del Din et al. (2011) evaluated gait alterations in patients with ankylosing spondylitis (AS). Twenty-four patients were evaluated: 12 normal and 12 pathologic in stabilized anti-tnf-alpha treatment. Physical examination and gait analysis were performed. Gait analysis results showed statistically significant alterations in the sagittal plane at each joint. According to the investigators, gait analysis, through gait alterations identification, allowed planning-specific rehabilitation intervention aimed to prevent patients' stiffness together with improve balance and avoid muscles' fatigue. Further research is needed to determine the clinical relevance of these findings. The evidence from these studies was too limited to draw definitive conclusions regarding the role of gait analysis for these conditions. U.S. FOOD AND DRUG ADMINISTRATION (FDA) The FDA has approved a large number of gait analysis systems for medical use under the 510(k) approval process, product code LXJ. Additional information regarding FDA approvals can be accessed at: Accessed on February CENTERS FOR MEDICARE AND MEDICAID SERVICES (CMS) Medicare does not have a National Coverage Determination (NCD) for gait analysis. Local Coverage Determinations (LCDs) do exist. Refer to the LCDs for Comprehensive Motion Analysis Studies. (Accessed February 26, 2014) REFERENCES Baker R. Gait analysis methods in rehabilitation. J Neuroengineering Rehabilitation. 2006; 3: 4. Bax MC. Terminology and classification of cerebral palsy. Dev Med Child Neurol.1964;11: Cited in: McLaughlin JF, Bjornson KF, Astley SJ, et al. The role of selective dorsal rhizotomy in cerebral palsy: critical evaluation of a prospective clinical series. Dev Med Child Neurol. 1994; 36 (9):

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13 2014. Ornetti P, Maillefert JF, Laroche D, et al. Gait analysis as a quantifiable outcome measure in hip or knee osteoarthritis: a systematic review. Joint Bone Spine Oct;77(5): Radler C, Kranzl A, Manner HM, et al. Torsional profile versus gait analysis: consistency between the anatomic torsion and the resulting gait pattern in patients with rotational malalignment of the lower extremity. Gait Posture Jul;32(3): Rodda JM, Graham HK, Carson L, et al. Sagittal gait patterns in spastic diplegia. J Bone Joint Surg Br. 2004; 86(2): Sankar C, Mundkur N. Cerebral palsy-definition, classification, etiology and early diagnosis. Indian J Pediatr. 2005; 72(10): Sankar WN, Rethlefsen SA, Weiss J, Kay RM. The recurrent clubfoot: can gait analysis help us make better preoperative decisions? Clin Orthop Relat Res May;467(5): Singh A, Crockard HA. Quantitative assessment of cervical spondylotic myelopathy by a simple walking test. Lancet Jul 31;354(9176): Singhi PD, Ray M, Suri G. Clinical spectrum of cerebral palsy in north India an analysis of 1,000 cases. J Trop Pediatr. 2002; 48(3): Steinwender G, Saraph V, Scheiber S, et al. Intra subject repeatability of gait analysis data in normal and spastic children. Clin Biomech (Bristol, Avon). 2000; 15(2): Sutherland DH. The evolution of clinical gait analysis part I: kinesiological EMG. Gait Posture. 2001; 14(1): Sutherland DH. The evolution of clinical gait analysis. Part II kinematics. Gait Posture. 2002; 16(2): Sutherland DH. The evolution of clinical gait analysis part III kinetics and energy assessment. Gait Posture. 2005; 21(4): Williams MA, Thomas G, de Lateur B, et al. Objective assessment of gait in normal-pressure hydrocephalus. Am J Phys Med Rehabil Jan;87(1): Wren TA, Elihu KJ, Mansour S, et al. Differences in implementation of gait analysis recommendations based on affiliation with a gait laboratory. Gait Posture. 2013c Feb;37(2): Wren TA, Gorton GE 3rd, Ounpuu S, et al. Efficacy of clinical gait analysis: A systematic review. Gait Posture. 2011b Jun;34(2): Wren TA, Kalisvaart MM, Ghatan CE, et al. Effects of preoperative gait analysis on costs and amount of surgery. J Pediatr Orthop Sep;29(6): Wren TA, Lening C, Rethlefsen SA, et al. Impact of gait analysis on correction of excessive hip internal rotation in ambulatory children with cerebral palsy: a randomized controlled trial. Dev Med Child Neurol. 2013a Oct;55(10): Wren TA, Otsuka NY, Bowen RE, et al. Influence of gait analysis on decision-making for lower extremity orthopaedic surgery: Baseline data from a randomized controlled trial. Gait Posture. 2011a Jul;34(3):