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Gait Kinematics in Individuals with Acute and Chronic Patellofemoral Pain


Medicine & Science in Sports & Exercise: March 2018 - Volume 50 - Issue 3 - p 502–509
doi: 10.1249/MSS.0000000000001465

Purpose This study aimed to identify the discriminating kinematic gait characteristics between individuals with acute and chronic patellofemoral pain (PFP) and healthy controls.

Methods Ninety-eight runners with PFP (39 male, 59 female) and 98 healthy control runners (38 male, 60 female) ran on a treadmill at a self-selected speed while three-dimensional lower limb kinematic data were collected. Runners with PFP were split into acute (n = 25) and chronic (n = 73) subgroups on the basis of whether they had been experiencing pain for less or greater than 3 months, respectively. Principal component analysis and linear discriminant analysis were used to determine the combination of kinematic gait characteristics that optimally separated individuals with acute PFP and chronic PFP and healthy controls.

Results Compared with controls, both the acute and chronic PFP subgroups exhibited greater knee flexion across stance and greater ankle dorsiflexion during early stance. The acute PFP subgroup demonstrated greater transverse plane hip motion across stance compared with healthy controls. In contrast, the chronic PFP subgroup demonstrated greater frontal plane hip motion, greater knee abduction, and reduced ankle eversion/greater ankle inversion across stance when compared with healthy controls.

Conclusions This study identified characteristics that discriminated between individuals with acute and chronic PFP when compared with healthy controls. Certain discriminating characteristics were shared between both the acute and chronic subgroups when compared with healthy controls, whereas others were specific to the duration of PFP.

1Centre for Sports Research, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, AUSTRALIA; 2Faculty of Kinesiology, University of Calgary, Calgary, CANADA; 3Faculty of Nursing, University of Calgary, Calgary, CANADA; and 4Running Injury Clinic, University of Calgary, Calgary, CANADA

Address for correspondence: Jason Bonacci, Ph.D., Centre for Sports Research, School of Exercise and Nutrition Sciences, Deakin University, 75 Pigdons Road, Waurn Ponds, Melbourne, VIC 3216, Australia; E-mail:

Submitted for publication April 2017.

Accepted for publication October 2017.

Patellofemoral pain (PFP) is the most prevalent injury among runners, with a reported incidence of 3%–15% among active populations (1). The condition is characterized by anterior knee pain or retropatellar pain in the absence of other specific pathology (2). PFP is suggested to relate to high patellar contact stresses that exceed tissue capacity, where malalignment between the patella and the femur can lead to increased patellar contact stress (3). Although the mechanisms underpinning PFP are not well understood, pain may be related to elevated patellar bone metabolic activity (4,5) stemming from elevated joint stress during locomotion.

A number of biomechanical factors during gait have been linked to elevated patellofemoral joint loads and stress, potentially leading to the development of PFP. For example, greater knee flexion results in increased patellofemoral compressive loads, elevating overall joint contact forces (6,7). Increased tibiofemoral rotation and knee abduction may induce lateral patellar tracking, resulting in increased lateral patellofemoral joint stress (8,9). Foot and hip motions have also been hypothesized as factors contributing to PFP, because of these motions altering kinematics at the knee and patellofemoral joint (10). Excessive eversion has also been suggested to increase tibial internal rotation and knee abduction (8), and increases in hip adduction and internal rotation can increase the magnitude of stress placed on the lateral aspect of the patella (11,12). These links between gait biomechanics and patellofemoral joint stress seem relevant to the development and persistence of PFP. A recent prospective study reported that women who developed PFP demonstrated greater peak hip adduction during running (6). Cross-sectional studies have also observed increased hip internal rotation and adduction (13–19), increased knee internal (17) and external rotation (15), and heel strike rearfoot eversion (20) in individuals with PFP compared with healthy controls.

A substantial problem with PFP is the high propensity for chronicity. Although treatment for PFP in the short term has shown promise, long-term treatment outcomes are less successful (21–23). Individuals who experience PFP for greater than 12 months have worse pain 5 to 8 yr later (24), whereas a 7-yr follow-up of those with chronic PFP found that approximately 30% had persistent complaints (23). Prolonged PFP can lead to decreases in physical activity (22,25,26) and may increase the risk of developing patellofemoral osteoarthritis (27,28).

The presence of prolonged pain may alter gait biomechanics in runners leading to these poor prognoses and outcomes. Although longitudinal monitoring is required to confirm this, cross-sectional studies have shown that female runners with PFP exhibit biomechanical characteristics such as greater hip adduction and internal rotation (13–19), which are associated with increased lateral patellofemoral stress (11,12) and overall patellofemoral joint stress (29). In contrast, compensatory biomechanical adjustments may be implemented to cope with the pain. Currently, no studies have examined gait biomechanics during the early versus later stages of PFP. It is therefore unknown whether prolonged PFP is associated with continuation of altered biomechanics, or whether other compensatory changes may play a role in the persistence of pain. Gait retraining has been advocated as a potential conservative treatment option for runners experiencing PFP (30). However, should differences in gait biomechanics exist between those with acute PFP and those with chronic PFP, these interventions may need to be specifically targeted to the individuals’ status. Furthermore, most studies examining biomechanical characteristics associated with PFP have used discrete point variables, such as peak values, to compare groups (6,13–19). The use of functional data analysis methods, such as principal component analysis (PCA), has multiple benefits over discrete point analysis techniques. Discrete point analysis can often discard the majority of data in a waveform (31). PCA views the entire waveform as a function, preserving the main features and patterns of the curve (32). Discrete point methods also involve the preselection of features thought to make up the important components of a given waveform (31). This preselection process is strongly dependent on previous knowledge or research within the area and has the potential to discard important information contained within the waveform (31–33). In addition, examining discrete points does not always take into account the timing of the points of interest (31). For example, the amplitude of a peak joint angle across two trials may be identical; however, this peak may occur at a substantially different time within the waveform. Lastly, discrete point analysis, as has been typical of previous investigations of runners with PFP, does not allow for the examination of patterns that occur over a specific time or phase of the waveform (31). Considering the potential negative effect prolonged PFP can have on health (23,24,27,28) and activity levels (22,25,26), identifying biomechanical subgroups and specific factors associated with the presence of long-term pain may be useful in directing treatment methods toward this population. Therefore, the purpose of this study was to identify the discriminating kinematic gait characteristics between individuals with acute and chronic PFP and healthy controls.

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A total of 196 recreational runners participated in this study (see Table 1). The university’s research ethics board approved the collection of the data and subsequent storage within a research database. Participant characteristics are provided in Table 1. Participants were required to be recreationally active (>30 min·d−1, 3–4 d·wk−1 for the past 6 months and exclusive of pain) to be included within this study. Participants were excluded if they had any of the following: (i) meniscal or other intra-articular injury; (ii) cruciate or collateral ligament laxity or tenderness; (iii) patellar tendon, iliotibial band, or pes anserine tenderness; (iv) positive patellar-apprehension sign; (v) Osgood–Schlatter or Sinding–Larsen–Johansson syndrome; (vi) evidence of effusion; (vii) hip or lumbar referred pain; (viii) history of recurrent patellar subluxation or dislocation, or surgery to the knee joint; (ix) nonsteroidal anti-inflammatory drug or corticosteroid use within 24 h before testing; (x) history of head injury or vestibular disorder within the last 6 months; and (xi) pregnancy. Of the total sample, 98 participants were injury-free for the past 6 months and had no additional acute or chronic lower limb pathologies. The remaining 98 participants were runners with diagnosed PFP. The additional inclusion criteria for participants with PFP were as follows: (i) visual analog score rating of pain during activities of daily living during the previous week at a minimum of 3 cm on a 10-cm scale; (ii) insidious onset of symptoms unrelated to trauma and persistent for at least 4 wk; (iii) pain in the anterior knee aggravated by at least three of the following: during or after activity, prolonged sitting, stair ascent/descent, or squatting; and (iv) pain with either palpation of the patellar facets, during step-down from a 20-cm box, or double-legged squat. The anterior knee pain scale (34) and worst pain on 100-mm visual analog scale (35) were used to indicate pain severity within the PFP subgroups (see Table 1).



Participants were split into three subgroups: 1) those with no injuries or pathology served as the control group, 2) those who had experienced PFP for less than 3 months served as the acute pain subgroup, and 3) those who had experienced PFP for greater than 3 months served as the chronic pain subgroup (36). Before data collection, participants provided written informed consent to participate.

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Data collection

Three-dimensional kinematics of the lower limb during treadmill running were collected using an eight-camera motion capture system (Vicon; Oxford Metrics Limited, Oxford, United Kingdom) sampling at 200 Hz. Nine-millimeter retroreflective markers were attached bilaterally to participants’ first and fifth metatarsal heads, medial and lateral malleoli, medial and lateral femoral condyles, tibial tuberosity, greater trochanter, anterior superior iliac spine, and iliac crest in the same manner as previously described (37,38). Marker clusters on rigid shells were also placed over the sacrum, bilateral shank and thigh segments, and posterior aspect of the shoe (38). All participants wore the same shoes (Pegasus; Nike, Beaverton, OR) during testing to standardize footwear conditions.

After marker placement and before running trials, a 1-s static calibration trial was recorded with the participant standing in a neutral position on the treadmill with their arms crossed over their chest (38). The neutral position was controlled using a graphic template placed on the treadmill, with the feet positioned 30 cm apart and pointing straight ahead (38). After the neutral trial, the markers on the anatomical landmarks were removed, whereas the segment markers remained (38). The participants were instructed to run on the treadmill at a comfortable self-selected pace, between 1.82 and 3.14 m·s−1. The self-selected pace was identified during the participants’ warm-up, where they ran for a minimum of 3 min and the speed of the treadmill was adjusted to their typical or comfortable endurance training pace. No differences were identified between groups for running speed (see Table 1). All participants were experienced treadmill users and were permitted as much time as they required to familiarize themselves with the treadmill before data collection. Data were collected for 60 s during which approximately 30–40 consecutive running strides were extracted over a 20-s period for analysis.

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Data analysis

Three-dimensional hip, knee, and ankle joint kinematics were calculated using 3D GAIT custom software (Running Injury Clinic Inc, Calgary, Alberta, Canada). The stance phase of each stride was extracted and normalized to 101 data points (i.e., 0%–100% of stance). Stance phase was defined as initial ground contact to toe-off. Initial ground contact was identified using the minimum vertical position of the heel marker, and toe-off was defined as the point of peak knee extension (39). Mean hip, knee, and ankle joint kinematic waveform data were calculated for each participant and used in subsequent analyses.

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Statistical analysis

The extracted kinematic waveform data were submitted to PCA to identify the kinematic patterns across each joint (hip, knee, and ankle) and plane (sagittal, frontal, and transverse). Kinematic data were arranged in nine separate 196 × 101 data matrices (196 participants × 101 time points per stance phase) for the PCA procedure. The n number of principal patterns (PP) that summed to explain at least 95% of the variation in the waveform were retained and referred to as PP1, PP2,…, PPn. PP scores, which measure the degree to which the shape of the waveform corresponds to each pattern (40), were then computed for each participant across the retained patterns. Before further analyses, a 3 × 2 (group–sex) ANOVA was conducted on all of the calculated PP scores to determine whether individual discriminant models between groups were required for both men and women, or whether sex could be collapsed within groups. Statistically significant (P < 0.05) main effects were identified for group and sex across most variables. However, no statistically significant group–sex interaction effects (P > 0.2 across all variables) were observed across any of the PP scores. These results determined that sex-specific differences did not need to be considered between groups. Overall group differences in PP scores were assessed using a one-way ANOVA. Tukey post hoc tests were used to examine pairwise differences between groups where ANOVA revealed a statistically significant difference. A Bonferroni correction based on the number of comparisons being made within variables was applied to an initial alpha level of 0.05, resulting in an alpha level of 0.017 being used for statistical tests.

Three separate backward selection, stepwise linear discriminant models were calculated between all combinations of groups (i.e., control vs acute, control vs chronic, acute vs chronic), with the PP scores showing statistically significant pairwise differences from ANOVA and post hoc analyses used as the input variables within the models. Discriminant models were used in the present study because these have been successfully used to identify discriminating gait features between acute and chronic lower limb osteoarthritis sufferers (41). The stepwise selection procedure simplified the models and identified the PP scores that had the greatest discriminatory power, by sequentially removing measures that did not affect the models’ classification rate of participants into the appropriate group. The PP scores that remained within the models were used to define optimal boundaries of separation between the groups (41). The magnitude of a PP score–normalized coefficient from the linear discriminant model indicated its relative importance in group separation (40,41). Group separation and the accuracy of the discriminant models were quantified by the misclassification rate determined via “leave-one-out” cross-validation.

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Hip, knee, and ankle joint kinematic data from the three groups are presented in Figure 1.



ANOVA and post hoc testing revealed seven PP score differences between the control and acute groups, eight between the control and chronic groups, and three between the acute and chronic groups (P < 0.017). Discriminant models separating the control and acute PFP (Wilk λ = 0.765; χ2 = 31.5; P < 0.001), control and chronic PFP groups (Wilk λ = 0.734; χ2 = 50.9; P < 0.001), and acute and chronic PFP groups (Wilk λ = 0.805; χ2 = 20.5; P < 0.001) were all statistically significant. Cross-validation misclassification error rates were 19.5% between the control and acute groups, 26.9% between the control and chronic groups, and 23.5% between the acute and chronic groups.

The stepwise discrimination procedure distinguished between the control and acute groups using five PPs (see Table 2). The most discriminatory features between runners in the control and acute groups were at the ankle in the transverse and sagittal plane, and knee in the sagittal plane. Runners in the acute PFP subgroup displayed greater transverse plane ankle range of motion, with greater peak ankle external rotation; greater ankle dorsiflexion from 0% to 10% of the stance phase; and greater overall knee flexion compared with runners in the control group. Reduced transverse plane hip range of motion and greater ankle dorsiflexion over the first 50% of stance were also observed in acute PFP runners compared with controls; however, these differences had less discriminatory power. Three of the five PPs that distinguished between the acute and control groups were also used in the model separating the chronic and control groups. Runners in the chronic PFP subgroup displayed greater ankle dorsiflexion from 0% to 10% of the stance phase, greater overall knee flexion, and greater ankle dorsiflexion over the first 50% of stance when compared with runners in the control group. Five additional PPs were also used in the discriminant model separating the chronic and control groups (see Table 3). Runners in the chronic PFP subgroup displayed greater peak knee flexion during midstance; reduced peak ankle eversion from approximately 20% to 60% of stance; reduced overall ankle eversion; greater frontal plane hip range of motion, with greater peak hip adduction; and greater overall knee abduction compared with runners in the control group. The measures with the greatest discriminatory power between the chronic PFP and control groups were at the ankle in the sagittal and frontal planes, knee in the sagittal plane, and hip in the frontal plane. Two PPs optimally separated the acute and chronic PFP subgroups (see Table 4). Runners in the acute PFP subgroup displayed greater transverse plane hip range of motion and greater overall ankle eversion compared with runners in the chronic PFP subgroup. The specific contribution of each PP to group separation within the three linear discriminant models is indicated by the normalized linear discriminant function coefficients included in Tables 2–4.







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The purpose of this study was to investigate the discriminating gait kinematics between individuals with acute versus chronic PFP and healthy controls. Similarities were evident in the discriminant models that separated the control group from both the acute and chronic PFP subgroups. For example, individuals with acute and chronic PFP demonstrated greater overall knee flexion across stance and greater ankle dorsiflexion in the early stages (0%–10% and 0%–50%) of stance relative to those without PFP. The greater dorsiflexion exhibited by those with PFP likely stemmed from the larger knee flexion angle as the tibia advanced over the foot in stance. Greater knee flexion increases patellofemoral compressive loads, which can increase overall contact stress (6,7), whereas reducing knee flexion during running has been shown to decrease patellofemoral joint stress (7). Our findings suggest that larger knee flexion angles distinguish between those with and without PFP and this gait characteristic is maintained with chronic pain. It seems that moderation of knee flexion angle via gait retraining programs may be a viable target regardless of the individual’s duration of pain. Training programs targeting a reduced step rate (42,43) have been effective in reducing peak knee flexion during running in those with PFP and could therefore be considered a viable approach.

Various differences were present in the models separating the acute versus chronic PFP subgroups with the healthy controls. Runners with acute PFP exhibited greater transverse plane hip motion across stance (i.e., greater shift from external to internal hip rotation across stance) compared with both the control and chronic PFP groups. In contrast, runners with chronic PFP exhibited greater frontal plane hip motion across stance (i.e., greater shift from neutral to hip adduction and back across stance) compared with controls. Increases in both hip adduction and internal rotation can increase the magnitude of stress placed on the lateral aspect of the patella (11,12). Gait retraining programs should therefore focus on minimizing both of these hip motions in runners with PFP. However, a specific focus on transverse versus frontal plane hip motion may be more beneficial for acute and chronic PFP sufferers, respectively. Noehren et al. (44) observed reductions in hip adduction during running with a program using real-time visual feedback targeting this motion, with this change persisting at 1-month follow-up. The difficulty of this method of gait retraining is that it relies on sophisticated laboratory equipment. A simpler method of gait retraining using a mirror has also been effective in reducing hip adduction immediately after training and at up to 3 months of follow-up (45). Given the findings of the present study, these forms of intervention may be particularly useful for those with chronic PFP.

There are variable findings across the literature pertaining to how PFP alters hip kinematics (15,19,46). Although greater peak hip adduction during running has been reported in those with PFP compared with healthy controls (15,46), others have found no difference in hip adduction between these cohorts (19). Similarly, peak hip internal rotation has been reported to be greater (19) in those with PFP compared with healthy controls, whereas other studies have shown that peak hip internal rotation in those with PFP is less than (15) or not different from (46) healthy controls. The sex of the participants across these studies may provide an explanation for these inconsistent findings. The study by Dierks et al. (46) included only five men and did not analyze their results on the basis of on sex, whereas the studies by Souza and Powers (19) and Willson and Davis (15) focused on women in isolation. In comparison to healthy controls and men with PFP, women with PFP have been shown to elicit greater peak hip adduction, but not internal rotation during running (47). The duration of PFP may also explain the variable findings. In the aforementioned studies, the duration of pain was either not reported (15,19) or reported to be greater than 2 months (46) or 3 months (47). The present study found that those with chronic PFP demonstrated greater peak hip adduction but less transverse plane hip range of motion compared with those with acute PFP. However, there was no group–sex interaction, which suggests that the effect of chronicity on gait kinematics occurs independent of sex (i.e., similar changes are observed from acute to chronic states across sexes). Nonetheless, future studies comparing runners with PFP to healthy controls may benefit from focusing on a specific subgroup (i.e., acute or chronic) or use a similar subgroup approach (i.e., male or female participants), particularly when a focus on hip kinematics is required.

Runners with acute PFP also exhibited greater transverse plane ankle range of motion across stance (i.e., greater shift from internal to external rotation and back across stance) compared with controls. To the authors’ knowledge, there is no evidence linking transverse plane ankle motion during running to patellofemoral joint loads or stress, or to the development of PFP. Therefore, it is difficult to hypothesize whether this gait pattern is a contributing factor to the pathology, or whether it is a beneficial or detrimental early adaptation to PFP.

A greater number of discriminating factors were present in the control–chronic PFP model in comparison with the control–acute PFP model. There are a number of potential reasons for these findings. First, the reduced number of discriminatory factors in the control–acute PFP model could suggest that this group’s pain developed from short-term training errors rather than underlying biomechanical factors leading to chronic pain. Second, the additional factors within the control–chronic PFP model could be related to the development of compensatory gait changes in response to prolonged pain. Finally, these differences may represent additional detrimental strategies that contribute to the ongoing pain experienced by these individuals. The findings from the present study suggest a mixture of these reasons. Additional patterns that discriminated the chronic PFP sufferers from healthy controls included greater knee abduction and reduced ankle eversion/greater ankle inversion across stance. Tibiofemoral rotation and knee abduction can induce lateral patellar tracking, increasing lateral patellofemoral joint stress (8,9). Subsequently, the increased knee abduction demonstrated by those with chronic PFP may contribute to their prolonged pain. In contrast, excessive eversion has been linked to increased internal tibial rotation (48,49). Therefore, those with chronic PFP may be using this frontal plane ankle strategy to minimize stress placed on the patellofemoral joint. Nonetheless, the specific gait parameters targeted in a program directed toward chronic PFP must be carefully considered to ensure that detrimental gait patterns are targeted, while ensuring gait patterns that have emerged to alleviate pain remain.

The strongest discriminators between groups tended to be the PPs that explained a smaller proportion of variance in the waveform data. For example, the strongest discriminators in the control–acute PFP model were PP3 for ankle internal/external rotation and PP4 for plantarflexion/dorsiflexion, which explained only 3.7% and 5.8% of the respective kinematic waveforms. Similarly, PP4 for ankle plantarflexion/dorsiflexion (5.8%), PP3 for knee flexion/extension (6.8%), and PP3 for ankle eversion/inversion (7.2%) were the strongest discriminators in the control–chronic PFP model. Similar findings have been made in a comparable study using a PCA and discriminant analysis approach to distinguish gait characteristics between individuals with different levels of knee osteoarthritis severity (41). Furthermore, Phinyomark et al. (50) found that changes in gait biomechanics associated with reductions in self-reported pain in runners with PFP were only detected by smaller-variance PPs. The findings from the present study suggest that small variations in gait kinematics may be important distinguishing factors between runners with and without PFP. Although small alterations to an individual’s gait pattern may only lead to minor changes in PF joint loads, these may still have important clinical implications. For example, Powers et al. (51) demonstrated that a small reduction in patellofemoral joint stress (~1 MPa) resulted in an immediate reduction in pain during walking. Similarly, small reductions in patellofemoral joint reaction force (0.3 BW) during running have been associated with improved symptoms and function in individuals with PFP (52). Therefore, targeting minor or subtle aspects of an individual’s gait pattern may have an important effect within a gait retraining program.

A limitation of this study is the cross-sectional nature of the data used. Although we were able to detect differences between the healthy, acute, and chronic PFP groups, we could not examine causality. Our findings do suggest that the biomechanical differences identified between the acute and chronic PFP subgroups are likely related to pain duration rather than severity, because both subgroups reported the same moderate levels (35) of pain and disability (see Table 1). Because of this, we cannot conclude whether the gait patterns identified in those with PFP represent a causative link to the presence of pain, or whether these gait patterns are an adaptive response to the presence of pain. However, the finding of increased hip adduction in the chronic PFP subgroup does agree with a prospective study linking greater hip adduction to the development of PFP (6). Further prospective studies, with a particular focus on the longitudinal monitoring of running biomechanics in conjunction with pain monitoring, may help determine the relationship between other biomechanical differences identified in this study and pain development, and/or pain persistence. Monitoring biomechanical and pain adaptations in response to gait retraining in individuals with PFP may also assist in determining whether certain changes are useful for the management of PFP.

Although pain duration was examined in an ordinal manner for this study (i.e., acute vs chronic PFP subgroups), pain duration may also be viewed on a continuous scale. Using regression-based methods to examine the time-course response of gait biomechanics to PFP can provide further insight into when specifically tailored gait retraining programs should be implemented. Although there was a large range of pain duration for participants within this study (0.5–120 months), there was a skew toward a longer duration of pain within the chronic group (i.e., most participants in the chronic PFP group had a pain duration greater than 2 yr). This made it difficult to yield insight into the potential linear or nonlinear adaptations to gait biomechanics with increasing pain duration. Future studies incorporating longitudinal monitoring of gait biomechanics as PFP duration continues, or those with a more balanced cohort may provide further insight into the time-course response and identify specific time points where gait retraining may be most valuable.

Misclassification error rates of 19.5%, 26.9%, and 23.5% were observed for the models separating control–acute PFP, control–chronic PFP, and acute PFP–chronic PFP, respectively. These rates are mostly higher than those seen previous studies using a similar design to identify the discriminating gait characteristics between those with moderate and severe knee osteoarthritis and healthy controls (range, 6.6%–21.7%) (41). However, the study by Astephen and colleagues (41) included both kinetic and electromyography data in addition to kinematics during gait. The inclusion of joint moment and muscle activation data within the present study may have further separated the three groups and improved the misclassification error rates. Future studies investigating the differences between PFP subgroups may benefit from the inclusion of these data.

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The present study identified kinematic gait characteristics that discriminated between individuals with acute and chronic PFP when compared with healthy controls. Greater overall knee flexion was a discriminating factor that was shared between both the acute and chronic subgroups when compared with healthy controls. In contrast, other biomechanical differences were specific to the duration of PFP. Greater hip adduction was identified in runners with chronic PFP, whereas runners with acute PFP demonstrated greater transverse plane hip and ankle motion. The findings from this study can assist in designing more specifically targeted programs relative to an individual’s duration of PFP.

No external funding was received for the undertaking of this study or production of this article. All authors declare no conflict of interest. The authors declare that the results of this study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of this study do not constitute endorsement by the American College of Sports Medicine.

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1. Neal BS, Barton CJ, Gallie R, O’Halloran P, Morrissey D. Runners with patellofemoral pain have altered biomechanics which targeted interventions can modify: a systematic review and meta-analysis. Gait Posture. 2016;45:69–82.
2. Crossley K, Bennell K, Green S, McConnell J. A systematic review of physical interventions for patellofemoral pain syndrome. Clin J Sport Med. 2001;11(2):103–10.
3. Powers CM. The influence of abnormal hip mechanics on knee injury: a biomechanical perspective. J Orthop Sports Phys Ther. 2010;40(2):42–51.
4. Ho KY, Hu HH, Colletti PM, Powers CM. Running-induced patellofemoral pain fluctuates with changes in patella water content. Eur J Sport Sci. 2014;14(6):628–34.
5. Draper CE, Fredericson M, Gold GE, et al. Patients with patellofemoral pain exhibit elevated bone metabolic activity at the patellofemoral joint. J Orthop Res. 2012;30(2):209–13.
6. Noehren B, Hamill J, Davis I. Prospective evidence for a hip etiology in patellofemoral pain. Med Sci Sports Exerc. 2013;45(6):1120–4.
7. Bonacci J, Vicenzino B, Spratford W, Collins P. Take your shoes off to reduce patellofemoral joint stress during running. Br J Sports Med. 2014;48(6):425–8.
8. Powers CM. The influence of altered lower-extremity kinematics on patellofemoral joint dysfunction: a theoretical perspective. J Orthop Sports Phys Ther. 2003;33(11):639–46.
9. Salsich GB, Perman WH. Patellofemoral joint contact area is influenced by tibiofemoral rotation alignment in individuals who have patellofemoral pain. J Orthop Sports Phys Ther. 2007;37(9):521–8.
10. Barton CJ, Levinger P, Webster KE, Menz HB. Walking kinematics in individuals with patellofemoral pain syndrome: a case–control study. Gait Posture. 2011;33(2):286–91.
11. Huberti HH, Hayes WC. Patellofemoral contact pressures. the influence of q-angle and tendofemoral contact. J Bone Joint Surg. 1984;66(5):715–24.
12. Li G, DeFrate LE, Zayontz S, Park SE, Gill TJ. The effect of tibiofemoral joint kinematics on patellofemoral contact pressures under simulated muscle loads. J Orthop Res. 2004;22(4):801–6.
13. Bazett-Jones DM, Cobb SC, Huddleston WE, O’Connor KM, Armstrong BS, Earl-Boehm JE. Effect of patellofemoral pain on strength and mechanics after an exhaustive run. Med Sci Sports Exerc. 2013;45(7):1331–9.
14. Esculier JF, Roy JS, Bouyer LJ. Lower limb control and strength in runners with and without patellofemoral pain syndrome. Gait Posture. 2015;41(3):813–9.
15. Willson JD, Davis IS. Lower extremity mechanics of females with and without patellofemoral pain across activities with progressively greater task demands. Clin Biomech (Bristol, Avon). 2008;23(2):203–11.
16. Dierks TA, Manal KT, Hamill J. Lower extremity kinematics in runners with patellofemoral pain during a prolonged run. Med Sci Sports Exerc. 2011;43(4):693–700.
17. Noehren B, Pohl MB, Sanchez Z, Cunningham T, Lattermann C. Proximal and distal kinematics in female runners with patellofemoral pain. Clin Biomech (Bristol, Avon). 2012;27(4):366–71.
18. Noehren B, Sanchez Z, Cunningham T, McKeon PO. The effect of pain on hip and knee kinematics during running in females with chronic patellofemoral pain. Gait Posture. 2012;36(3):596–9.
19. Souza RB, Powers CM. Differences in hip kinematics, muscle strength, and muscle activation between subjects with and without patellofemoral pain. J Orthop Sports Phys Ther. 2009;39(1):12–9.
20. Duffey MJ, Martin DF, Cannon DW, Craven T, Messier SP. Etiologic factors associated with anterior knee pain in distance runners. Med Sci Sports Exerc. 2000;32(11):1825–32.
21. Davis IS, Powers CM. Patellofemoral pain syndrome: proximal, distal, and local factors—an international retreat. April 30–May 2, 2009, Fells Point, Baltimore, MD. J Orthop Sports Phys Ther. 2010;40(3):A1–16.
22. Blønd L, Hansen L. Patellofemoral pain syndrome in athletes: a 5 to 7-year retrospective follow-up study of 250 athletes. Acta Orthop Belg. 1998;64(4):393–400.
23. Kannus P, Natri A, Paakkala T, Järvinen M. An outcome study of chronic patellofemoral pain syndrome: seven-year follow-up of patients in a randomized, controlled trial. J Bone Joint Surg. 1999;81(3):355–63.
24. Lankhorst NE, Bierma-Zeinstra SM, van Middelkoop M. Factors associated with patellofemoral pain syndrome: a systematic review. Br J Sports Med. 2013;47(4):193–206.
25. Nimon G, Murray D, Sandow M, Goodfellow J. Natural history of anterior knee pain: a 14- to 20-year follow-up of nonoperative management. J Pediatr Orthop. 1998;18(1):118–22.
26. Stathopulu E, Baildam E. Anterior knee pain: a long-term follow-up. Rheumatology (Oxford). 2003;42(2):380–2.
27. Thomas MJ, Wood L, Selfe J, Peat G. Anterior knee pain in younger adults as a precursor to subsequent patellofemoral osteoarthritis: a systematic review. BMC Musculoskelet Disord. 2010;11:201.
28. Utting MR, Davies G, Newman JH. Is anterior knee pain a predisposing factor to patellofemoral osteoarthritis? Knee. 2005;12(5):362–5.
29. Liao TC, Yang N, Ho KY, Farrokhi S, Powers CM. Femur rotation increases patella cartilage stress in females with patellofemoral pain. Med Sci Sports Exerc. 2015;47(9):1775–80.
30. Barton CJ, Lack S, Hemmings S, Tufail S, Morrissey D. The ‘Best Practice Guide to Conservative Management of Patellofemoral Pain’: incorporating level 1 evidence with expert clinical reasoning. Br J Sports Med. 2015;49(14):923–34.
31. Richter C, O’Connor NE, Marshall B, Moran K. Comparison of discrete-point vs. dimensionality-reduction techniques for describing performance-related aspects of maximal vertical jumping. J Biomech. 2014;47(12):3012–7.
32. Donoghue OA, Harrison AJ, Coffey N, Hayes K. Functional data analysis of running kinematics in chronic Achilles tendon injury. Med Sci Sports Exerc. 2008;40(7):1323–35.
33. Donà G, Preatoni E, Cobelli C, Rodano R, Harrison AJ. Application of functional principal component analysis in race walking: an emerging methodology. Sports Biomech. 2009;8(4):284–301.
34. Kujala UM, Jaakkola LH, Koskinen SK, Taimela S, Hurme M, Nelimarkka O. Scoring of patellofemoral disorders. Arthroscopy. 1993;9(2):159–63.
35. Crossley KM, Bennell KL, Cowan SM, Green S. Analysis of outcome measures for persons with patellofemoral pain: which are reliable and valid? Arch Phys Med Rehabil. 2004;85(5):815–22.
36. Thorstensson CA, Andersson ML, Jönsson H, Saxne T, Petersson IF. Natural course of knee osteoarthritis in middle-aged subjects with knee pain: 12-year follow-up using clinical and radiographic criteria. Ann Rheum Dis. 2009;68(12):1890–3.
37. Pohl MB, Lloyd C, Ferber R. Can the reliability of three-dimensional running kinematics be improved using functional joint methodology? Gait Posture. 2010;32(4):559–63.
38. Phinyomark A, Osis S, Hettinga BA, Ferber R. Kinematic gait patterns in healthy runners: a hierarchical cluster analysis. J Biomech. 2015;48(14):3897–904.
39. Fellin RE, Rose WC, Royer TD, Davis IS. Comparison of methods for kinematic identification of footstrike and toe-off during overground and treadmill running. J Sci Med Sport. 2010;13(6):646–50.
40. Deluzio KJ, Astephen JL. Biomechanical features of gait waveform data associated with knee osteoarthritis: an application of principal component analysis. Gait Posture. 2007;25(1):86–93.
41. Astephen JL, Deluzio KJ, Caldwell GE, Dunbar MJ, Hubley-Kozey CL. Gait and neuromuscular pattern changes are associated with differences in knee osteoarthritis severity levels. J Biomech. 2008;41(4):868–76.
42. Heiderscheit BC, Chumanov ES, Michalski MP, Wille CM, Ryan MB. Effects of step rate manipulation on joint mechanics during running. Med Sci Sports Exerc. 2011;43(2):296–302.
43. Lenhart RL, Thelen DG, Wille CM, Chumanov ES, Heiderscheit BC. Increasing running step rate reduces patellofemoral joint forces. Med Sci Sports Exerc. 2014;46(3):557–64.
44. Noehren B, Schoz J, Davis I. The effect of real-time gait retraining on hip kinematics, pain and function in subjects with patellofemoral pain syndrome. Br J Sports Med. 2011;45(9):691–6.
45. Willy RW, Scholz JP, Davis IS. Mirror gait retraining for the treatment of patellofemoral pain in female runners. Clin Biomech (Bristol, Avon). 2012;27(10):1045–51.
46. Dierks TA, Manal KT, Hamill J, Davis IS. Proximal and distal influences on hip and knee kinematics in runners with patellofemoral pain during a prolonged run. J Orthop Sports Phys Ther. 2008;38(8):448–56.
47. Willy RW, Manal KT, Witrouv EE, Davis IS. Are mechanics different between male and female runners with patellofemoral pain? Med Sci Sports Exerc. 2012;44(11):2165–71.
48. Pohl MB, Messenger N, Buckley JG. Changes in foot and lower limb coupling due to systematic variations in step width. Clin Biomech (Bristol, Avon). 2006;21(2):175–83.
49. Nigg BM, Cole GK, Nachbauer W. Effects of arch height of the foot on angular motion of the lower extremities in running. J Biomech. 1993;26(8):909–16.
50. Phinyomark A, Hettinga BA, Osis S, Ferber R. Do intermediate- and higher-order principal components contain useful information to detect subtle changes in lower extremity biomechanics during running? Hum Mov Sci. 2015;44:91–101.
51. Powers CM, Ward SR, Chen YJ, Chan LD, Terk MR. The effect of bracing on patellofemoral joint stress during free and fast walking. Am J Sports Med. 2004;32(1):224–31.
52. Esculier JF, Bouyer LJ, Dubois B, et al. Is combining gait retraining or an exercise programme with education better than education alone in treating runners with patellofemoral pain? A randomised clinical trial. Br J Sports Med. 2017; doi:10.1136/bjsports-2016-096988.


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