Association between 3D knee kinematics and clinical phenotypes in people with Patellofemoral Pain Syndrome: a prospective comparative study

Association between 3D knee kinematics and clinical phenotypes in people with Patellofemoral Pain Syndrome: a prospective comparative study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association between 3D knee kinematics and clinical phenotypes in people with Patellofemoral Pain Syndrome: a prospective comparative study Marvin Coleman, Marie-Martine Lefèvre-Colau, Christelle Nguyen, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6906409/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Patellofemoral pain syndrome (PFPS) includes static and dynamic lower limb dysfunctions. We used a pragmatic classification differentiating 3 main clinical phenotypes: PFPS with 1) objective patellar displacement, 2) altered extra-patellar alignment, and 3) no altered alignment. Objective : To compare kinematic gait parameters associated with the 3 main clinical phenotypes. Method : Prospective comparative study. We used the KneeKG® device (EMOVI) to assess 3D femoro-tibial (FT) rotations during gait. We assessed static FT alignment using EOS imaging, foot posture and knee function using clinical tests, neuromuscular activity using EMG and an isokinetic device, and single-leg stability using posturography. Joint angle time series were compared between phenotypes using Statistical Parametric Mapping. We used the Kruskall-Wallis test (Dwass-Steel test for post-hoc analyses) for group comparisons, p<0.05. Results We included 45 participants: 29 (64.4%) females, mean (SD) age 36.3 (13.7) years, BMI: 22.9 (3.8) kg.m 2 , symptom duration: 8.1 (9.6) years. Four (9%) participants were classified as Phenotype 1, 25 (56%) as Phenotype 2 and 10 (22%) as Phenotype 3. Six (13%) participants fitted both Phenotypes 1 and 2; thus, we added Phenotype 4. Knee valgus angle during the gait loading phase differed significantly between phenotypes (p=0.03); Phenotypes 2 and 4 had the highest value (2.1 [1.9]° and 2.1 [2.3]°, respectively). Static knee valgus angle also differed (p=0.014), with Phenotype 4 having the highest value (3.6 [2.0]°). No other parameters differed between groups. Conclusion Increased knee valgus during the gait loading phase was the only kinematic parameter that differed significantly between the phenotypes. Knee valgus may differentiate PFPS phenotypes. Trial registration : NCT05441332 (ClinicalTrials.gov). Date of registration 14/06/2022, date of first publication 2022-07-01, date of last modification 2023-09-07. https://clinicaltrials.gov/study/NCT05441332?cond=Patello%20Femoral%20Syndrome&term=PHENOPAT&rank=1 Physical Medicine & Rehab Biomedical Engineering Patellofemoral pain syndrome 3D kinematics clinical phenotypes dynamic alterations. Figures Figure 1 Figure 2 Figure 3 Background Patellofemoral Pain Syndrome (PFPS) is a common condition in the general population, with an annual prevalence of 22.7% ( 1 ). This syndrome represents 17% of general practitioner consultations for knee injuries ( 2 ). PFPS is particularly common in young, physically active women ( 2 – 5 ). Rehabilitation is the first-line treatment for PFPS ( 5 ) but more than 50% of individuals with PFPS develop chronic pain, and two-thirds still have symptoms 1 year after diagnosis ( 6 , 7 ). A common definition of PFPS is anterior knee pain located around or behind the patella and aggravated by activities that load or compress the patellofemoral joint ( 8 ). However, this definition is unspecific ( 9 ). PFPS is diagnosed by exclusion, using both clinical and imaging findings. There is a consensus to exclude femoro-tibial (FT) osteoarthritis and peri-articular pathologies from the diagnosis of PFPS ( 10 – 12 ). The pathophysiology of PFPS is considered to be multifactorial, including biomechanical factors ( 13 , 14 ). It is associated with both static and dynamic deficiencies of the hip, knee, and foot ( 15 ). The interactions between clinical symptoms, kinematics and neuromuscular deficiencies are poorly understood ( 16 , 17 ). Numerous classifications based on presumed contributing factors have been proposed. A multicentre observational study including 127 participants proposed a 3-group classification (weak and tighter, strong, weak and pronated) based on lower limb length and strength, patellar mobility and foot posture ( 18 ). The European Rehabilitation Panel determined 2 main categories: malalignment and muscular dysfunction, which were further subdivided into 5 etiological factors: malalignment of the entire lower limb, malalignment of the patellofemoral joint, loss of strength and flexibility, and neuromuscular changes ( 19 ). Another widely used classification from the American practice guidelines additionally includes overuse for people without lower limb malalignment or neuromuscular dysfunction ( 15 ). This classification describes 4 subcategories based on the predominant factors: muscle performance, movement coordination, mobility and overuse ( 15 ). These classifications are quite complex and involve many time consuming assessments, some of which require the use of specific measuring devices. Therefore, they cannot be performed during routine medical consultations. We used a pragmatic clinical classification based on biomechanical factors because we wanted to determine whether lower limb postural or movement alterations resulted in specific knee kinematic patterns. The clinical classification was divided into 3 main phenotypes. Phenotype 1: PFPS with objective displacement of the patella, Phenotype 2: PFPS with altered static and/or dynamic lower limb alignment, Phenotype 3: PFPS without altered alignment or objective displacement of the patella. Clinical tests cannot accurately assess knee 3D kinematics ( 15 ). Optoelectronic techniques are the gold standard method for kinematic assessment ( 20 ). The KneeKG® (EMOVI) is a non-invasive optoelectronic device that assesses 3D knee kinematics in real-time during gait. Several studies have demonstrated the validity and reproducibility of this system ( 21 – 25 ). Although PFPS symptoms are usually not aggravated by walking, walking is the most common human physical activity and is a good model for assessing dynamic repeated 3D knee rotations involving both single and double limb loading ( 26 ). Altered kinematic and kinetic gait patterns have been found in people with PFPS (27,28). Two main kinematic alterations have been found: decreased peak knee flexion during stance phase (specifically at heel contact) and decreased femoral medial rotation range of motion (RoM) ( 29 ). Increased knee abduction (valgus) during gait has been described in a subgroup of PFPS participants with higher pain levels ( 30 ). However, several studies found that knee abduction angle did not differ between people with PFPS and asymptomatic individuals during gait (27,29). Consensus regarding kinematic alterations during gait is thus lacking. The primary aim of this study was to describe and compare the kinematic alterations during gait (increased or decreased FT 3D rotation angles during stance) between the 3 main clinical phenotypes. The secondary aims were to describe and compare postural, neuromuscular and proprioceptive alterations between the 3 main clinical phenotypes. Our primary hypothesis was that each of the 3 PFPS phenotypes would show specific kinematic alterations. We expected that Phenotype 1 would be associated with decreased knee flexion/extension RoM during stance and that Phenotype 2 would be associated with increased knee valgus during stance and /or increased tibial medial rotation (especially during loading). We did not expect to find any specific kinematic alterations in Phenotype 3. Methods Study design We conducted a single-centre comparative, non-randomised interventional study (ClinicalTrials.gov Identifier: NCT05441332). We reported our study in accordance with the Strengthening the reporting of observational studies in Epidemiology ( Additional file 1 ) (31) and Template for Intervention Description and Replication ( Additional file 2 ) checklists (32), given the observational nature of our data analysis. Changes were made to the study protocol after the trial commencement to facilitate participant inclusion. The assessment could take place over 2 separate days, and the inclusion period was extended by 18 months. We did not change any outcomes after the trial had begun. Setting and participants The study was conducted in the physical medicine and rehabilitation (PMR) and the imaging department of Cochin Hospital, Paris, France. Participants were screened for eligibility during consultations at the orthopaedic, rheumatology, and 2 PMR (tertiary care) departments of Cochin Hospital, Paris, France and Corentin-Celton hospital, Issy-les-Moulineaux, France, general practice clinics and out-patient physiotherapy clinics. Information about the study was communicated by posters and flyers specifying the study objective, inclusion and non-inclusion criteria, and the assessment procedure. The baseline face-to-face visit was conducted by the principal investigator (MC), a physiotherapist (MSc) with 7 years of experience in PFPS rehabilitation and 5 years of research experience. During the year before the study commenced, the principal investigator performed the clinical and biomechanical examinations on 28 knees in asymptomatic individuals and 13 in individuals with various knee pathologies including PFPS. During that time, the KneeKG® 3D kinematic measurements made by MC were checked and validated by engineers from EMOVI. Inclusion and exclusion criteria The main inclusion criteria were: 1) age 18 to 70 years, and 2) diagnosis of PFPS based on symptom duration >1 month and pain rated ≥4/10 on the Numeric Rating Scale (NRS) during at least one of the following activities: stair climbing and/or descending, squatting, jumping, jogging, prolonged sitting and/or crouching. The main exclusion criteria were 1) a history or presence of neurological disorders affecting the lower limbs, 2) signs of FT osteoarthritis on x-ray, 3) a history of surgery or trauma to the lower limbs <1 year previously, and 4) intra-articular knee injection in the past 2 months. Experimental Protocol Development of the clinical classification The pragmatic classification was derived from the scientific literature (15,19) and clinical practice and based on the detection of biomechanical alterations in patellar displacement and lower-limb alignment by a clinician during a consultation. A committee of 3 Physical and Rehabilitation Medicine (PRM) physicians (MMLC, CN, CD) and 2 physiotherapists (AR, MC), all experts in the diagnosis and treatment of musculoskeletal pathologies, defined the clinical classification and selected the tests routinely used in clinical practice. Three main clinical phenotypes were defined: Phenotype 1: PFPS with objective displacement of the patella. This phenotype was identified on the following yes/no clinical signs: positive apprehension test, lateral displacement of the patella of >25% of its width, and positive J-sign. Phenotype 2: PFPS with static and/or dynamic lower limb alignment deficiencies. This phenotype was identified on the following yes/no clinical signs: static knee valgus and dynamic (increased) knee valgus during single-leg squat, recurvatum of the knee, Q-angle >15°, lower limb length discrepancy, and Navicular Drop test >1.1 cm. Phenotype 3: PFPS without alignment deficiency or objective displacement of the patella. This phenotype was identified by a lack of detectable biomechanical alterations on clinical inspection. Assessments Inclusion and assessments took place on the same day. The assessments could span over 2 different days according to participant preference and availability. After the physician (MMLC or CD) included and classified the participant’s phenotype using the approach described above, the principal investigator (MC) performed the data collection and assessments, beginning with the collection of demographic and clinical characteristics. The principal investigator (MC) and the participants were blinded to the phenotype classification that was performed by the physician (MMLC or CD). The data analysts (HA and CO) were blinded. All assessments were performed bilaterally on the asymptomatic or less symptomatic limb first. Only the symptomatic or most symptomatic limb was classified. The assessment order alternated physically demanding tests with more passive tests to avoid participant fatigue and according to the EOS imaging slot. Kinematic assessment The kinematic variables were measured using the KneeKG® optoelectronic device (Knee3DTM Software, EMOVI). This device includes a 3D infrared camera (Polaris Spectra, Northern Digital) and 3 tripod reflectors positioned on the arches above the femoral condyles and medial side of the tibia and on a belt facing the sacrum (Figure 1a). Data acquisition was performed on a treadmill. Participants walked on the treadmill for 5 to 10 minutes prior to recording to get used to the speed and the equipment and ensure that the sensors were well-attached and could always be detected by the camera. After a calibration procedure (Figure 1b), data were acquired at 60 Hz for 1 minute at the participant’s chosen (comfortable and usual) gait speed. The KneeKG® provides common knee gait parameters in the format of 3D kinematic curves (33). The mean accuracy is 0.4° for knee varus/valgus and 2.3° for axial rotations (25). Anonymised 3D knee kinematic data were checked by the engineers from EMOVI, who sought atypical data from incorrect estimation of the gait cycle initiation (34). This review identified 3 problematic analyses, which were then corrected. Postural, neuromuscular and proprioceptive assessment The clinical assessment included standard muscle length and strength tests routinely used to assess PFPS (15): hip, knee and ankle passive maximal RoM and hamstring and calf muscle tightness (in degrees) using a goniometer, and quadriceps tightness (in cm) using a measuring tape (35). The Ober’s test was used to evaluate iliotibial band tightness (36). Patellar mobility was assessed using the lateral apprehension test, the glide test, the lateral tilt test and the J sign (15,36–38). EOS imaging was performed on the same day (or the second day) in the radiology unit by a senior radiographer (JM) under the supervision of a senior radiologist, who were both blinded to the phenotype classification. The inter-observer reliability of lower extremity measurements using 2D EOS is excellent (39). FT alignment and the Q-angle (angle between the quadriceps muscle and the patella tendon representing the line of pull of the quadriceps relative to the patella) were measured using EOS lower limb imaging (40). We used the foot posture index and the Navicular Drop test (cm) to quantify foot pronation (15,41). The knee function assessment was performed using functional tests, EMG and isokinetic dynamometry. The Y balance test (Y test) was used to measure single limb dynamic balance expressed by the average distance reached in the 3 directions divided by the participant’s leg length, as a % (42), the forward step-down test to assess pain during functional movement (43), and the lateral step-down test (36) to evaluate movement quality. The activation times of the vastus medialis obliquus (VMO) and vastus lateralis (VL) were assessed using surface EMG (EMG Zerowire, Aurion). Hip and knee muscle strength and endurance were assessed using an isokinetic dynamometer (Humac NORM, CSMi, Stoughton, MA, Software HUMAC 2009, v.9.7.1). The isokinetic test was perfomed last as it required maximal effort and causes fatigue. All assessments are detailed in the study protocol (35). Single-leg postural stability was assessed on both lower extremities successively using a posturography platform (Posture Win Sabots, Technoconcept), the less symptomatic lower limb was assessed first. Outcomes Primary outcome The primary outcome included the following 3D knee rotations assessed (in degrees) by the KneeKG®: Mean increase in knee valgus (valgus thrust defined by a sudden lateral shift of the knee) during the loading phase of the gait, (0-20% of the gait cycle). It was measured as the difference between the peak valgus point and the valgus point at initial contact, Knee flexion/extension RoM during stance (20% to 54% of the gait cycle), Tibial medial rotation RoM during loading. Secondary outcomes 3D knee rotations: mean varus/valgus at initial contact and during stance, tibial lateral rotation RoM at initial contact and total tibial rotation RoM during the entire gait cycle, flexion/extension at initial contact, flexion/extension RoM during the entire gait cycle. Knee posture (FT alignment): knee valgus and Q-angle (angle formed between the quadriceps muscle and the patella tendon) measured using EOS imaging. Foot posture: The Foot Posture Index (FPI; -12; +12: -12: high supination, +12: high pronation, -2 ≤ normal scores ≤ 9)(44) and the Navicular Drop test, which measures the change in arch height from the sitting to the standing position (mm), a value >1.1 cm indicates excessive foot pronation (45). Knee function : the Y test (range 0-100+: 0: minimal dynamic balance, 100+: excellent dynamic balance): a mean composite score of 95.5% of leg length has been found in healthy recreational adult athletes (46), the forward step-down test (assessing pain during movement: yes/no question) and the lateral step-down test (assessing quality of movement: range 0-6 points, 0 and 1: good quality movement, 2 and 3: average quality movement, and 4 to 6: poor quality movement) (47). Neuromuscular activity : VMO activation delay (VL activation time minus VMO activation time, in ms) during the stand-up test. In asymptomatic individuals, the mean VMO activation delay during active knee extension is less than 4 milliseconds (48). Isokinetic strength (peak quadriceps and hamstrings torque and quadriceps/hamstrings ratio at 60°.s -1 ) and knee muscle endurance (quadriceps and hamstrings total work and quadriceps/hamstrings total work ratio at 180°.s -1 ) (N.m), hip abductor: gluteus medius isometric strength (N.m) and gluteus medius time to peak torque (s). Single-leg postural stability: total excursion (mm) and mean velocity (mm.s -1 ) of the centre of pressure (CoP) during posturography, eyes open (EO) and eyes closed (EC) for each lower limb. Other variables were collected for descriptive purposes: mean knee pain intensity and pain intensity during activities of daily living (ADL) the week before the test (NRS, range 0-100; 0: no pain; 100: worst pain imaginable); subjective symptoms and activity limitation using the Anterior Knee Pain Scale (AKPS) (range 0-100; 0: maximal symptoms, 100: no symptoms), quality of life using the 12-Item Short Form Survey (SF-12) (physical component summary score 9.95, minimum quality of life 70.02, maximum quality of life and mental component summary score 5.89, minimum quality of life 71.97, maximum quality of life), tightness of the main hip, knee and ankle muscles: hamstring and calf muscle tightness using joint angles (in degrees) and quadriceps using the heel-to-buttock distance (in cm). Statistical analysis Sample size calculation We did not find other studies comparing FT biomechanical alterations between people with different PFPS phenotypes. Based on recent studies comparing 3D FT kinematics between asymptomatic and OA knees with the KneeKG® device (49) and a literature review on biomechanical FT parameters during gait in participants with PFPS (17), we estimated that a sample size of 15 participants per group (45 participants in total) was appropriate to detect a difference in knee 3D kinematics between the 3 PFPS phenotypes. Statistical analysis Statistical analyses were performed using Systat 13 for Windows (Systat Software, Inc., Point Richmond, CA). Continuous data were expressed as means (SD) and standard deviations (SD) or 95% confidence intervals (CI) and medians (Q1, Q3) Categorical data were expressed as absolute and relative frequencies (n/N [%]). The normality of the data distribution was assessed using the Kolmogorov Smirnov test with Lilliefors correction. The kinematic variables used for the primary outcome and most other kinematic variables did not follow a normal distribution for any phenotype. Participants with the clinical characteristics of both phenotypes 1 and 2 were classed as Phenotype 4. Most clinical variables were not normally distributed. For clarity and to compare the current results with the literature, we chose to present both mean (SD) and median (Q1-Q3) values. A sensitivity analysis was performed by including the kinematic values of Phenotype 4 in both Phenotype 1 (Phenotype 1’) and 2 (Phenotype 2’). Joint angle time series were compared using Statistical Parametric Mapping (SPM). The SPM was computed using the SPM1D Python package (version 3.9.7) with permutation analysis (500 permutations). The Krsukall-Wallis test (with Dwass-Steel test for post-hoc analyses) was used to compare clinical and kinematic parameters between groups. All tests were two-tailed, with a p-value <0.05 considered significant. Results Demographic and clinical characteristics We included 45 participants between December 2022 and February 2024: 29 (64%) females, mean (SD) age 36.3 (13.7) years, BMI 22.9 (3.8) kg.m -2 and symptom duration 8.1 (9.6) years. Twenty-three participants/45 had unilateral symptoms. Four participants (9%) were classed as Phenotype 1, 25 (56%) as Phenotype 2, 10 (22%) as Phenotype 3, and 6 (13%) had both the clinical characteristics of phenotypes 1 and 2 and were classed as Phenotype 4 (Table 1, and Figure 2). The assessment lasted 3 to 5 hours, depending on the participant. The mean participant age was lower for Phenotype 1 (25.0 [5.5] years) than for the other phenotypes (Table 1). The mean NRS scores (37.5 [17.1]/100 for pain and 52.5 [34.0]/100 for pain during ADL) were higher in Phenotype 1 than in the other Phenotypes. The AKPS scores ranged from 60.8 (18.5)/100 for Phenotype 4 to 71.3 (16.5)/100 for Phenotype 3. Phenotype 3 had the highest SF-12 physical score: 44.5 (11.1), and Phenotype 2 had the lowest: 40.9 (10.4). All Phenotypes had knee hyperextension (goniometry), ranging from 3.0 (3.4)° for Phenotype 3 to 5.7 (4.5)° for Phenotype 4. The shortest heel-to-buttock distance was 1.4 (2.1) cm (Phenotype 3), and the longest was 6.0 (7.7) cm (Phenotype 1) (Table 1). Demographic and general clinical characteristics did not differ between the Phenotypes (Table 1). Table 1 . Demographic and clinical characteristics of participants with PFPS All groups (N=45) Phenotype 1 (n=4) Phenotype 2 (n=25) Phenotype 3 (n=10) Phenotype 4 (n=6) p-value Demographic characteristics Female n (%) 29 (64%) 3 (75%) 15 (60%) 6 (60%) 5 (83%) Age (years), mean (SD) 36.3 (13.7) 25.0 (5.5) 38.7 (14.5) 36.5 (14.9) 33.5 (9.9) 0.41 BMI (kg.m -2 ), mean (SD) 22.9 (3.8) 21.7 (2.9) 22.9 (3.9) 22.7 (2.9) 24.4 (5.3) 0.77 General clinical characteristics, mean (SD) Knee Pain (NS, 0-100) 28.9 (19.1) 37.5 (17.1) 30.4 (16.7) 20 (22.1) 31.7 (24.0) 0.24 Knee pain during ADL (NS, 0-100) 38.4 (23.4) 52.5 (34.0) 40.0 (22.7) 32.0 (23.5) 33.3 (19.7) 0.53 AKPS (0-100) 68.1 (14.2) 65.8 (6.5) 68.9 (13.2) 71.3 (16.5) 60.8 (18.5) 0.64 SF-12 Physical Score (9.95-70.02) 42.3 (9.7) 43.7 (6.1) 40.9 (10.4) 44.5 (11.1) 44.1 (7.0) 0.95 SF-12 Mental Score (5.89-71.97) 43.3 (9.6) 45.3 (5.7) 43.8 (9.6) 41.7 (13.1) 42.9 (5.2) 0.99 Symptoms duration, years 8.1 (9.6) 4.6 (4.4) 5.8 (5.7) 10.3 (15.4) 16.4 (9.6) 0.47 Current treatments (n) 1 Physical therapy 20 4 10 3 3 Self exercices 30 3 17 5 5 Insoles 19 4 9 3 3 Nonsteroïdal anti-inflammatory drugs 6 1 4 0 1 Analgesics Grade I 7 0 2 3 2 Analgesics Grade II 3 0 3 0 0 Knee and ankle mobility (Maximal RoM, in degrees) Knee Flexion 143.8 (8.8) 141.5 (10.1) 144.7 (5.7) 143.7 (5.6) 137.5 (18.9) 0.86 Knee Extension 2 4.1 (3.6) 4.5 (4.1) 3.7 (3.3) 3.0 (3.4) 5.7 (4.5) 0.60 Global knee axial rotation 3 44.7 (7.4) 45.0 (5.8) 44.0 (8.2) 42.1 (7.9) 45.0 (7.9) 0.94 Ankle dorsal flexion 35.3 (7.0) 38.5 (9.0) 33.4 (9.0) 34.3 (4.8) 36.3 (2.9) 0.63 Muscle length Hamstrings, popliteal angle (°) 160.9 (18.0) 162.5 (15.0) 160.0 (18.8) 159.0 (22.2) 168.0 (14.7) 0.83 Rectus femoris, heel-to-buttock distance (cm) 4.0 (7.8) 6.0 (7.7) 2.9 (6.1) 1.4 (2.1) 6.3 (15.0) 0.80 Triceps, ankle dorsal flexion (knee extended) (°) 33.6 (6.1) 33.0 (5.3) 33.0 (7.2) 30.5 (6.0) 35.0 (4.5) 0.35 BMI: body mass index; AKPS: Anterior Knee Pain Scale; SF-12: Medical Outcome Study Short Form 12; 1 The total number of current treatments exceeds the number of participants because one participant could have more than one treatment for PFPS; 2 Positive values mean hyperextension; RoM: range of motion; 3 Global knee axial rotation includes knee medial and lateral RoM. P value is for group (1,2,3,4) comparison (Kruskall-Wallis test) Kinematic variables during gait Mean (95% CI) increased knee valgus angle was 0.3 (-0.41; 0.96)° for Phenotype 1, 2.1 (1.24; 2.82)° for Phenotype 2, 0.5 (0.04; 1.01)° for Phenotype 3 and 2.1 (-0.06; 5.02)° for Phenotype 4, (p=0.03) (Table 2). The post-hoc analyses revealed significant differences between groups for all comparisons, except between Phenotypes 1 and 4 (p=0.97). There were no between-group differences for the 2 other primary outcomes: knee flexion/extension RoM during stance and tibial medial rotation RoM during loading (p>0.2) (Table 2). There were no between-group differences for the secondary kinematic outcomes at any point in the gait cycle (Table 2). The sensitivity analysis showed no further differences between Phenotypes 1’ (1+4), 2’ (2+4) and 3. The sensitivity analysis showed a between-group difference (1’, 2’ and 3) for increased knee valgus during gait loading (p=0.04); the post-hoc analyses showed significant differences between Phenotypes 1’ and 2’, 2’ and 3 but no difference between Phenotypes 1’ and 3 (p=0.78). Table 2 . Between-group comparison of kinematic knee variables during gait Kinematic knee variables, (in degrees) Symptomatic lower limbs all groups pooled (n=42) a,b Phenotype 1 (n=4) Phenotype 2 (n=24) a Phenotype 3 (n=9) b Phenotype 4 (n=5) b P value Contralateral lower limbs (n=42) Increased valgus during loading Mean (SD) 1.6 (1.8) 0.3 (0.4) 2.1 (1.9) 0.5 (0.6) 2.1 (2.3) 0.03 1.3 (0.9) Median (Q1, Q3) 1.0 (0.2, 2.3) 0.1 (0, 0.4) 1.4 (0.6, 3.3) 0.2 (0, 1.3) 1.1 (0.3, 4.5) 0.9 (0.4, 1.7) Flexion RoM during stance Mean (SD) 14.2 (8.6) 7.2 (4.9) 16.7 (9.0) 11.4 (8.1) 12.7 (7.4) 0.21 14.2 (6.1) Median (Q1, Q3) 11.9 (8.0, 20.7) 7.5 (3.8, 10.9) 16.4 (9.3, 23.9) 10.4 (6.2, 17.5) 10.1 (7.8, 19.0) 14.1 (8.7, 18.8) Tibial medial RoM during loading Mean (SD) 4.7 (2.8) 5.4 (2.9) 4.6 (2.5) 4.3 (2.6) 3.9 (3.5) 0.78 3.6 (2.2) Median (Q1, Q3) 4.3 (2.6, 6.2) 4.7 (3.7, 6.4) 4.5 (2.6, 6.3) 4.7 (2.9, 5.8) 3.2 (1.4, 4.0) 3.5 (2.0, 4.4) Varus/valgus at initial contact Mean (SD) 2.1 (5.0) -0.7 (4.2) 2.8 (5.7) 1.8 (4.2) 1.9 (3.9) 0.72 2.5 (4.3) Median (Q1, Q3) 2.1 (-1.1, 3.9) -0.4 (-3.9, 2.8) 2.3 (0.1, 4.8) 1.8 (0.3, 4.6) 3.2 (1.1, 4.5) 2.3 (-0.8, 5.6) Varus/valgus during stance Mean (SD) 1.3 (3.8) 2.7 (3.1) 1.8 (4.0) 0.7 (3.8) 0.8 (3.7) 0.86 1.8 (3.6) Median (Q1, Q3) 1.3 (-0.6, 2.9) 2.9 (1.9, 3.7) 1.5 (-0.6, 2.9) 0.9 (-0.1, 2.6) 0.5 (0.2, 3.3) 1.6 (-1.9, 5.6) Tibial lateral rotation at initial contact Mean (SD) 3.8 (4.0) 3.9 (6.6) 2.7 (2.8) 4.6 (2.4) 5.1 (5.69) 0.27 2.2 (2.5) Median (Q1, Q3) 3.6 (1.4, 5.5) 2.4 (-0.3, 6.6) 2.9 (1.5, 3.9) 5.0 (4.5, 6) 3.3 (1.7, 5.5) 2.2 (0.8, 4.7) Tibial rotation RoM during the entire gait cycle Mean (SD) 13.4 (5.1) 12.5 (3.0) 12.9 (4.3) 13.8 (4.5) 14.6 (10.1) 0.96 14.4 (4.1) Median (Q1, Q3) 13.0 (10.0, 16.0) 12.0 (10.0, 14.5) 12.5 (10.8, 16.3) 15.0 (10.0, 16.0) 13.0 (8.0, 13.0) 14.0 (10.0, 17.0) Flexion/extension at initial contact Mean (SD) 10.6 (8.9) 5.0 (4.6) 12.4 (10.3) 9.7 (7.7) 8.3 (5.4) 0.47 9.8 (5.8) Median (Q1, Q3) 8.5 (4.8, 15.1) 5.7 (2.4, 8.2) 10.4 (5.5, 19.7) 8.3 (4.5, 13.8) 7.9 (6.3, 9.7) 8.8 (5.0, 14.0) Flexion RoM during loading Mean (SD) 5.0 (4.1) 8.8 (4.7) 4.4 (4.1) 4.0 (3.4) 6.8 (4.4) 0.18 5.8 (4.2) Median (Q1, Q3) 4.5 (1.3, 7.8) 8.2 (6.8, 10.2) 3.3 (1.1, 7.6) 3.6 (0.9, 6.1) 6.7 (6.6, 8.7) 5.5 (1.1, 9.5) Flexion-extension RoM during the entire gait cycle Mean (SD) 60.9 (11.0) 61.8 (2.2) 62.8 (8.0) 56.3 (18.4) 63.2 (7.2) 0.73 62.2 (5.4) Median (Q1, Q3) 64.5 (59.8, 68.0) 62.0 (60.5, 63.3) 65.0 (61.0, 67.3) 64.0 (54.0, 65.0) 67.0 (56.0, 67.0) 63.7 (58.5, 66.8) SPM analysis showed no significant differences between the kinematic curves in the coronal, sagittal or transverse planes during gait; all F -values were below the significance threshold ( F =4.45 in the coronal plane, F =4.97 in the sagittal plane and F =4.45 in the transversal plane) (Figure 3). Clinical variables Knee posture (FT alignment) The static knee valgus angles measured on EOS images were statistically different between phenotypes (p=0.01). Phenotype 4 had the highest knee valgus value: 3.6 (1.95)°, and Phenotype 1 had the lowest: 1.0 (0.82)°. There were no significant differences between phenotypes for other clinical variables (all P>0.07). The mean Q-angle values ranged 4.7 (2.4)° for Phenotype 3 to 6.3 (2.8)° for Phenotype 4 ( Additional file 3 - Supplementary Table ). Foot posture All participants had normal FPI scores and 38/45 (4/4 in Phenotype 1, 21/25 in Phenotype 2, 9/10 in Phenotype 3, and 4/6 in Phenotype 4) had a pronated foot. All mean Navicular Drop test scores were <1.1 cm. The Navicular Drop test was negative for all participants in Phenotype 1, and positive for 6/25 participants in Phenotype 2, 2/10 in Phenotype 3 and 2/6 in Phenotype 4 ( Additional file 3 ). Knee function Good quality movement was found in 3/4 (75%) participants in Phenotype 1, 14/25 (56%) in Phenotype 2, 5/9 (56%) in Phenotype 3 and 4/6 (67%) in Phenotype 4. Average quality movement was observed in 1/4 (25%) participants in Phenotype 1, 9/25 (36%) in Phenotype 2, 4/9 (44%) in Phenotype 3, and 2/6 (33%) in Phenotype 4. Poor quality movement was found in 2/25 (8%) participants in Phenotype 2 and none in the other phenotypes ( Additional file 3 ). Neuromuscular activity The VMO was activated after the VL in 3/4 phenotypes. The longest VMO activation delay was -23.0 (66.0) ms (Phenotype 4). In Phenotype 1, the VMO was activated 8.2 (36.3) ms before the VL ( Additional file 3 ). The isokinetic strength and endurance and isometric values were similar between Phenotypes 1, 2 and 3, and Phenotype 4 had slightly lower values than the other groups. The mean total work Q/H ratios were ≥ 95.3 in all groups ( Additional file 3 ). Postural stability : Phenotype 2 had the highest total CoP excursion (758.5 [237.3] mm) and mean velocity (111.9 [158.2] mm.s -1 ). Phenotype 1 had the highest total CoP excursion: 264.8 (67.5) mm, and Phenotype 2 had the highest mean velocity: 27.5 (8.2) mm.s -1 in the EO condition. Phenotype 4 had the lowest mean velocity and total CoP excursion in both the EC and EO conditions ( Additional file 3 ). Contralateral lower limb variables Most kinematic and clinical variable values were similar between the contralateral lower limbs and the symptomatic lower limbs (all phenotypes pooled). Tibial medial rotation angles during loading (3.6 [2.2]° VS 4.7 [2.8]°) and at initial contact (2.2 [2.5]° VS 3.8 [4.0]°) were lower and quadriceps (180.5 [43.5] N.m VS 165.5 [63.3] N.m] and gluteus medius (123.7 [39.9] N.m VS 116.7 [47.7] N.m) strength were higher in the contralateral lower limbs than in the pooled symptomatic limbs. Mean total CoP excursion (318.2 [151.0] VS 243.0 [99.9]) in the EO condition was higher in the contralateral lower limb showing poorer stability than the symptomatic lower limb. Discussion The comparison of kinematic gait parameters associated with the clinical phenotypes showed that only the magnitude of increased knee valgus during the gait loading phase differed between phenotypes. The highest value was for Phenotypes 2 and 4, characterised by clinical static and/or dynamic lower limb alignment alterations, as hypothesised. Also in accordance with our hypothesis, Phenotype 1 was associated with a non-significant loss of knee flexion/extension RoM during stance and Phenotype 3 had no specific kinematic alterations. Three main PFPS phenotypes were determined a priori based on scientific, clinical and biomechanical reasoning. However, in practice a fourth phenotype emerged, highlighting that objective patellar displacement and lower-limb alignment alterations may be combined. The best-known classifications have distinguished several aetiologies, without excluding the fact that they may be combined ( 15 , 19 ). This association is supported by the link between knee valgus and patellar tilt ( 50 ). The magnitude of increase in knee valgus during the gait loading phase differed significantly between groups and was higher for Phenotypes 2 and 4, characterised by clinical knee valgus assessed by the physician and radiological knee valgus assessed using EOS, in accordance with our primary hypothesis. Few studies have reported knee kinematics during gait in people with PFPS. A study comparing 20 participants with PFPS and 20 asymptomatic participants during free speed and fast-speed walking showed greater knee valgus during the free speed at maximum knee extension (which includes the beginning of the loading phase) in the PFPS group ( 30 ). A second study found increased knee valgus at the beginning of the gait cycle in 30 participants with PFPS ( 51 ). Most studies of gait parameters in people with PFPS reported kinetic factors and measured knee abduction or adduction moments (17,27). One study using force platforms reported increased knee abduction moments at initial contact during gait in 14 participants with PFPS compared to 131 asymptomatic participants ( 52 ). A study assessing knee kinematics using the KneeKG® in 90 asymptomatic participants reported no increase in knee valgus during the loading phase ( 51 ). The participants showed a slight varus (1–4°) during the loading phase that returned to 0° during the rest of the stance phase ( 51 ). In addition to dynamic knee valgus, Phenotype 2 had the highest knee flexion RoM values during stance, the longest VMO activation delay, the highest mean velocity and the longest total CoP excursion in the EC condition. These results may indicate altered knee stability in the frontal and sagittal planes and altered postural stability, which may indicate a lack of neuromuscular control in people with PFPS. However, a loss of proprioceptive ability seems unlikely, as shown by the Y test results and the literature ( 53 ). The static knee valgus measured using EOS differed across the phenotypes. It was larger for Phenotype 4, characterised by patellar displacement and altered lower-limb alignment. Static knee valgus angle was higher in Phenotypes 2 and 4 than in the contralateral limbs. Several studies assessed the association between static knee valgus and patello-femoral joint stress ( 30 , 54 ); however, the association between static knee valgus and PFPS has been poorly investigated ( 55 ). A systematic review of 47 studies exploring factors associated with PFPS ( 55 ) found only one study that assessed the relationship between static lower limb malalignment and PFPS. The study found no association between static knee valgus and PFPS in 61 infantry soldiers ( 38 ). Those results suggest that knee valgus may be a marker of specific PFPS phenotypes. Participants with Phenotype 1 had decreased knee flexion/extension RoM during stance in accordance with our main hypothesis. Knee flexion angle at initial contact was lower than for the other phenotypes and the contralateral lower limbs. This is consistent with suggestions that reducing RoM during the early stance phase of gait is a strategy to reduce patellofemoral joint pain ( 28 ). We did not find any specific kinematic alterations in Phenotype 3, in accordance with our main hypothesis. The mean Q-angle measured on EOS was within normal physiological ranges for all phenotypes and smaller than those reported in previous studies ( 7 , 38 , 56 ). These results are consistent with a systematic review of prospective studies that included 243 individuals with PFPS and found no evidence that a larger Q-angle was a risk factor for PFPS ( 55 ). Quadriceps strength was reduced in all phenotypes. A study showed that the endurance Q/H ratio was lower in participants with PFPS than in asymptomatic, nonathletic individuals ( 57 ). Decreased quadriceps strength and/or endurance have been strongly associated with PFPS ( 7 , 55 , 58 ). In the absence of knee kinematic alterations, knee muscle insufficiency may the main explanatory factor for PFPS in Phenotype 3. Surprisingly, stability was poorer on the contralateral limb than on the symptomatic limb in the EO condition. This difference may reflect specific training of the symptomatic limb during rehabilitation sessions; 20/45 participants were undergoing physiotherapy at the time of the study. The participants in the present study were reasonably comparable to those in similar studies. Although they were older than those in most biomechanical studies of PFPS (1,27), the mean age is consistent with a large epidemiological study that showed that PFPS prevalence peaks at several time points between the ages of 30 and 60 years ( 59 ). The moderate pain intensity ( 60 ), the mean level of subjective knee symptoms ( 61 – 63 ) and health-related quality of life ( 64 ) were similar to previous reports. However, symptom duration was longer ( 65 ), which may be related to the mean older age ( 66 ). The large proportion of participants with Phenotype 2 (altered static and/or dynamic lower limb alignment) supports the association between lower limb alignment and PFPS reported in several studies ( 14 , 19 , 67 ). Excessive foot pronation has been associated with tibial medial rotation ( 68 ) tibial abduction and hip adduction ( 69 ), which have been associated with hip muscle weakness ( 70 , 71 ). However, we found no clear difference in hip abduction strength, tibial medial rotation or foot pronation between the phenotypes or between the pooled symptomatic lower limbs and the contralateral lower limbs. A systematic review of 7 studies and 135 variables found no risk factors for PFPS other than lower knee extension strength ( 58 ). The high proportion of participants with Phenotype 2 may also reflect the heterogeneous lower limb alignment in the general population ( 72 ). A cohort study comparing 446 symptomatic and asymptomatic adolescents found various lower limb morphologies in both groups and reported no relationship between knee symptoms and lower limb alignment ( 73 ). The small proportion of participants with Phenotype 1, characterised by objective patellar displacement, seems surprising given this is a patello-femoral pathology. However, this finding is consistent with a cross-sectional study that found that none of the 127 participants with PFPS met the criteria for patellar hypermobility based on 1 SD from published norms ( 18 , 74 ). The low proportion of participants with Phenotype 1 reflects the low prevalence of patellar instability ( 75 ). The proportion of patellar displacement may be underestimated because of the difficulty in detecting and measuring patellar displacement using the most common tests ( 18 , 76 ). The patellar glide test has moderate reliability (Kappa = 0.59) ( 77 ), the J-sign has moderate to good reliability (Kappa 0.53 to 0.72) ( 78 , 79 ), and the lateral patellar apprehension test has no to fair intra- and inter-rater reliability (-0.01 ≤ Kappa ≤ 0.32)( 80 ). In summary, this study suggested that static and dynamic knee valgus is strongly associated with PFPS. The results suggest that 2 main phenotypes can be differentiated in people with PFPS: a type with static and/or dynamic knee valgus, suggesting poor motor control, and a type with no specific kinematic alterations, suggesting knee muscle insufficiency in relation to high knee joint stress. Strengths and limitations The results indicate that kinematic knee parameters during gait can be used to differentiate PFPS phenotypes. The detailed analysis of biomechanical and neuromuscular factors deepens the understanding of PFPS. This study has several limitations. The sample size calculation was based on 3 pre-specified groups; however, the statistical analysis was conducted on 4 groups, which may have reduced the study power but which may reflect clinical reality. The primary outcome is in 3D; we cannot be sure that the 3 rotations are independent, and if the p value requires correction. The participants were unequally distributed among the clinical subgroups, with Phenotype 2 including 25/45 participants and Phenotype 1 including only 4/45 participants. An unexpected number of participants had bilateral symptoms, challenging the clinical examinations and diagnosis that rely on inter-limb comparisons, as well as the comparison between the symptomatic and contralateral lower limbs. Our results reported small quantitative values and differences between phenotypes, which raises the question of their clinical relevance. The KneeKG® does not provide a direct measurement of patellar kinematics. Conclusion Increased knee valgus during the gait loading phase and static knee valgus angle differed significantly between 4 clinical PFPS phenotypes and was increased in the phenotype with altered lower limb alignment detected by clinical assessment. The results of the current study support the association between knee valgus and specific PFPS phenotypes. They also highlight the low prevalence of objective patellar displacement in adults with PFPS and the combination of patellar displacement and knee valgus in a small proportion of participants. The results also confirm the contribution of decreased quadriceps strength and endurance to PFPS. Based on this study, 2 main PFPS phenotypes may be differentiated: a type with static and/or dynamic knee valgus suggesting poor motor control, and a type with no specific kinematic alterations suggesting knee muscle insufficiency. This simple classification may help clinicians to provide the most appropriate rehabilitation treatments. Curve analysis derived from the assessment of 3D knee kinematics during gait could be a promising tool to deepen the phenotyping of PFPS participants. Future studies should assess the effectiveness on pain and function of a rehabilitation program that takes into account kinematic gait alterations in people with PFPS. Abbreviations ADL Activities of daily living AKPS Anterior knee pain scale CoP Centre of pressure EC Eyes closed EO Eyes open FT Femoro-tibial NRS Numeric rating scale PFPS Patellofemoral pain syndrome PMR Physical medicine and rehabilitation Q/H Quadriceps/Hamstrings RoM Range of motion SF-12 Short Form Survey SPM Statistical parametric mapping VL Vastus lateralis VMO Vastus medialis obliquus Declarations Ethics statement The study was approved by the Comité de Protection des Personnes CPP EST-3 (n°21-12-03). Informed consent was obtained from all participants, including consent for the publication of identifying images. Consent for publication Informed consent for publication of his/her clinical images was obtained from the patient. The identifiable individual in the photo is the principal investigator. Availability of data and materials Data are owned by the promotor Assistance-Publique Hôpitaux de Paris (AP-HP). Data cannot be shared publicly because of AP-HP sharing data policy. Data are available from the AP-HP Institutional Data Access (contact via Unité de Recherche Clinique (URC) Necker-Cochin, Marie Benhammani-Godard, [email protected] , for researchers who meet the criteria for access to confidential data. Conflicts of interest All authors declare they have no conflicts of interest. Funding This study received financial support from Assistance Publique - Hopitaux de Paris (MSERI 204, hôpitaux AP-HP. Centre, Université Paris Cité, 2020). The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Contributorship statement Conceptualisation. AR, MMLC, CN, MC, CD, FR Funding acquisition. MC, AR Methodology. AR, MMLC, NH, CN Data acquisition: MC, MMLC, CD, JM, JZ, FL Analysis. MC, AR, NH, MMLC Supervision. AR, NH, MMLC, GD Writing – Original Draft. 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A systematic review. J Orthop. août 2023;42:54‑62. DOI: 10.1016/j.jor.2023.07.005. Additional Declarations The authors declare no competing interests. Supplementary Files Additionalfile1STROBEChecklist.docx Additional files Additional file 1 File name: Additional file 1 - STROBE-Checklist File format: (.docx) File description of data : The STROBE checklist is a tool designed to improve the quality of reporting in cohort, case-control and cross-sectional studies. Additionalfile2TIDieRChecklist.docx Additional file 2 File name: Additional file 2 - TIDieR-Checklist File format: (.docx) File description of data : The Template for Intervention Description and Replication (TIDieR) is a checklist developed to help to improve completeness in the reporting of interventions in research studies. Additionalfile3SupplementaryTable.docx Additional file 3 File name: Additional file 3 – Supplementary Table File format: (.docx) File description of data : Between-group comparison of clinical variables Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6906409","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":473113519,"identity":"c94ba17b-072f-41f2-bd61-f6f2c084b61e","order_by":0,"name":"Marvin Coleman","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYLCCBBDBDmbaMDBIAKkKorQwg5lpEC1niLIKouUwYS267WefSTzcwSDPz8x8dMPPHeflzaV7DzAc3INbi9mZdDOJxDMMhjOb2dJu9p65bbhzzrkEhgPP8Gg5kMZskNjGkGBwmMfsBm/bbcYNN3IMmD8cwKPl/DOYFv5vN/+2nbMHaWE4gE/LjTTGB1Bb2G7zth1IJELLM5AWCZBfzG7LtiUn75yRl3AAr5bzaQwHf7bZyPOzNz+7+bbNzna7RO7BB/i0QIEEgmnAwMNAWAMKAGkZBaNgFIyCUYAMAE+uV2tcJ5fmAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-8717-0640","institution":"AP-HP, Centre-Université Paris Cité, Service de Rééducation et de Réadaptation de l’Appareil Locomoteur et des Pathologies du Rachis, Hôpital Cochin, France","correspondingAuthor":true,"prefix":"","firstName":"Marvin","middleName":"","lastName":"Coleman","suffix":""},{"id":473113520,"identity":"64ba3891-bbc6-4936-af59-cfc047565937","order_by":1,"name":"Marie-Martine Lefèvre-Colau","email":"","orcid":"","institution":"Université Paris Cité, Faculté de Santé, UFR de Médecine, France","correspondingAuthor":false,"prefix":"","firstName":"Marie-Martine","middleName":"","lastName":"Lefèvre-Colau","suffix":""},{"id":473113521,"identity":"5949ce68-2ce3-4d20-ac10-55c537426786","order_by":2,"name":"Christelle Nguyen","email":"","orcid":"","institution":"Université Paris Cité, Faculté de Santé, UFR de Médecine, France","correspondingAuthor":false,"prefix":"","firstName":"Christelle","middleName":"","lastName":"Nguyen","suffix":""},{"id":473113522,"identity":"c84ace4d-b9be-418b-ad47-aec5edd52e7b","order_by":3,"name":"Camille Daste","email":"","orcid":"","institution":"AP-HP, Centre-Université Paris Cité, Service de Rééducation et de Réadaptation de l’Appareil Locomoteur et des Pathologies du Rachis, Hôpital Cochin, France","correspondingAuthor":false,"prefix":"","firstName":"Camille","middleName":"","lastName":"Daste","suffix":""},{"id":473113523,"identity":"0e6bcb27-7755-4d73-96d8-5e5a499b60f5","order_by":4,"name":"François Rannou","email":"","orcid":"","institution":"Université Paris Cité, Faculté de Santé, UFR de Médecine, France","correspondingAuthor":false,"prefix":"","firstName":"François","middleName":"","lastName":"Rannou","suffix":""},{"id":473113524,"identity":"353ba176-5f38-4e94-a797-4a52802498e8","order_by":5,"name":"Julie Molina","email":"","orcid":"","institution":"AP-HP. 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STROBE-Checklist\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFile format: (.docx)\u003c/p\u003e\n\u003cp\u003eFile description of data : The STROBE checklist is a tool designed to improve the quality of reporting in cohort, case-control and cross-sectional studies.\u003c/p\u003e","description":"","filename":"Additionalfile1STROBEChecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-6906409/v1/08f4fea9ba6669925778967f.docx"},{"id":85081260,"identity":"a3b9fbe8-9318-47d5-aeeb-2a5ef5bc82c3","added_by":"auto","created_at":"2025-06-20 17:50:28","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":32453,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFile name:\u003cstrong\u003e Additional file 2 - TIDieR-Checklist\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFile format: (.docx)\u003c/p\u003e\n\u003cp\u003eFile description of data : The Template for Intervention Description and Replication (TIDieR) is a checklist developed to help to improve completeness in the reporting of interventions in research studies.\u003c/p\u003e","description":"","filename":"Additionalfile2TIDieRChecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-6906409/v1/6133f9be1857a2b3fbfe3b76.docx"},{"id":85081264,"identity":"1d922a19-7c57-4ee5-9cd7-1ddd075c772e","added_by":"auto","created_at":"2025-06-20 17:50:28","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":38730,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFile name:\u003cstrong\u003e Additional file 3 – Supplementary Table\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFile format: (.docx)\u003c/p\u003e\n\u003cp\u003eFile description of data : Between-group comparison of clinical variables\u003c/p\u003e","description":"","filename":"Additionalfile3SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-6906409/v1/3108595fae25d03d242c2d0e.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAssociation between 3D knee kinematics and clinical phenotypes in people with Patellofemoral Pain Syndrome: a prospective comparative study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003ePatellofemoral Pain Syndrome (PFPS) is a common condition in the general population, with an annual prevalence of 22.7% (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This syndrome represents 17% of general practitioner consultations for knee injuries (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). PFPS is particularly common in young, physically active women (\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Rehabilitation is the first-line treatment for PFPS (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) but more than 50% of individuals with PFPS develop chronic pain, and two-thirds still have symptoms 1 year after diagnosis (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA common definition of PFPS is anterior knee pain located around or behind the patella and aggravated by activities that load or compress the patellofemoral joint (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, this definition is unspecific (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). PFPS is diagnosed by exclusion, using both clinical and imaging findings. There is a consensus to exclude femoro-tibial (FT) osteoarthritis and peri-articular pathologies from the diagnosis of PFPS (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe pathophysiology of PFPS is considered to be multifactorial, including biomechanical factors (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). It is associated with both static and dynamic deficiencies of the hip, knee, and foot (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The interactions between clinical symptoms, kinematics and neuromuscular deficiencies are poorly understood (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNumerous classifications based on presumed contributing factors have been proposed. A multicentre observational study including 127 participants proposed a 3-group classification (weak and tighter, strong, weak and pronated) based on lower limb length and strength, patellar mobility and foot posture (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The European Rehabilitation Panel determined 2 main categories: malalignment and muscular dysfunction, which were further subdivided into 5 etiological factors: malalignment of the entire lower limb, malalignment of the patellofemoral joint, loss of strength and flexibility, and neuromuscular changes (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Another widely used classification from the American practice guidelines additionally includes overuse for people without lower limb malalignment or neuromuscular dysfunction (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). This classification describes 4 subcategories based on the predominant factors: muscle performance, movement coordination, mobility and overuse (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). These classifications are quite complex and involve many time consuming assessments, some of which require the use of specific measuring devices. Therefore, they cannot be performed during routine medical consultations.\u003c/p\u003e \u003cp\u003eWe used a pragmatic clinical classification based on biomechanical factors because we wanted to determine whether lower limb postural or movement alterations resulted in specific knee kinematic patterns. The clinical classification was divided into 3 main phenotypes. Phenotype 1: PFPS with objective displacement of the patella, Phenotype 2: PFPS with altered static and/or dynamic lower limb alignment, Phenotype 3: PFPS without altered alignment or objective displacement of the patella.\u003c/p\u003e \u003cp\u003eClinical tests cannot accurately assess knee 3D kinematics (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Optoelectronic techniques are the gold standard method for kinematic assessment (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The KneeKG\u0026reg; (EMOVI) is a non-invasive optoelectronic device that assesses 3D knee kinematics in real-time during gait. Several studies have demonstrated the validity and reproducibility of this system (\u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough PFPS symptoms are usually not aggravated by walking, walking is the most common human physical activity and is a good model for assessing dynamic repeated 3D knee rotations involving both single and double limb loading (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Altered kinematic and kinetic gait patterns have been found in people with PFPS (27,28). Two main kinematic alterations have been found: decreased peak knee flexion during stance phase (specifically at heel contact) and decreased femoral medial rotation range of motion (RoM) (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Increased knee abduction (valgus) during gait has been described in a subgroup of PFPS participants with higher pain levels (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). However, several studies found that knee abduction angle did not differ between people with PFPS and asymptomatic individuals during gait (27,29). Consensus regarding kinematic alterations during gait is thus lacking.\u003c/p\u003e \u003cp\u003eThe primary aim of this study was to describe and compare the kinematic alterations during gait (increased or decreased FT 3D rotation angles during stance) between the 3 main clinical phenotypes. The secondary aims were to describe and compare postural, neuromuscular and proprioceptive alterations between the 3 main clinical phenotypes.\u003c/p\u003e \u003cp\u003eOur primary hypothesis was that each of the 3 PFPS phenotypes would show specific kinematic alterations. We expected that Phenotype 1 would be associated with decreased knee flexion/extension RoM during stance and that Phenotype 2 would be associated with increased knee valgus during stance and /or increased tibial medial rotation (especially during loading). We did not expect to find any specific kinematic alterations in Phenotype 3.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy design\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eWe conducted a single-centre comparative, non-randomised interventional study (ClinicalTrials.gov Identifier: NCT05441332). We reported our study in accordance with the Strengthening the reporting of observational studies in Epidemiology (\u003cstrong\u003eAdditional file 1\u003c/strong\u003e)\u0026nbsp;(31)\u0026nbsp;and Template for Intervention Description and Replication (\u003cstrong\u003eAdditional file 2\u003c/strong\u003e) checklists\u0026nbsp;(32), given the observational nature of our data analysis.\u003c/p\u003e\n\u003cp\u003eChanges were made to the study protocol after the trial commencement to facilitate participant inclusion. The assessment could take place over 2 separate days, and the inclusion period was extended by 18 months. We did not change any outcomes after the trial had begun.\u003c/p\u003e\n\u003ch2\u003eSetting and participants\u003c/h2\u003e\n\u003cp\u003eThe study was conducted in the physical medicine and rehabilitation (PMR) and the imaging department of Cochin Hospital, Paris, France. Participants were screened for eligibility during consultations at the orthopaedic, rheumatology, and 2 PMR (tertiary care) departments of Cochin Hospital, Paris, France and Corentin-Celton hospital, Issy-les-Moulineaux, France, general practice clinics and out-patient physiotherapy clinics. Information about the study was communicated by posters and flyers specifying the study objective, inclusion and non-inclusion criteria, and the assessment procedure. The baseline face-to-face visit was conducted by the principal investigator (MC), a physiotherapist (MSc) with 7 years of experience in PFPS rehabilitation and 5 years of research experience. During the year before the study commenced, the principal investigator performed the clinical and biomechanical examinations on 28 knees in asymptomatic individuals and 13 in individuals with various knee pathologies including PFPS. During that time, the KneeKG® 3D kinematic measurements made by MC were checked and validated by engineers from EMOVI.\u003c/p\u003e\n\u003ch2\u003eInclusion and exclusion criteria\u003c/h2\u003e\n\u003cp\u003eThe main inclusion criteria were: 1) age 18 to 70 years, and 2) diagnosis of PFPS based on symptom duration \u0026gt;1 month and pain rated ≥4/10 on the Numeric Rating Scale (NRS) during at least one of the following activities: stair climbing and/or descending, squatting, jumping, jogging, prolonged sitting and/or crouching.\u003c/p\u003e\n\u003cp\u003eThe main exclusion criteria were 1) a history or presence of neurological disorders affecting the lower limbs, 2) signs of FT osteoarthritis on x-ray, 3) a history of surgery or trauma to the lower limbs \u0026lt;1 year previously, and 4) intra-articular knee injection in the past 2 months.\u003c/p\u003e\n\u003ch2\u003eExperimental Protocol\u0026nbsp;\u003c/h2\u003e\n\u003ch3\u003eDevelopment of the clinical classification\u003c/h3\u003e\n\u003cp\u003eThe pragmatic classification was derived from the scientific literature\u0026nbsp;(15,19)\u0026nbsp;and clinical practice and based on the detection of biomechanical alterations in patellar displacement and lower-limb alignment by a clinician during a consultation. \u0026nbsp;A committee of 3 Physical and Rehabilitation Medicine (PRM) physicians (MMLC, CN, CD) and 2 physiotherapists (AR, MC), all experts in the diagnosis and treatment of musculoskeletal pathologies, defined the clinical classification and selected the tests routinely used in clinical practice.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThree main clinical phenotypes were defined:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePhenotype 1: PFPS with objective displacement of the patella. This phenotype was identified on the following yes/no clinical signs: positive apprehension test, lateral displacement of the patella of \u0026gt;25% of its width, and positive J-sign.\u003c/p\u003e\n\u003cp\u003ePhenotype 2: PFPS with static and/or dynamic lower limb alignment deficiencies. This phenotype was identified on the following yes/no clinical signs: static knee valgus and dynamic (increased) knee valgus during single-leg squat, recurvatum of the knee, Q-angle \u0026gt;15°, lower limb length discrepancy, and Navicular Drop test \u0026gt;1.1 cm.\u003c/p\u003e\n\u003cp\u003ePhenotype 3: PFPS without alignment deficiency or objective displacement of the patella. This phenotype was identified by a lack of detectable biomechanical alterations on clinical inspection.\u003c/p\u003e\n\u003ch3\u003eAssessments\u003c/h3\u003e\n\u003cp\u003eInclusion and assessments took place on the same day. The assessments could span over 2 different days according to participant preference and availability.\u003c/p\u003e\n\u003cp\u003eAfter the physician (MMLC or CD) included and classified the participant’s phenotype using the approach described above, the principal investigator (MC) performed the data collection and assessments, beginning with the collection of demographic and clinical characteristics. The principal investigator (MC) and the participants were blinded to the phenotype classification that was performed by the physician (MMLC or CD). The data analysts (HA and CO) were blinded.\u003c/p\u003e\n\u003cp\u003eAll assessments were performed bilaterally on the asymptomatic or less symptomatic limb first. Only the symptomatic or most symptomatic limb was classified. The assessment order alternated physically demanding tests with more passive tests to avoid participant fatigue and according to the EOS imaging slot.\u0026nbsp;\u003c/p\u003e\n\u003ch4\u003eKinematic assessment\u003c/h4\u003e\n\u003cp\u003eThe kinematic variables were measured using the KneeKG® optoelectronic device (Knee3DTM Software, EMOVI). This device includes a 3D infrared camera (Polaris Spectra, Northern Digital) and 3 tripod reflectors positioned on the arches above the femoral condyles and medial side of the tibia and on a belt facing the sacrum (Figure 1a). Data acquisition was performed on a treadmill. Participants walked on the treadmill for 5 to 10 minutes prior to recording to get used to the speed and the equipment and ensure that the sensors were well-attached and could always be detected by the camera. After a calibration procedure (Figure 1b), data were acquired at 60 Hz for 1 minute at the participant’s chosen (comfortable and usual) gait speed. The KneeKG® provides common knee gait parameters in the format of 3D kinematic curves (33). The mean accuracy is 0.4° for knee varus/valgus and 2.3° for axial rotations (25). Anonymised 3D knee kinematic data were checked by the engineers from EMOVI, who sought atypical data from incorrect estimation of the gait cycle initiation (34). This review identified 3 problematic analyses, which were then corrected.\u003c/p\u003e\n\u003ch4\u003ePostural, neuromuscular and proprioceptive assessment\u003c/h4\u003e\n\u003cp\u003eThe clinical assessment included standard muscle length and strength tests routinely used to assess PFPS\u0026nbsp;(15): hip, knee and ankle passive maximal RoM and hamstring and calf muscle tightness (in degrees) using a goniometer, and quadriceps tightness (in cm) using a measuring tape\u0026nbsp;(35). The Ober’s test was used to evaluate iliotibial band tightness\u0026nbsp;(36). Patellar mobility was assessed using the lateral apprehension test, the glide test, the lateral tilt test and the J sign\u0026nbsp;(15,36–38).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEOS imaging was performed on the same day (or the second day) in the radiology unit by a senior radiographer (JM) under the supervision of a senior radiologist, who were both blinded to the phenotype classification. The inter-observer reliability of lower extremity measurements using 2D EOS is excellent\u0026nbsp;(39). FT alignment and the Q-angle (angle between the quadriceps muscle and the patella tendon representing the line of pull of the quadriceps relative to the patella) were measured using EOS lower limb imaging\u0026nbsp;(40).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe used the foot posture index and the Navicular Drop test (cm) to quantify foot pronation\u0026nbsp;(15,41). The knee function assessment was performed using functional tests, EMG and isokinetic dynamometry. The Y balance test (Y test) was used to measure single limb dynamic balance expressed by the average distance reached in the 3 directions divided by the participant’s leg length, as a %\u0026nbsp;(42), the forward step-down test to assess pain during functional movement\u0026nbsp;(43), and the lateral step-down test\u0026nbsp;(36)\u0026nbsp;to evaluate movement quality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe activation times of the vastus medialis obliquus (VMO) and vastus lateralis (VL) were assessed using surface EMG (EMG Zerowire, Aurion). Hip and knee muscle strength and endurance were assessed using an isokinetic dynamometer (Humac NORM, CSMi, Stoughton, MA, Software HUMAC 2009, v.9.7.1). The isokinetic test was perfomed last as it required maximal effort and causes fatigue. All assessments are detailed in the study protocol\u0026nbsp;(35).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSingle-leg postural stability was assessed on both lower extremities successively using a posturography platform (Posture Win Sabots, Technoconcept), the less symptomatic lower limb was assessed first.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eOutcomes\u0026nbsp;\u003c/h2\u003e\n\u003ch3\u003ePrimary outcome\u003c/h3\u003e\n\u003cp\u003eThe primary outcome included the following 3D knee rotations assessed (in degrees) by the KneeKG®:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eMean increase in knee valgus (valgus thrust defined by a sudden lateral shift of the knee) during the loading phase of the gait, (0-20% of the gait cycle). It was measured as the difference between the peak valgus point and the valgus point at initial contact,\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eKnee flexion/extension RoM during stance (20% to 54% of the gait cycle),\u003c/li\u003e\n \u003cli\u003eTibial medial rotation RoM during loading.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003eSecondary outcomes\u003c/h3\u003e\n\u003cp\u003e\u003cu\u003e3D knee rotations:\u003c/u\u003e mean varus/valgus at initial contact and during stance, tibial lateral rotation RoM at initial contact and total tibial rotation RoM during the entire gait cycle, flexion/extension at initial contact, flexion/extension RoM during the entire gait cycle.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eKnee posture\u0026nbsp;\u003c/u\u003e(FT alignment): knee valgus and Q-angle (angle formed between the quadriceps muscle and the patella tendon) measured using EOS imaging.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFoot posture:\u003c/u\u003e The Foot Posture Index (FPI; -12; +12: -12: high supination, +12: high pronation, -2 ≤ normal scores ≤ 9)(44)\u0026nbsp;and the Navicular Drop test, which measures the change in arch height from the sitting to the standing position (mm), a value \u0026gt;1.1 cm indicates excessive foot pronation\u0026nbsp;(45).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eKnee function\u003c/u\u003e: the Y test (range 0-100+: 0: minimal dynamic balance, 100+: excellent dynamic balance): a mean composite score of 95.5% of leg length has been found in healthy recreational adult athletes\u0026nbsp;(46), the forward step-down test (assessing pain during movement: yes/no question) and the lateral step-down test (assessing quality of movement: range 0-6 points, 0 and 1: good quality movement, 2 and 3: average quality movement, and 4 to 6: poor quality movement)\u0026nbsp;(47).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eNeuromuscular activity\u003c/u\u003e: VMO activation delay (VL activation time minus VMO activation time, in ms) during the stand-up test. In asymptomatic individuals,\u0026nbsp;the mean VMO activation delay during active knee extension\u0026nbsp;is less than 4 milliseconds\u0026nbsp;(48). Isokinetic strength (peak quadriceps and hamstrings torque and quadriceps/hamstrings ratio at 60°.s\u003csup\u003e-1\u003c/sup\u003e) and knee muscle endurance (quadriceps and hamstrings total work and quadriceps/hamstrings total work ratio at 180°.s\u003csup\u003e-1\u003c/sup\u003e) (N.m), hip abductor: gluteus medius isometric strength (N.m) and gluteus medius time to peak torque (s).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eSingle-leg postural stability:\u003c/u\u003e total excursion (mm) and mean velocity (mm.s\u003csup\u003e-1\u003c/sup\u003e) of the centre of pressure (CoP) during posturography, eyes open (EO) and eyes closed (EC) for each lower limb.\u003c/p\u003e\n\u003cp\u003eOther variables were collected for descriptive purposes: mean knee pain intensity and pain intensity during activities of daily living (ADL) the week before the test (NRS, range 0-100; 0: \u0026nbsp;no pain; 100: worst pain imaginable); subjective symptoms and activity limitation using the Anterior Knee Pain Scale (AKPS) (range 0-100; 0: maximal symptoms, 100: no symptoms), quality of life using the 12-Item Short Form Survey (SF-12) (physical component summary score 9.95, minimum quality of life 70.02, maximum quality of life and mental component summary score 5.89, minimum quality of life 71.97, maximum quality of life), tightness of the main hip, knee and ankle muscles: hamstring and calf muscle tightness using joint angles (in degrees) and quadriceps using the heel-to-buttock distance (in cm).\u003c/p\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003ch3\u003eSample size calculation\u003c/h3\u003e\n\u003cp\u003eWe did not find other studies comparing FT biomechanical alterations between people with different PFPS phenotypes. Based on recent studies comparing 3D FT kinematics between asymptomatic and OA knees with the KneeKG® device\u0026nbsp;(49)\u0026nbsp;and a literature review on biomechanical FT parameters during gait in participants with PFPS\u0026nbsp;(17), we estimated that a sample size of 15 participants per group (45 participants in total) was appropriate to detect a difference in knee 3D kinematics between the 3 PFPS phenotypes.\u003c/p\u003e\n\u003ch3\u003eStatistical analysis\u003c/h3\u003e\n\u003cp\u003eStatistical analyses were performed using Systat 13 for Windows (Systat Software, Inc., Point Richmond, CA). Continuous data were expressed as means (SD) and standard deviations (SD) or 95% confidence intervals (CI) and medians (Q1, Q3) Categorical data were expressed as absolute and relative frequencies (n/N [%]). The normality of the data distribution was assessed using the Kolmogorov Smirnov test with Lilliefors correction. The kinematic variables used for the primary outcome and most other kinematic variables did not follow a normal distribution for any phenotype. Participants with the clinical characteristics of both phenotypes 1 and 2 were classed as Phenotype 4. Most clinical variables were not normally distributed. For clarity and to compare the current results with the literature, we chose to present both mean (SD) and median (Q1-Q3) values.\u003c/p\u003e\n\u003cp\u003eA sensitivity analysis was performed by including the kinematic values of Phenotype 4 in both Phenotype 1 (Phenotype 1’) and 2 (Phenotype 2’).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJoint angle time series were compared using Statistical Parametric Mapping (SPM). The SPM was computed using the SPM1D Python package (version 3.9.7) with permutation analysis (500 permutations). The Krsukall-Wallis test (with Dwass-Steel test for post-hoc analyses) was used to compare clinical and kinematic parameters between groups. All tests were two-tailed, with a p-value \u0026lt;0.05 considered significant.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eDemographic and clinical characteristics\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eWe included 45 participants between December 2022 and February 2024: 29 (64%) females, mean (SD) age 36.3 (13.7) years, BMI 22.9 (3.8) kg.m\u003csup\u003e-2\u0026nbsp;\u003c/sup\u003eand symptom duration 8.1 (9.6) years. Twenty-three participants/45 had unilateral symptoms. Four participants (9%) were classed as Phenotype 1, 25 (56%) as Phenotype 2, 10 (22%) as Phenotype 3, and 6 (13%) had both the clinical characteristics of phenotypes 1 and 2 and were classed as Phenotype 4 (Table 1, and\u0026nbsp;Figure 2). The assessment lasted 3 to 5 hours, depending on the participant.\u003c/p\u003e\n\u003cp\u003eThe mean participant age was lower for Phenotype 1 (25.0 [5.5] years) than for the other phenotypes (Table 1). The mean NRS scores (37.5 [17.1]/100 for pain and 52.5 [34.0]/100 for pain during ADL) were higher in Phenotype 1 than in the other Phenotypes. The AKPS scores ranged from 60.8 (18.5)/100 for Phenotype 4 to 71.3 (16.5)/100 for Phenotype 3. Phenotype 3 had the highest SF-12 physical score: 44.5 (11.1), and Phenotype 2 had the lowest: 40.9 (10.4). All Phenotypes had knee hyperextension (goniometry), ranging from 3.0 (3.4)\u0026deg; for Phenotype 3 to 5.7 (4.5)\u0026deg; for Phenotype 4. The shortest heel-to-buttock distance was 1.4 (2.1) cm (Phenotype 3), and the longest was 6.0 (7.7) cm (Phenotype 1) (Table 1). Demographic and general clinical characteristics did not differ between the Phenotypes (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e. Demographic and clinical characteristics of participants with PFPS\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"662\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll groups (N=45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenotype 1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=4)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenotype 2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=25)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenotype 3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=10)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenotype 4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eFemale n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e29 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e15 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e6 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5 (83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eAge (years), mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e36.3 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e25.0 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e38.7 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e36.5 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e33.5 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eBMI (kg.m\u003csup\u003e-2\u003c/sup\u003e), mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e22.9 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e21.7 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e22.9 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e22.7 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e24.4 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral clinical characteristics, mean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eKnee Pain (NS, 0-100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e28.9 (19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e37.5 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e30.4 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e20 (22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e31.7 (24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eKnee pain during ADL (NS, 0-100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e38.4 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e52.5 (34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e40.0 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e32.0 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e33.3 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eAKPS (0-100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e68.1 (14.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e65.8 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e68.9 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e71.3 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e60.8 (18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eSF-12\u0026nbsp;Physical Score (9.95-70.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e42.3 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e43.7 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e40.9 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e44.5 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e44.1 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eSF-12 Mental Score (5.89-71.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e43.3 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e45.3 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e43.8 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e41.7 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e42.9 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eSymptoms duration, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e8.1 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4.6 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5.8 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e10.3 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e16.4 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent treatments (n)\u003c/strong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003ePhysical therapy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eSelf exercices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eInsoles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eNonstero\u0026iuml;dal anti-inflammatory drugs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eAnalgesics Grade I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eAnalgesics Grade II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKnee and ankle mobility\u0026nbsp;\u003c/strong\u003e(Maximal RoM, in degrees)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eKnee Flexion\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e143.8 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e141.5 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e144.7 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e143.7 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e137.5 (18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eKnee Extension\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.1 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4.5 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3.7 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3.0 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5.7 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eGlobal knee axial rotation\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e44.7 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e45.0 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e44.0 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e42.1 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e45.0 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eAnkle dorsal flexion\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e35.3 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e38.5 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e33.4 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e34.3 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e36.3 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMuscle length\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eHamstrings, popliteal angle (\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e160.9 (18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e162.5 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e160.0 (18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e159.0 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e168.0 (14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.83\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eRectus femoris, heel-to-buttock distance (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.0 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e6.0 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.9 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.4 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e6.3 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eTriceps, ankle dorsal flexion (knee extended) (\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e33.6 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e33.0 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e33.0 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e30.5 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e35.0 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.35\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 662px;\"\u003e\n \u003cp\u003eBMI: body mass index; AKPS: Anterior Knee Pain Scale; SF-12: Medical Outcome Study Short Form 12; \u0026nbsp;\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eThe total number of current treatments exceeds the number of participants because one participant could have more than one treatment for PFPS; \u003csup\u003e2\u003c/sup\u003ePositive values mean hyperextension; RoM: range of motion; \u003csup\u003e3\u003c/sup\u003eGlobal knee axial rotation includes knee medial and lateral RoM. P value is for group (1,2,3,4) comparison (Kruskall-Wallis test)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eKinematic variables during gait\u003c/h2\u003e\n\u003cp\u003eMean (95% CI) increased knee valgus angle was 0.3 (-0.41; 0.96)\u0026deg; for Phenotype 1, 2.1 (1.24; 2.82)\u0026deg; for Phenotype 2, 0.5 (0.04; 1.01)\u0026deg; for Phenotype 3 and 2.1 (-0.06; 5.02)\u0026deg; for Phenotype 4, (p=0.03) (Table 2). The post-hoc analyses revealed significant differences between groups for all comparisons, except between Phenotypes 1 and 4 (p=0.97).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere were no between-group differences for the 2 other primary outcomes: knee flexion/extension RoM during stance and tibial medial rotation RoM during loading (p\u0026gt;0.2) (Table 2). There were no between-group differences for the secondary kinematic outcomes at any point in the gait cycle (Table 2). The sensitivity analysis showed no further differences between Phenotypes 1\u0026rsquo; (1+4), 2\u0026rsquo; (2+4) and 3. The sensitivity analysis showed a between-group difference (1\u0026rsquo;, 2\u0026rsquo; and 3) for increased knee valgus during gait loading (p=0.04); the post-hoc analyses showed significant differences between Phenotypes 1\u0026rsquo; and 2\u0026rsquo;, 2\u0026rsquo; and 3 but no difference between Phenotypes 1\u0026rsquo; and 3 (p=0.78).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e. Between-group comparison of kinematic knee variables during gait\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"765\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKinematic knee variables,\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(in degrees)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptomatic lower limbs\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eall groups pooled\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=42)\u003csup\u003ea,b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenotype 1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=4)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenotype 2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=24)\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenotype 3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=9)\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenotype 4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=5)\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eContralateral lower limbs\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=42)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u003cu\u003eIncreased valgus during loading\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.6 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.3 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.1 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.5 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.1 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.3 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.0 (0.2, 2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.1 (0, 0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.4 (0.6, 3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.2 (0, 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.1 (0.3, 4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.9 (0.4, 1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u003cu\u003eFlexion RoM during stance\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e14.2 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e7.2 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e16.7 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e11.4 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.7 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e14.2 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e11.9 (8.0, 20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e7.5 (3.8, 10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e16.4 (9.3, 23.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e10.4 (6.2, 17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e10.1 (7.8, 19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e14.1 (8.7, 18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u003cu\u003eTibial medial RoM during loading\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.7 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e5.4 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.6 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.3 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.9 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.6 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.3 (2.6, 6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.7 (3.7, 6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.5 (2.6, 6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.7 (2.9, 5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.2 (1.4, 4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.5 (2.0, 4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eVarus/valgus at initial contact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.1 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e-0.7 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.8 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.8 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.9 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2.5 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.1 (-1.1, 3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e-0.4 (-3.9, 2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.3 (0.1, 4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.8 (0.3, 4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.2 (1.1, 4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2.3 (-0.8, 5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eVarus/valgus during stance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.3 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.7 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.8 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.7 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.8 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.8 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.3 (-0.6, 2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.9 (1.9, 3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e1.5 (-0.6, 2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.9 (-0.1, 2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.5 (0.2, 3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.6 (-1.9, 5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eTibial lateral rotation at initial contact\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.8 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.9 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.7 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.6 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e5.1 (5.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2.2 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.6 (1.4, 5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.4 (-0.3, 6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e2.9 (1.5, 3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e5.0 (4.5, 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.3 (1.7, 5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2.2 (0.8, 4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eTibial rotation RoM during the entire gait cycle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e13.4 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.5 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.9 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e13.8 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e14.6 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e14.4 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e13.0 (10.0, 16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.0 (10.0, 14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.5 (10.8, 16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e15.0 (10.0, 16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e13.0 (8.0, 13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e14.0 (10.0, 17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eFlexion/extension at initial contact\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e10.6 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e5.0 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.4 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e9.7 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e8.3 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e9.8 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e8.5 (4.8, 15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e5.7 (2.4, 8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e10.4 (5.5, 19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e8.3 (4.5, 13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e7.9 (6.3, 9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e8.8 (5.0, 14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eFlexion RoM during loading\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e5.0 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e8.8 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.4 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.0 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e6.8 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e5.8 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.5 (1.3, 7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e8.2 (6.8, 10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.3 (1.1, 7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.6 (0.9, 6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e6.7 (6.6, 8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e5.5 (1.1, 9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eFlexion-extension RoM during the entire gait cycle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e60.9 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e61.8 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e62.8 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e56.3 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e63.2 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e62.2 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 155px;\"\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e64.5 (59.8, 68.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e62.0 (60.5, 63.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e65.0 (61.0, 67.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e64.0 (54.0, 65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e67.0 (56.0, 67.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e63.7 (58.5, 66.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSPM analysis showed no significant differences between the kinematic curves in the coronal, sagittal or transverse planes during gait; all \u003cem\u003eF\u003c/em\u003e-values were below the significance threshold (\u003cem\u003eF\u003c/em\u003e=4.45 in the coronal plane, \u003cem\u003eF\u003c/em\u003e=4.97 in the sagittal plane and \u003cem\u003eF\u003c/em\u003e=4.45 in the transversal plane) (Figure 3).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eClinical variables\u003c/h2\u003e\n\u003ch3\u003eKnee posture (FT alignment)\u003c/h3\u003e\n\u003cp\u003eThe static knee valgus angles measured on EOS images were statistically different between phenotypes (p=0.01). Phenotype 4 had the highest knee valgus value: 3.6 (1.95)\u0026deg;, and Phenotype 1 had the lowest: 1.0 (0.82)\u0026deg;. There were no significant differences between phenotypes for other clinical variables (all P\u0026gt;0.07).\u003c/p\u003e\n\u003cp\u003eThe mean Q-angle values ranged 4.7 (2.4)\u0026deg; for Phenotype 3 to 6.3 (2.8)\u0026deg; for Phenotype 4 (\u003cstrong\u003eAdditional file 3 - Supplementary Table\u003c/strong\u003e).\u003c/p\u003e\n\u003ch3\u003eFoot posture\u003c/h3\u003e\n\u003cp\u003eAll participants had normal FPI scores and 38/45 (4/4 in Phenotype 1, 21/25 in Phenotype 2, 9/10 in Phenotype 3, and 4/6 in Phenotype 4) had a pronated foot. All mean Navicular Drop test scores were \u0026lt;1.1 cm. The Navicular Drop test was negative for all participants in Phenotype 1, and positive for 6/25 participants in Phenotype 2, 2/10 in Phenotype 3 and 2/6 in Phenotype 4 (\u003cstrong\u003eAdditional file 3\u003c/strong\u003e).\u003c/p\u003e\n\u003ch3\u003eKnee function\u003c/h3\u003e\n\u003cp\u003eGood quality movement was found in 3/4 (75%) participants in Phenotype 1, 14/25 (56%) in Phenotype 2, 5/9 (56%) in Phenotype 3 and 4/6 (67%) in Phenotype 4. Average quality movement was observed in 1/4 (25%) participants in Phenotype 1, 9/25 (36%) in Phenotype 2, 4/9 (44%) in Phenotype 3, and 2/6 (33%) in Phenotype 4. Poor quality movement was found in 2/25 (8%) participants in Phenotype 2 and none in the other phenotypes (\u003cstrong\u003eAdditional file 3\u003c/strong\u003e).\u003c/p\u003e\n\u003ch3\u003eNeuromuscular activity\u003c/h3\u003e\n\u003cp\u003eThe VMO was activated after the VL in 3/4 phenotypes. The longest VMO activation delay was -23.0 (66.0) ms (Phenotype 4). In Phenotype 1, the VMO was activated 8.2 (36.3) ms before the VL (\u003cstrong\u003eAdditional file 3\u003c/strong\u003e). The isokinetic strength and endurance and isometric values were similar between Phenotypes 1, 2 and 3, and Phenotype 4 had slightly lower values than the other groups. The mean total work Q/H ratios were \u0026ge; 95.3 in all groups (\u003cstrong\u003eAdditional file 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ePostural stability\u003c/u\u003e: Phenotype 2 had the highest total CoP excursion (758.5 [237.3] mm) and mean velocity (111.9 [158.2] mm.s\u003csup\u003e-1\u003c/sup\u003e). Phenotype 1 had the highest total CoP excursion: 264.8 (67.5) mm, and Phenotype 2 had the highest mean velocity: 27.5 (8.2) mm.s\u003csup\u003e-1\u003c/sup\u003e in the EO condition. Phenotype 4 had the lowest mean velocity and total CoP excursion in both the EC and EO conditions (\u003cstrong\u003eAdditional file 3\u003c/strong\u003e).\u003c/p\u003e\n\u003ch3\u003eContralateral lower limb variables\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eMost kinematic and clinical variable values were similar between the contralateral lower limbs and the symptomatic lower limbs (all phenotypes pooled). Tibial medial rotation angles during loading (3.6 [2.2]\u0026deg; VS 4.7 [2.8]\u0026deg;) and at initial contact (2.2 [2.5]\u0026deg; VS 3.8 [4.0]\u0026deg;) were lower and quadriceps (180.5 [43.5] N.m VS 165.5 [63.3] N.m] and gluteus medius (123.7 [39.9] N.m VS 116.7 [47.7] N.m) strength were higher in the contralateral lower limbs than in the pooled symptomatic limbs. Mean total CoP excursion (318.2 [151.0] VS 243.0 [99.9]) in the EO condition was higher in the contralateral lower limb showing poorer stability than the symptomatic lower limb.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe comparison of kinematic gait parameters associated with the clinical phenotypes showed that only the magnitude of increased knee valgus during the gait loading phase differed between phenotypes. The highest value was for Phenotypes 2 and 4, characterised by clinical static and/or dynamic lower limb alignment alterations, as hypothesised. Also in accordance with our hypothesis, Phenotype 1 was associated with a non-significant loss of knee flexion/extension RoM during stance and Phenotype 3 had no specific kinematic alterations.\u003c/p\u003e \u003cp\u003eThree main PFPS phenotypes were determined a priori based on scientific, clinical and biomechanical reasoning. However, in practice a fourth phenotype emerged, highlighting that objective patellar displacement and lower-limb alignment alterations may be combined. The best-known classifications have distinguished several aetiologies, without excluding the fact that they may be combined (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). This association is supported by the link between knee valgus and patellar tilt (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe magnitude of increase in knee valgus during the gait loading phase differed significantly between groups and was higher for Phenotypes 2 and 4, characterised by clinical knee valgus assessed by the physician and radiological knee valgus assessed using EOS, in accordance with our primary hypothesis. Few studies have reported knee kinematics during gait in people with PFPS. A study comparing 20 participants with PFPS and 20 asymptomatic participants during free speed and fast-speed walking showed greater knee valgus during the free speed at maximum knee extension (which includes the beginning of the loading phase) in the PFPS group (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). A second study found increased knee valgus at the beginning of the gait cycle in 30 participants with PFPS (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Most studies of gait parameters in people with PFPS reported kinetic factors and measured knee abduction or adduction moments (17,27). One study using force platforms reported increased knee abduction moments at initial contact during gait in 14 participants with PFPS compared to 131 asymptomatic participants (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). A study assessing knee kinematics using the KneeKG\u0026reg; in 90 asymptomatic participants reported no increase in knee valgus during the loading phase (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). The participants showed a slight varus (1\u0026ndash;4\u0026deg;) during the loading phase that returned to 0\u0026deg; during the rest of the stance phase (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). In addition to dynamic knee valgus, Phenotype 2 had the highest knee flexion RoM values during stance, the longest VMO activation delay, the highest mean velocity and the longest total CoP excursion in the EC condition. These results may indicate altered knee stability in the frontal and sagittal planes and altered postural stability, which may indicate a lack of neuromuscular control in people with PFPS. However, a loss of proprioceptive ability seems unlikely, as shown by the Y test results and the literature (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe static knee valgus measured using EOS differed across the phenotypes. It was larger for Phenotype 4, characterised by patellar displacement and altered lower-limb alignment. Static knee valgus angle was higher in Phenotypes 2 and 4 than in the contralateral limbs. Several studies assessed the association between static knee valgus and patello-femoral joint stress (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e); however, the association between static knee valgus and PFPS has been poorly investigated (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). A systematic review of 47 studies exploring factors associated with PFPS (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e) found only one study that assessed the relationship between static lower limb malalignment and PFPS. The study found no association between static knee valgus and PFPS in 61 infantry soldiers (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Those results suggest that knee valgus may be a marker of specific PFPS phenotypes.\u003c/p\u003e \u003cp\u003eParticipants with Phenotype 1 had decreased knee flexion/extension RoM during stance in accordance with our main hypothesis. Knee flexion angle at initial contact was lower than for the other phenotypes and the contralateral lower limbs. This is consistent with suggestions that reducing RoM during the early stance phase of gait is a strategy to reduce patellofemoral joint pain (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). We did not find any specific kinematic alterations in Phenotype 3, in accordance with our main hypothesis.\u003c/p\u003e \u003cp\u003eThe mean Q-angle measured on EOS was within normal physiological ranges for all phenotypes and smaller than those reported in previous studies (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). These results are consistent with a systematic review of prospective studies that included 243 individuals with PFPS and found no evidence that a larger Q-angle was a risk factor for PFPS (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eQuadriceps strength was reduced in all phenotypes. A study showed that the endurance Q/H ratio was lower in participants with PFPS than in asymptomatic, nonathletic individuals (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Decreased quadriceps strength and/or endurance have been strongly associated with PFPS (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). In the absence of knee kinematic alterations, knee muscle insufficiency may the main explanatory factor for PFPS in Phenotype 3.\u003c/p\u003e \u003cp\u003eSurprisingly, stability was poorer on the contralateral limb than on the symptomatic limb in the EO condition. This difference may reflect specific training of the symptomatic limb during rehabilitation sessions; 20/45 participants were undergoing physiotherapy at the time of the study.\u003c/p\u003e \u003cp\u003eThe participants in the present study were reasonably comparable to those in similar studies. Although they were older than those in most biomechanical studies of PFPS (1,27), the mean age is consistent with a large epidemiological study that showed that PFPS prevalence peaks at several time points between the ages of 30 and 60 years (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). The moderate pain intensity (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e), the mean level of subjective knee symptoms (\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e) and health-related quality of life (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e) were similar to previous reports. However, symptom duration was longer (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e), which may be related to the mean older age (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e). The large proportion of participants with Phenotype 2 (altered static and/or dynamic lower limb alignment) supports the association between lower limb alignment and PFPS reported in several studies (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). Excessive foot pronation has been associated with tibial medial rotation (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e) tibial abduction and hip adduction (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e), which have been associated with hip muscle weakness (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). However, we found no clear difference in hip abduction strength, tibial medial rotation or foot pronation between the phenotypes or between the pooled symptomatic lower limbs and the contralateral lower limbs. A systematic review of 7 studies and 135 variables found no risk factors for PFPS other than lower knee extension strength (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). The high proportion of participants with Phenotype 2 may also reflect the heterogeneous lower limb alignment in the general population (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e). A cohort study comparing 446 symptomatic and asymptomatic adolescents found various lower limb morphologies in both groups and reported no relationship between knee symptoms and lower limb alignment (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe small proportion of participants with Phenotype 1, characterised by objective patellar displacement, seems surprising given this is a patello-femoral pathology. However, this finding is consistent with a cross-sectional study that found that none of the 127 participants with PFPS met the criteria for patellar hypermobility based on 1 SD from published norms (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e). The low proportion of participants with Phenotype 1 reflects the low prevalence of patellar instability (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). The proportion of patellar displacement may be underestimated because of the difficulty in detecting and measuring patellar displacement using the most common tests (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). The patellar glide test has moderate reliability (Kappa\u0026thinsp;=\u0026thinsp;0.59) (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e), the J-sign has moderate to good reliability (Kappa 0.53 to 0.72) (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e), and the lateral patellar apprehension test has no to fair intra- and inter-rater reliability (-0.01\u0026thinsp;\u0026le;\u0026thinsp;Kappa\u0026thinsp;\u0026le;\u0026thinsp;0.32)(\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn summary, this study suggested that static and dynamic knee valgus is strongly associated with PFPS. The results suggest that 2 main phenotypes can be differentiated in people with PFPS: a type with static and/or dynamic knee valgus, suggesting poor motor control, and a type with no specific kinematic alterations, suggesting knee muscle insufficiency in relation to high knee joint stress.\u003c/p\u003e \u003cp\u003eStrengths and limitations\u003c/p\u003e \u003cp\u003eThe results indicate that kinematic knee parameters during gait can be used to differentiate PFPS phenotypes. The detailed analysis of biomechanical and neuromuscular factors deepens the understanding of PFPS.\u003c/p\u003e \u003cp\u003eThis study has several limitations. The sample size calculation was based on 3 pre-specified groups; however, the statistical analysis was conducted on 4 groups, which may have reduced the study power but which may reflect clinical reality. The primary outcome is in 3D; we cannot be sure that the 3 rotations are independent, and if the p value requires correction. The participants were unequally distributed among the clinical subgroups, with Phenotype 2 including 25/45 participants and Phenotype 1 including only 4/45 participants. An unexpected number of participants had bilateral symptoms, challenging the clinical examinations and diagnosis that rely on inter-limb comparisons, as well as the comparison between the symptomatic and contralateral lower limbs. Our results reported small quantitative values and differences between phenotypes, which raises the question of their clinical relevance. The KneeKG\u0026reg; does not provide a direct measurement of patellar kinematics.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIncreased knee valgus during the gait loading phase and static knee valgus angle differed significantly between 4 clinical PFPS phenotypes and was increased in the phenotype with altered lower limb alignment detected by clinical assessment. The results of the current study support the association between knee valgus and specific PFPS phenotypes. They also highlight the low prevalence of objective patellar displacement in adults with PFPS and the combination of patellar displacement and knee valgus in a small proportion of participants. The results also confirm the contribution of decreased quadriceps strength and endurance to PFPS. Based on this study, 2 main PFPS phenotypes may be differentiated: a type with static and/or dynamic knee valgus suggesting poor motor control, and a type with no specific kinematic alterations suggesting knee muscle insufficiency. This simple classification may help clinicians to provide the most appropriate rehabilitation treatments. Curve analysis derived from the assessment of 3D knee kinematics during gait could be a promising tool to deepen the phenotyping of PFPS participants. Future studies should assess the effectiveness on pain and function of a rehabilitation program that takes into account kinematic gait alterations in people with PFPS.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eADL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eActivities of daily living\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eAKPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eAnterior knee pain scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eCoP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eCentre of pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eEC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eEyes closed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eEO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eEyes open\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eFT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eFemoro-tibial\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eNRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eNumeric rating scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003ePFPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003ePatellofemoral pain syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003ePMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003ePhysical medicine and rehabilitation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eQ/H \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eQuadriceps/Hamstrings\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eRoM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eRange of motion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eSF-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eShort Form Survey\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eSPM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eStatistical parametric mapping\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eVL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eVastus lateralis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eVMO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eVastus medialis obliquus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Comité de Protection des Personnes CPP EST-3 (n°21-12-03). Informed consent was obtained from all participants, including consent for the publication of identifying images.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent for publication of his/her clinical images was obtained from the patient. The identifiable individual in the photo is the principal investigator.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are owned by the promotor Assistance-Publique Hôpitaux de Paris (AP-HP). Data cannot be shared publicly because of AP-HP sharing data policy. Data are available from the AP-HP Institutional Data Access (contact via Unité de Recherche Clinique (URC) Necker-Cochin, Marie Benhammani-Godard, [email protected], for researchers who meet the criteria for access to confidential data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received financial support from Assistance Publique - Hopitaux de Paris (MSERI 204, hôpitaux AP-HP. Centre, Université Paris Cité, 2020). The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributorship statement\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eConceptualisation. AR, MMLC, CN, MC, CD, FR\u003c/li\u003e\n \u003cli\u003eFunding acquisition. MC, AR\u003c/li\u003e\n \u003cli\u003eMethodology. AR, MMLC, NH, CN\u003c/li\u003e\n \u003cli\u003eData acquisition: MC, MMLC, CD, JM, JZ, FL\u003c/li\u003e\n \u003cli\u003eAnalysis. MC,\u0026nbsp;AR, NH, MMLC\u003c/li\u003e\n \u003cli\u003eSupervision. AR, NH, MMLC, GD\u003c/li\u003e\n \u003cli\u003eWriting – Original Draft. Preparation MC, AR\u003c/li\u003e\n \u003cli\u003eWriting – Review \u0026amp; Editing. MC, MMLC, CN, CD, FR, JM, JZ, FL, GD, NH, AR\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Kenny Roger (MD in PMR), Josette Bertheau (PT) and Anne-Marie Fortin (assistant) for their help with the organisation of the participants’ assessments. We thank Adrien Beaud (MSc) for his support with the EMG analysis, Alix Cagnin for his support with the SPM analysis and Hendy Abdoul (MD in public health) and Camille Ollivier (biostatistician) for their help with the statistical analysis. We acknowledge Johanna Robertson, PT, PhD for professional copy editing and constructive criticism.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSmith BE, Selfe J, Thacker D, Hendrick P, Bateman M, Moffatt F, et al. Incidence and prevalence of patellofemoral pain: A systematic review and meta-analysis. Screen HR, \u0026eacute;diteur. PLoS ONE. 11 janv 2018;13(1):e0190892. DOI: 10.1371/journal.pone.0190892.\u003c/li\u003e\n\u003cli\u003eWood L, Muller S, Peat G. The epidemiology of patellofemoral disorders in adulthood: a review of routine general practice morbidity recording. Prim Health Care Res Dev. avr 2011;12(02):157‑64. DOI: 10.1017/S1463423610000460.\u003c/li\u003e\n\u003cli\u003eRoush JR, Curtis Bay R. Prevalence of anterior knee pain in 18-35 year-old females. Int J Sports Phys Ther. ao\u0026ucirc;t 2012;7(4):396‑401. \u003c/li\u003e\n\u003cli\u003eBoling M, Padua D, Marshall S, Guskiewicz K, Pyne S, Beutler A. Gender differences in the incidence and prevalence of patellofemoral pain syndrome. Scand J Med Sci Sports. oct 2010;20(5):725‑30. DOI: 10.1111/j.1600-0838.2009.00996.x.\u003c/li\u003e\n\u003cli\u003eRixe JA, Glick JE, Brady J, Olympia RP. A review of the management of patellofemoral pain syndrome. Phys Sportsmed. sept 2013;41(3):19‑28. 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DOI: 10.1016/j.jor.2023.07.005.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Assistance Publique – Hôpitaux de Paris","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Patellofemoral pain syndrome, 3D kinematics, clinical phenotypes, dynamic alterations.","lastPublishedDoi":"10.21203/rs.3.rs-6906409/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6906409/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Patellofemoral pain syndrome (PFPS) includes static and dynamic lower limb dysfunctions. We used\u0026nbsp; a pragmatic classification differentiating 3 main clinical phenotypes: PFPS with 1) objective patellar displacement, 2) altered extra-patellar alignment, and 3) no altered alignment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: To compare kinematic gait parameters associated with the 3 main clinical phenotypes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e: Prospective comparative study. We used the KneeKG® device (EMOVI) to assess 3D femoro-tibial (FT) rotations during gait. We assessed static FT alignment using EOS imaging, foot posture and knee function using clinical tests, neuromuscular activity using EMG and an isokinetic device, and single-leg stability using posturography. Joint angle time series were compared between phenotypes using Statistical Parametric Mapping. We used the Kruskall-Wallis test (Dwass-Steel test for post-hoc analyses) for group comparisons, p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included 45 participants: 29 (64.4%) females, mean (SD) age 36.3 (13.7) years, BMI: 22.9 (3.8) kg.m\u003csup\u003e2\u003c/sup\u003e, symptom duration: 8.1 (9.6) years. Four (9%) participants were classified as Phenotype 1, 25 (56%) as Phenotype 2 and 10 (22%) as Phenotype 3. Six (13%) participants fitted both Phenotypes 1 and 2; thus, we added Phenotype 4. Knee valgus angle during the gait loading phase differed significantly between phenotypes (p=0.03); Phenotypes 2 and 4 had the highest value (2.1 [1.9]° and 2.1 [2.3]°, respectively). Static knee valgus angle also differed (p=0.014), with Phenotype 4 having the highest value (3.6 [2.0]°). No other parameters differed between groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIncreased knee valgus during the gait loading phase was the only kinematic parameter that differed significantly between the phenotypes. Knee valgus may differentiate PFPS phenotypes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial\u003c/strong\u003e \u003cstrong\u003eregistration\u003c/strong\u003e: NCT05441332 (ClinicalTrials.gov). Date of registration 14/06/2022, date of first publication 2022-07-01, date of last modification 2023-09-07.\u003c/p\u003e\n\u003cp\u003ehttps://clinicaltrials.gov/study/NCT05441332?cond=Patello%20Femoral%20Syndrome\u0026amp;term=PHENOPAT\u0026amp;rank=1\u003c/p\u003e","manuscriptTitle":"Association between 3D knee kinematics and clinical phenotypes in people with Patellofemoral Pain Syndrome: a prospective comparative study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-20 17:50:23","doi":"10.21203/rs.3.rs-6906409/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"913cbeb4-e195-4eb0-8135-50639fcc80af","owner":[],"postedDate":"June 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50243929,"name":"Physical Medicine \u0026 Rehab"},{"id":50243930,"name":"Biomedical Engineering"}],"tags":[],"updatedAt":"2025-06-20T17:50:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-20 17:50:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6906409","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6906409","identity":"rs-6906409","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}