Ashley N. Buck

Objective: High body mass index (BMI ≥ 27 kg/m ² ) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and characterize the shared and individual variation between vGRF profiles and clinical features in individuals with KOA and high BMI. Methods: Baseline gait and clinical data from the Intensive Diet and Exercise for Arthritis trial (N = 431; 29% male; age 65 ± 6 years; BMI 34 ± 4 kg/m ² ) were analyzed. vGRF waveforms (n = 2,394) were represented using three functional data analysis methods: time and body weight normalization, elastic shape analysis, and optimal transport (OT). Principal component analysis extracted the dominant vGRF modes of variation, and data integration via analysis of subspaces (DIVAS) quantified shared and individual variation among vGRF profiles and 40 clinical features. Results: A sustained loading phenotype emerged across all vGRF representations (lesser early‐ and late‐stance vGRF; greater midstance vGRF). DIVAS identified shared variation between sustained loading and higher BMI, elevated inflammatory biomarkers, greater pain, worse Kellgren‐Lawrence grade, and slower walking speed. OT identified a temporal loading phenotype that shared variation with female sex. Conclusion: Unsupervised ML identified a sustained loading biomechanical phenotype that shared variation with greater BMI, increased inflammation, worse radiographic severity, and slower walking speed. These data highlight the complex interplay among gait biomechanics and clinical KOA features in individuals with high BMI and may help to guide future work evaluating targeted gait‐retraining interventions.

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Background/Objectives: The educational needs of individuals with OA and obesity can drive personalized resources for effective dietary interventions that align patient interests with weight and disease management. Therefore, the purpose of the present study was to evaluate differences in nutritional education topics of interest between patients with OA who are characterized as having higher (≥30 kg/m²; HBMI) and lower BMI (2; LBMI). Methods: Cross-sectional survey data (n = 296) were dichotomized into HBMI (n = 172; BMI: 38.67 ± 6.59 kg/m²) and LBMI (n = 124; BMI: 25.59 ± 3.00 kg/m²) groups. A mixed-method approach examined group differences across four primary domains: (i) strategies for weight management and healthy lifestyle, (ii) interest in vitamins and supplements, (iii) foods and nutrient with anti-inflammatory properties, and (iv) dietary patterns for weight loss. Logistic regression models compared topic interests between groups. Thematic analysis of open-ended responses captured additional insights. Results: Compared to LBMI participants, those in the HBMI group showed greater interest in weight loss strategies, emotional eating, and diets such as low-carbohydrate and ketogenic approaches, but less interest in general supplement information and plant-based diets. HBMI also had greater interest in practical strategies (e.g., feeling full, affordable foods) and reduced interest in certain anti-inflammatory foods. Both groups expressed a desire for evidence-based resources on foods that promote joint health. Conclusions: BMI-specific differences in nutritional education preferences highlight the need for tailored, patient-centered strategies in OA management. Addressing these differences may improve the effectiveness of education interventions and enhance patient–provider communication around diet and lifestyle in OA care.

A history of anterior cruciate ligament reconstruction (ACLR) and high body mass index (BMI) are strong risk factors for incident knee osteoarthritis. Limited research has evaluated the interaction between ACLR and high BMI on limb‐level loading and early deleterious changes in cartilage health. The purpose of this study was to separately investigate the association between vertical ground reaction force (vGRF) loading profiles during gait and tibiofemoral cartilage composition in ACLR patients with high and normal BMI. Forty‐three participants with primary unilateral ACLR (17 ± 14 months post‐ACLR) were categorized as high (≥ 25 kg/m²; n = 18) or normal (< 25 kg/m²; n = 25) BMI and performed an overground gait at self‐selected speed. For biomechanical outcomes, we calculated the differences between first peak and midstance minimum (∆vGRF1) and between the second peak and midstance minimum (∆vGRF2). T1ρ relaxation time interlimb ratios (ILR), calculated as the T1ρ relaxation time in the ACLR relative to the uninjured limb, were calculated for the medial and lateral tibia and femur. Stepwise linear regressions were used to determine associations between biomechanical outcomes and T1ρ relaxation time ILR for each region of interest. Lesser ∆vGRF1 and ∆vGRF2 in the high‐BMI group significantly associated with greater T1ρ relaxation time ILR for the medial femoral condyle (ΔR² = 0.28, p = 0.03; ΔR² = 0.25, p = 0.04, respectively) and tibial plateau (ΔR² = 0.55, p < 0.001; ΔR² = 0.25, p = 0.004, respectively). Aberrant limb‐level loading, characterized by less dynamic limb loading, is linked to deleterious changes in tibiofemoral cartilage in ACLR patients with high BMI, suggesting that gait retraining may be more critical for ACLR with a BMI ≥ 25 kg/m².

Purpose: Determine the associations of body mass index (BMI) and body composition (lean and fat mass) with i ) patient-reported outcomes, ii ) quadriceps strength, and iii ) physical performance in anterior cruciate ligament reconstruction (ACLR) patients. Methods: Thirty-four individuals participated (56% female; 22 ± 4 yr; % body fat: 22.9% ± 6.7%). Dual-energy x-ray absorptiometry was used to measure percent lean (%LM) and fat (%FM) mass for the whole-body, and the whole-limb and thigh region of the ACLR limb. Knee Injury and Osteoarthritis Outcomes Score (KOOS) subscales were used to evaluate patient-reported outcomes. Isometric quadriceps strength (maximal voluntary isometric contraction (MVIC)) was measured using an isokinetic dynamometer with the knee flexed at 90°. Single-leg hop (SLH) distance was used to evaluate physical performance. Spearman rank correlations were used to separately evaluate the associations between BMI and body composition with KOOS, MVIC, and SLH. Results: BMI was not significantly associated with KOOS, MVIC, or SLH ( P > 0.05). Greater whole-body %LM was associated with greater MVIC and SLH, whereas greater whole-body %FM was associated with worse KOOS Activities of Daily Life, MVIC, and SLH ( P < 0.05). Greater whole-limb %LM was associated with greater MVIC, whereas greater whole-limb %FM was associated with worse KOOS Symptoms, Pain, Quality of Life, and MVIC ( P < 0.05). Greater thigh %LM was associated with better KOOS Symptoms and MVIC, and greater thigh %FM was associated with worse KOOS Symptoms, Pain, Quality of Life, and MVIC ( P < 0.05). Conclusions: Body composition characteristics of higher %LM and lower %FM were associated with better clinical outcomes in ACLR patients of normal BMI status, thereby elucidating a potential modifiable target to mitigate poor ACLR-related outcomes. Future research should further evaluate mechanistic links between body composition and ACLR-related outcomes to inform clinical practice and rehabilitation frameworks.

Context: Slower habitual walking speed and aberrant gait biomechanics are linked to clinically significant knee-related symptoms and articular cartilage composition changes linked to posttraumatic osteoarthritis after anterior cruciate ligament reconstruction (ACLR). Objectives: To (1) determine whether specific gait biomechanical variables can accurately identify individuals with clinically significant knee-related symptoms post-ACLR and (2) determine the corresponding threshold values, sensitivity, specificity, and odds ratios for each biomechanical variable. Design: Cross-sectional study. Setting: Laboratory. Patients or Other Participants: A total of 71 individuals (38 female, 33 male; age = 21 ± 4 years, height = 1.76 ± 0.11 m, mass = 75.38 ± 13.79 kg, time after primary unilateral ACLR = 6.2 ± 0.4 months). Main Outcome Measure(s): Three-dimensional motion capture of 5 overground walking trials was used to calculate discrete gait biomechanical variables of interest during stance phase (first and second peak vertical ground reaction force [vGRF], midstance minimum vGRF, peak internal knee-abduction and -extension moments, and peak knee-flexion angle), along with habitual walking speed. Previously established Knee Injury and Osteoarthritis Outcome Score cutoff scores were used to define patients with (ie, symptomatic; n = 51) and those without (ie, asymptomatic; n = 20) clinically significant knee-related symptoms. Separate receiver operating characteristic curves and respective areas under the curve (AUCs) were used to evaluate the capability of each biomechanical variable of interest to identify individuals with clinically significant knee-related symptoms. Results: Habitual walking speed (AUC = 0.66), vGRF at midstance (AUC = 0.69), and second peak vGRF (AUC = 0.76) demonstrated low to moderate accuracy for identifying individuals with clinically significant knee-related symptoms. Individuals who exhibited habitual walking speeds ≤ 1.27 m/s, midstance minimum vGRF ≥ 0.82 body weights, and second peak vGRF ≤ 1.11 body weights demonstrated 3.13, 6.36, and 9.57 times higher odds of experiencing clinically significant knee-related symptoms, respectively. Conclusions: Critical thresholds for gait variables may be used to identify individuals with increased odds of clinically significant knee-related symptoms and potential targets for future interventions.

Context: Gait biomechanics and daily steps are important aspects of knee-joint loading that change after anterior cruciate ligament reconstruction (ACLR). Understanding their relationship during the first 6 months post-ACLR could help clinicians develop comprehensive rehabilitation interventions that promote optimal joint loading after injury, thereby improving long-term knee-joint health. Objectives: To compare biomechanical gait waveforms throughout stance at early time points post-ACLR in individuals with different daily step behaviors at 6 months post-ACLR and to examine how these gait waveforms compare with those of uninjured controls. Design: Case-control study. Setting: Laboratory. Patients or Other Participants: A total of 32 individuals with primary ACLR assigned to the low-step group (LSG; n = 13) or the high-step group (HSG; n = 19) based on their average daily steps at 6 months post-ACLR and 32 uninjured matched controls. Main Outcome Measure(s): Gait biomechanics were collected at 2, 4, and 6 months post-ACLR for the ACLR groups and at a single session for the control group. Knee-adduction moment, knee-extension moment (KEM), and knee-flexion angle (KFA) waveforms were calculated during gait stance and then compared via functional waveform analyses. Mean differences and corresponding 95% CIs between groups were reported. Results: Primary results demonstrated less KFA (1%–45% versus 79%–92% of stance) and greater KEM (65%–93% of stance) at 2 months and greater knee-adduction moment (14%–20% versus 68%–92% of stance) at 4 months post-ACLR for the HSG compared with the LSG. Knee-adduction moment, KEM, and KFA waveforms differed across various proportions of stance at all time points between the step and control groups. Conclusions: Differences in gait biomechanics were present at 2 and 4 months post-ACLR between step groups, with the LSG demonstrating an overall more flexed knee and more profound stepwise underloading throughout stance than the HSG. The results indicate a relation between early gait biomechanics and later daily step behaviors post-ACLR.

The purpose of this study was to compare gait biomechanics between limbs and to matched uninjured controls (i.e., sex, age, and body mass index) preoperatively and at 2, 4, 6, and 12 months following primary unilateral anterior cruciate ligament reconstruction (ACLR). Functional mixed effects models were used to identify differences in gait biomechanics throughout the stance phase between the a) ACLR limb and uninvolved limb, b) ACLR limb and controls, and c) uninvolved limb and controls. Compared with the uninvolved limb, the ACLR limb demonstrated lesser knee extension moment (KEM; within 8–37% range of stance) during early stance as well as lesser knee flexion moment (KFM; 45–84%) and greater knee flexion angle (KFA; 43–90%) during mid‐ to late stance at all timepoints. Compared with controls, the ACLR limb demonstrated lesser vertical ground reaction force (vGRF; 5–26%), lesser KEM (7–47%), and lesser knee adduction moment (KAM; 12–35%) during early stance as well as greater vGRF (39–63%) and greater KFA (34–95%) during mid‐ to late stance at all timepoints. Compared with controls, the uninvolved limb demonstrated lesser KFA (1–56%) and lesser KEM (12–54%) during early to mid‐stance at all timepoints. While gait becomes more symmetrical over the first 12 months post‐ACLR, the ACLR and uninvolved limbs both demonstrate persistent aberrant gait biomechanics compared to controls. Biomechanical waveforms throughout stance can be generally described as less dynamic following ACL injury and ACLR compared with uninjured controls.

Lesser peak vertical ground reaction force (vGRF) has been widely reported among individuals with anterior cruciate ligament reconstruction (ACLR). Peak vGRF remains less than uninjured controls and relatively stable during the first year following ACLR. However, it is unknown whether there are subgroups of individuals exhibiting consistently greater peak vGRF in the first 6‐months following ACLR and if individuals with consistently greater peak vGRF exhibit kinematic and kinetic gait differences compared to individuals with low vGRF. The purpose of this study was to determine if distinct clusters exist based upon magnitude of peak vGRF 2‐ and 6‐months post‐ACLR. Subsequently, we explored between cluster differences in vGRF, knee flexion angle, and sagittal and frontal plane knee kinetics throughout stance between clusters. Forty‐three individuals (58.1%female, 21.4 ± 4.4 years‐old, 95.3% patellar‐tendon autograft) completed five gait trials at their habitual walking speed 2‐ and 6‐months post‐ACLR. A single K‐means cluster analysis was used to identify clusters of individuals based on peak vGRF at 2‐ and 6‐months post‐ACLR. Functional waveform analyses were used to compare gait outcomes between clusters with and without controlling for gait speed and age. We identified two clusters that included a subgroup with high vGRF (n = 16) and low vGRF (n = 27). The cluster with high vGRF demonstrated greater vGRFs, knee flexion angles, and knee extension moments during early stance as compared to the low vGRF cluster 2‐ and 6‐months post‐ACLR. Individuals with peak vGRF ≥1.02 times body‐weight 2‐months post‐ACLR had 35.4 times greater odds of being assigned to the high vGRF cluster.