Peak vertical ground reaction force used to identify sub-groups of individuals with differing biomechanical gait profiles post-anterior cruciate ligament reconstruction.

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.

Association of Serum Biochemical Biomarker Profiles of Joint Tissue Inflammation and Cartilage Metabolism With Posttraumatic Osteoarthritis-Related Symptoms at 12 Months After ACLR.

BACKGROUND: Anterior cruciate ligament injury and anterior cruciate ligament reconstruction (ACLR) are risk factors for symptomatic posttraumatic osteoarthritis (PTOA). After ACLR, individuals demonstrate altered joint tissue metabolism indicative of increased inflammation and cartilage breakdown. Serum biomarker changes have been associated with tibiofemoral cartilage composition indicative of worse knee joint health but not with PTOA-related symptoms. PURPOSE/HYPOTHESIS: The purpose of this study was to determine associations between changes in serum biomarker profiles from the preoperative sample collection to 6 months after ACLR and clinically relevant knee PTOA symptoms at 12 months after ACLR. It was hypothesized that increases in biomarkers of inflammation, cartilage metabolism, and cartilage degradation would be associated with clinically relevant PTOA symptoms after ACLR. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: Individuals undergoing primary ACLR were included (N = 30). Serum samples collected preoperatively and 6 months after ACLR were processed to measure markers indicative of changes in inflammation (ie, monocyte chemoattract protein 1 [MCP-1]) and cartilage breakdown (ie, cartilage oligomeric matrix protein [COMP], matrix metalloproteinase 3, ratio of type II collagen breakdown to type II collagen synthesis). Knee injury and Osteoarthritis Outcome Score surveys were completed at 12 months after ACLR and used to identify participants with and without clinically relevant PTOA-related symptoms. K-means cluster analyses were used to determine serum biomarker profiles. One-way analyses of variance and logistic regressions were used to assess differences in Knee injury and Osteoarthritis Outcome Score subscale scores and clinically relevant PTOA-related symptoms between biomarker profiles. RESULTS: Two profiles were identified and characterized based on decreases (profile 1: 67% female; age, 21.4 ± 5.1 years; body mass index, 24.4 ± 2.4) and increases (profile 2: 33% female; age, 21.3 ± 3.2 years; body mass index, 23.4 ± 2.6) in sMCP-1 and sCOMP preoperatively to 6 months after ACLR. Participants with profile 2 did not demonstrate differences in knee pain, symptoms, activities of daily living, sports function, or quality of life at 12 months after ACLR compared to those with profile 1 (P = .56-.81; η2 = 0.002-0.012). No statistically significant associations were noted between biomarker profiles and clinically relevant PTOA-related symptoms (odds ratio, 1.30; 95% CI, 0.23-6.33). CONCLUSION: Serum biomarker changes in MCP-1 and sCOMP within the first 6 months after ACLR were not associated with clinically relevant PTOA-related symptoms.

Biomechanical Threshold Values for Identifying Clinically Significant Knee-Related Symptoms Six Months Following Anterior Cruciate Ligament Reconstruction.

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 (PTOA) following anterior cruciate ligament reconstruction (ACLR). OBJECTIVE: To determine specific gait biomechanical variables that can accurately identify individuals with clinically significant knee-related symptoms post-ACLR, and the corresponding threshold values, sensitivity, specificity, and odds ratios for each biomechanical variable. DESIGN: Cross-sectional analysis. SETTING: Laboratory. PATIENTS OR OTHER PARTICIPANTS: Seventy-one individuals (n=38 female; age=21±4 years; height=1.76±0.11 m; mass=75.38±13.79 kg) who were 6 months post-primary unilateral ACLR (6.2±0.4 months). MAIN OUTCOME MEASURES: 3D motion capture of 5 overground walking trials was used to calculate discrete gait biomechanical variables of interest during stance phase (1st and 2nd 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. Knee Injury and Osteoarthritis Outcome Scores (KOOS) was used to dichotomize patients as symptomatic (n=51) or asymptomatic (n=20) using the Englund et al. 2003 KOOS guidelines for defining clinically significant knee-related symptoms. Separate receiver operating characteristic (ROC) curves and respective areas under the curve (AUC) were used to evaluate the capability of each biomechanical variable of interest for identifying individuals with clinically significant knee-related symptoms. RESULTS: Habitual walking speed (AUC=0.66), vGRF at midstance (AUC=0.69), and 2nd 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 vGRF ≥0.82 BW, and 2nd peak vGRF ≤1.11 BW, 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 utilized to identify individuals with increased odds of clinically significant knee-related symptoms and potential targets for future interventions.

Modifying loading during gait leads to biochemical changes in serum cartilage oligomeric matrix protein concentrations in a subgroup of individuals with anterior cruciate ligament reconstruction.

PURPOSE: Strong observational evidence has linked changes in limb loading during walking following anterior cruciate ligament reconstruction (ACLR) to posttraumatic osteoarthritis (PTOA). It remains unknown if manipulating peak loading influences joint tissue biochemistry. Thus, the purpose of this study is to determine whether manipulating peak vertical ground reaction force (vGRF) during gait influences changes in serum cartilage oligomeric matrix protein (sCOMP) concentrations in ACLR participants. METHODS: Forty ACLR individuals participated in this randomized crossover study (48% female, age = 21.0 ± 4.4 years, BMI = 24.6 ± 3.1). Participants attended four sessions, wherein they completed one of four biofeedback conditions (habitual loading (no biofeedback), high loading (5% increase in vGRF), low loading (5% decrease in vGRF), and symmetrical loading (between-limb symmetry in vGRF)) while walking on a treadmill for 3000 steps. Serum was collected before (baseline), immediately (acute post), 1 h (1 h post), and 3.5 h (3.5 h post) following each condition. A comprehensive general linear mixed model was constructed to address the differences in sCOMP across all conditions and timepoints in all participants and a subgroup of sCOMP Increasers. RESULTS: No sCOMP differences were found across the entire cohort. In the sCOMP Increasers, a significant time × condition interaction was found (F9,206 = 2.6, p = 0.009). sCOMP was lower during high loading than low loading (p = 0.009) acutely (acute post). At 3.5 h post, sCOMP was higher during habitual loading than symmetrical loading (p = 0.001). CONCLUSION: These data suggest that manipulating lower limb loading in ACLR patients who habitually exhibit an acute increase in sCOMP following walking results in improved biochemical changes linked to cartilage health. Key Points • This study assesses the mechanistic link between lower limb load modification and joint tissue biochemistry at acute and delayed timepoints. • Real-time biofeedback provides a paradigm to experimentally assess the mechanistic link between loading and serum biomarkers. • Manipulating peak loading during gait resulted in a metabolic effect of lower sCOMP concentrations in a subgroup of ACLR individuals. • Peak loading modifications may provide an intervention strategy to mitigate the development of PTOA following ACLR.

Practical Guide to Machine Learning and Artificial Intelligence in Surgical Education Research.

This Guide to Statistics and Methods gives an overview of artificial intelligence techniques and tools in surgical education research.

Practical Guide to Experimental and Quasi-Experimental Research in Surgical Education.

This Guide to Statistics and Methods describes the methods and pitfalls of experimental and quasi-experimental study designs in surgical education.

Practical Guide to Assessment Tool Development for Surgical Education Research.

This Guide to Statistics and Methods describes the process of validation and gathering validity evidence for assessment tool development for surgical education research.

Practical Guide to Curricular Development Research.

This Guide to Statistics and Methods provides an overview of performing curricular development research.