The Influence of Quadriceps Strength and Rate of Torque Development on the Recovery of Knee Biomechanics During Running After Anterior Cruciate Ligament Reconstruction

BACKGROUND

After anterior cruciate ligament reconstruction (ACLR), altered surgical knee biomechanics during running is common. Although greater quadriceps strength is associated with more symmetrical running knee kinetics after ACLR, abnormal running mechanics persist even after resolution of quadriceps strength deficits. As running is a submaximal effort task characterized by limited time to develop knee extensor torque, quadriceps rate of torque development (RTD) may be more closely associated with recovery of running knee mechanics than peak torque (PT).

PURPOSE

To assess the influence of recovery in quadriceps PT and RTD symmetry on knee kinematic and kinetic symmetry during running over the initial 2 years after ACLR.

STUDY DESIGN

Cohort study; Level of evidence, 3.

METHODS

A total of 39 Division I collegiate athletes (106 testing sessions; 19 female) completed serial isometric performance testing and running analyses between 3 and 24 months after ACLR. Athletes performed maximal and rapid isometric knee extension efforts with each limb to assess PT and RTD between-limb symmetry indices (PTLSI and RTDLSI), respectively. Peak knee flexion difference (PKFDIFF) and peak knee extensor moment limb symmetry index (PKEMLSI) during running were computed. Multivariable linear mixed-effects models assessed the influence of PTLSI and RTDLSI on PKFDIFF and PKEMLSI over the initial 2 years after ACLR.

RESULTS

Significant main effects of RTDLSI (P < .001) and time (P≤ .02) but not PTLSI (P≥ .24) were observed for both PKFDIFF and PKEMLSI models. For a 10% increase in RTDLSI, while controlling for PTLSI and time, a 0.9° (95% CI, 0.5°-1.3°) reduction in PKFDIFF and a 3.5% (95% CI, 1.9%-5.1%) increase in PKEMLSI are expected. For every month after ACLR, a 0.2° (95% CI, 0.1°-0.4°) reduction in PKFDIFF and a 1.3% (95% CI, 0.6%-2.0%) increase in PKEMLSI are expected, controlling for PTLSI and RTDLSI.

CONCLUSION

Quadriceps RTDLSI was more strongly associated with symmetrical knee biomechanics during running compared with PTLSI or time throughout the first 2 years after ACLR.

Quadriceps Performance and Running Biomechanics Influence Femur BMD Changes after ACL Reconstruction in Collegiate Athletes

PURPOSE

Reduced bone mineral density of the distal femur (BMD DF ) can persist long term after anterior cruciate ligament reconstruction (ACLR), even in athletes who return to high levels of competition. These deficits may have implications for the onset and progression of knee osteoarthritis. It is unknown if clinically modifiable factors are associated with losses in BMD DF . This study evaluated the potential influence of knee extensor peak torque (PT), rate of torque development (RTD), as well as peak knee flexion (PKF) angle and peak knee extensor moment (PKEM) during running, on longitudinal changes in BMD DF post-ACLR.

METHODS

After ACLR, 57 Division I collegiate athletes underwent serial whole-body dual-energy x-ray absorptiometry (DXA) scans between 3 and 24 months post-ACLR. Of these, 43 athletes also had isometric knee extensor testing (21 female, 105 observations), and 54 had running analyses (26 female, 141 observations). Linear mixed-effects models, controlling for sex, assessed the influence of surgical limb quadriceps performance (PT and RTD), running mechanics (PKF and PKEM), and time post-ACLR on BMD DF (5% and 15% of femur length). Simple slope analyses were used to explore interactions.

RESULTS

Athletes with RTD less than 7.20 (N·m)·kg -1 ·s -1 (mean) at 9.3 months post-ACLR demonstrated significant decreases in 15% BMD DF over time ( P = 0.03). Athletes with PKEM during running less than 0.92 (N·m)·kg -1 (-1 SD below mean) at 9.8 months post-ACLR demonstrated significant decreases in 15% BMD DF over time ( P = 0.02). Significant slopes were not detected at -1 SD below the mean for PT (1.75 (N·m)·kg -1 , P = 0.07) and PKF (31.3°, P = 0.08).

CONCLUSIONS

Worse quadriceps RTD and running PKEM were associated with a greater loss of BMD DF between 3 and 24 months post-ACLR.

Comparison of eccentric hamstring strength and asymmetry at return-to-sport after hamstring strain injury among those who did and did not re-injure

OBJECTIVES

The primary aim of this study was to describe eccentric hamstring strength magnitude and asymmetry at the time of return-to-sport (RTS) after an index hamstring strain injury (HSI) and determine if there were differences in strength asymmetry at RTS between those who did and did not go on to re-injure within 1-month and within 3-months of RTS.

DESIGN

Cross-sectional study.

SETTING

Laboratory-based.

PARTICIPANTS

Sixty National Collegiate Athletic Association Division I athletes with index HSI.

MAIN OUTCOME MEASURES

Maximum hamstring eccentric strength for each limb, total maximum strength summed across limbs, and between-limb asymmetry at the time of RTS following the index HSI, assessed using the NordBord Hamstring Testing System.

RESULTS

Of the 60 index HSIs, 8 (13%), and 11 (18%) re-injuries occurred within 1 and 3-months of RTS, respectively. There were no differences between those who did and did not re-injure in maximum eccentric force of either limb (p-values≥0.52), total force from both limbs (p-values≥0.47), and between limb force asymmetry (p-values≥0.91), regardless if re-injury occurred within 1 or 3-months after RTS.

CONCLUSIONS

Eccentric hamstring strength and asymmetry measured at the time of RTS did not differ between those who did and did not re-injure within 3-months of RTS.

Vertical Loading Rate Is Not Associated with Running Injury, Regardless of Calculation Method

INTRODUCTION

Loading rate (LR), the slope of the vertical ground reaction force (vGRF), is commonly used to assess running-related injury risk. However, the relationship between LR and running-related injuries, including bone stress injuries (BSI), is unclear. Inconsistent findings may result from the numerous LR calculation methods that exist and their application across different running speeds.

PURPOSE

This study aimed to assess the influence of calculation method and running speed on LR values and to determine the association of LR during healthy running with subsequent injury.

METHODS

Healthy preseason running data and subsequent injury records from Division I cross-country athletes ( n = 79) over four seasons (2015-2019) at 2.68 m·s -1 , preferred training pace, and 4.47 m·s -1 were collected. LR at each speed was calculated four ways: 1) maximum and 2) average slope from 20% to 80% of vGRF magnitude at impact peak (IP), 3) average slope from initial contact to IP, and 4) average slope from 3% to 12% of stance time. Linear mixed effects models and generalized estimation equations were used to assess LR associations.

RESULTS

LR values differed depending on speed and calculation method ( P value <0.001). The maximum slope from 20% to 80% of the vGRF at 4.47 m·s -1 produced the highest LR estimate and the average slope from initial contact to IP at 2.68 m·s -1 produced the lowest. Sixty-four injuries (20 BSI) were observed. No significant association was found between LR and all injuries or BSI across any calculation method ( P values ≥0.13).

CONCLUSIONS

Calculation method and running speed result in significantly different LR values. Regardless of calculation method, no association between LR and subsequent injury was identified. Thus, healthy baseline LR may not be useful to prospectively assess running-related injury risk.

Preseason Eccentric Strength Is Not Associated with Hamstring Strain Injury: A Prospective Study in Collegiate Athletes

INTRODUCTION

Established risk factors for hamstring strain injuries (HSI) include older age and prior HSI. However, these are nonmodifiable and have a limited role in injury prevention. Eccentric hamstring strength is a common component of HSI prevention programs, but its association with injury is less clear.

PURPOSE

This study aimed to determine if eccentric hamstring strength was prospectively associated with HSI among collegiate athletes, while controlling for sex, age, and prior HSI. We hypothesized that athletes with lower eccentric hamstring strength or greater between-limb strength asymmetry at preseason would have an increased risk of HSI.

METHODS

Hamstring eccentric strength measures, maximum total force ( FTotal ) and between-limb asymmetry in maximum force ( FAsym ), were measured at preseason on male and female athletes. HSIs were tracked over the subsequent 12 months. Generalized estimating equations were used to identify univariable and multivariable associations between athlete demographics, eccentric hamstring strength, and HSI risk.

RESULTS

Data for 326 athletes (85 female; 30 track, 43 basketball, 160 American football, 93 soccer) were included, and 64 HSIs were observed. Univariable associations between eccentric hamstring strength and subsequent HSI were nonsignificant ( FTotal : odds ratio [OR], 0.99 (95% confidence interval (CI), 0.93-1.05); P = 0.74; FAsym : OR, 1.35 (95% CI, 0.87-2.09); P = 0.23). No relationship between eccentric hamstring strength and HSI ( FAsym : OR, 1.32 (95% CI, 0.84-2.08); P = 0.23) was identified after adjusting for confounders including sex, age, and prior HSI.

CONCLUSIONS

No association between preseason eccentric hamstring strength and risk of subsequent HSI was identified after controlling for known risk factors and sex among collegiate athletes. Eccentric hamstring strengthening may continue to serve as a preventative approach to HSI, but it does not provide additional insight into HSI risk beyond factors such as age and prior HSI.

A hierarchical clustering approach for examining potential risk factors for bone stress injury in runners

Bone stress injuries (BSI) are overuse injuries that commonly occur in runners. BSI risk is multifactorial and not well understood. Unsupervised machine learning approaches can potentially elucidate risk factors for BSI by looking for groups of similar runners within a population that differ in BSI incidence. Here, a hierarchical clustering approach is used to identify groups of collegiate cross country runners (32 females, 21 males) based on healthy pre-season running (4.47 m·s^-1) gait data which were aggregated and dimensionally reduced by principal component analysis. Five distinct groups were identified using the cluster tree. Visual inspection revealed clear differences between groups in kinematics and kinetics, and linear mixed effects models showed between-group differences in metrics potentially related to BSI risk. The groups also differed in BSI incidence during the subsequent academic year (Rand index = 0.49; adjusted Rand index = -0.02). Groups ranged from those including runners spending less time contacting the ground and generating higher peak ground reaction forces and joint moments to those including runners spending more time on the ground with lower loads. The former groups showed higher BSI incidence, indicating that short stance phases and high peak loads may be risk factors for BSI. Since ground contact duration may itself account for differences in peak loading metrics, we hypothesize that the percentage of time a runner is in contact with the ground may be a useful metric to include in machine learning models for predicting BSI risk.

The development of a HAMstring InjuRy (HAMIR) index to mitigate injury risk through innovative imaging, biomechanics, and data analytics: protocol for an observational cohort study

Background

The etiology of hamstring strain injury (HSI) in American football is multi-factorial and understanding these risk factors is paramount to developing predictive models and guiding prevention and rehabilitation strategies. Many player-games are lost due to the lack of a clear understanding of risk factors and the absence of effective methods to minimize re-injury. This paper describes the protocol that will be followed to develop the HAMstring InjuRy (HAMIR) index risk prediction models for HSI and re-injury based on morphological, architectural, biomechanical and clinical factors in National Collegiate Athletic Association Division I collegiate football players.

Methods

A 3-year, prospective study will be conducted involving collegiate football student-athletes at four institutions. Enrolled participants will complete preseason assessments of eccentric hamstring strength, on-field sprinting biomechanics and muscle–tendon volumes using magnetic-resonance imaging (MRI). Athletic trainers will monitor injuries and exposure for the duration of the study. Participants who sustain an HSI will undergo a clinical assessment at the time of injury along with MRI examinations. Following completion of structured rehabilitation and return to unrestricted sport participation, clinical assessments, MRI examinations and sprinting biomechanics will be repeated. Injury recurrence will be monitored through a 6-month follow-up period. HAMIR index prediction models for index HSI injury and re-injury will be constructed.

Discussion

The most appropriate strategies for reducing risk of HSI are likely multi-factorial and depend on risk factors unique to each athlete. This study will be the largest-of-its-kind (1200 player-years) to gather detailed information on index and recurrent HSI, and will be the first study to simultaneously investigate the effect of morphological, biomechanical and clinical variables on risk of HSI in collegiate football athletes. The quantitative HAMIR index will be formulated to identify an athlete’s propensity for HSI, and more importantly, identify targets for injury mitigation, thereby reducing the global burden of HSI in high-level American football players.

Trial Registration The trial is prospectively registered on ClinicalTrials.gov (NCT05343052; April 22, 2022).

Spatial frequency analysis detects altered tissue organization following hamstring strain injury at time of injury but not return to sport

Background

Hamstring strain injury (HSI) diagnosis is often corroborated using ultrasound. Spatial frequency analysis (SFA) is a quantitative ultrasound method that has proven useful in characterizing altered tissue organization. The purpose of this study was to determine changes in muscular tissue organization using SFA following HSI.

Methods

Ultrasound B-mode images were captured at time of injury (TOI) and return to sport (RTS) in collegiate athletes who sustained an HSI. Spatial frequency parameters extracted from two-dimensional Fourier Transforms in user-defined regions of interest (ROI) were analyzed. Separate ROIs encompassed injured and adjacent tissue within the same image of the injured limb and mirrored locations in the contralateral limb at TOI. The ROIs for RTS images were drawn to correspond to the injury-matched location determined from TOI imaging. Peak spatial frequency radius (PSFR) and the fascicular banded pattern relative to image background (Mmax%) were compared between injured and adjacent portions within the same image with separate paired t-tests. Within-image differences of SFA parameters in the injured limb were calculated and compared between TOI and RTS with Wilcoxon rank sum tests.

Results

Within the injured limb at TOI, PSFR differences in injured and healthy regions did not strictly meet statistical significance (p = 0.06), while Mmax% was different between regions (p < 0.001). No differences were observed between regions in the contralateral limb at TOI (PSFR, p = 0.16; Mmax%, p = 0.30). Significant within-image differences in PSFR (p = 0.03) and Mmax% (p = 0.04) at RTS were detected relative to TOI.

Conclusions

These findings are a first step in determining the usefulness of SFA in muscle injury characterization and provide quantitative assessment of both fascicular disruption and edema presence in acute HSI.

Running Biomechanics Before Injury and 1 Year After Anterior Cruciate Ligament Reconstruction in Division I Collegiate Athletes

BACKGROUND

Preinjury running biomechanics are an ideal comparator for quantifying recovery after anterior cruciate ligament (ACL) reconstruction (ACLR), allowing for assessments within the surgical and nonsurgical limbs. However, availability of preinjury running biomechanics is rare and has been reported in case studies only.

PURPOSE/HYPOTHESIS

The purpose of this study was to determine if running biomechanics return to preinjury levels within the first year after ACLR among collegiate athletes. We hypothesized that (1) surgical knee biomechanics would be significantly reduced shortly after ACLR and would not return to preinjury levels by 12 months and (2) nonsurgical limb mechanics would change significantly from preinjury.

STUDY DESIGN

Cohort study; Level of evidence, 2.

METHODS

Thirteen Division I collegiate athletes were identified between 2015 and 2020 (6 female; mean ± SD age, 20.7 ± 1.3 years old) who had whole body kinematics and ground-reaction forces recorded during treadmill running (3.7 ± 0.6 m/s) before sustaining an ACL injury. Running analyses were repeated at 4, 6, 8, and 12 months (4M, 6M, 8M, 12M) after ACLR. Linear mixed effects models were used to assess differences in running biomechanics between post-ACLR time points and preinjury within each limb, reported as Tukey-adjusted P values.

RESULTS

When compared with preinjury, the surgical limb displayed significant deficits at all postoperative assessments (P values <.01; values reported as least squares mean difference [SE]): peak knee flexion angle (4M, 13.2° [1.4°]; 6M, 9.9° [1.4°]; 8M, 9.8° [1.4°]; 12M, 9.0° [1.5°]), peak knee extensor moment (N·m/kg; 4M, 1.32 [0.13]; 6M, 1.04 [0.13]; 8M, 1.04 [0.13]; 12M, 0.87 [0.15]; 38%-57% deficit), and rate of knee extensor moment (N·m/kg/s; 4M, 22.7 [2.4]; 6M, 17.9 [2.3]; 8M, 17.5 [2.4]; 12M, 16.1 [2.6]; 33%-46% deficit). No changes for these variables from preinjury (P values >.88) were identified in the nonsurgical limb.

CONCLUSION

After ACLR, surgical limb knee running biomechanics were not restored to the preinjury state by 12M, while nonsurgical limb mechanics remained unchanged as compared with preinjury. Collegiate athletes after ACLR demonstrate substantial deficits in running mechanics as compared with preinjury that persist beyond the typical return-to-sport time frame. The nonsurgical knee appears to be a valid reference for recovery of the surgical knee mechanics during running, owing to the lack of change within the nonsurgical limb.

Lower step rate is associated with a higher risk of bone stress injury: a prospective study of collegiate cross country runners

OBJECTIVES

To determine if running biomechanics and bone mineral density (BMD) were independently associated with bone stress injury (BSI) in a cohort of National Collegiate Athletic Association Division I cross country runners.

METHODS

This was a prospective, observational study of 54 healthy collegiate cross country runners over three consecutive seasons. Whole body kinematics, ground reaction forces (GRFs) and BMD measures were collected during the preseason over 3 years via motion capture on an instrumented treadmill and total body densitometer scans. All medically diagnosed BSIs up to 12 months following preseason data collection were recorded. Generalised estimating equations were used to identify independent risk factors of BSI.

RESULTS

Univariably, step rate, centre of mass vertical excursion, peak vertical GRF and vertical GRF impulse were associated with BSI incidence. After adjusting for history of BSI and sex in a multivariable model, a higher step rate was independently associated with a decreased risk of BSI. BSI risk decreased by 5% (relative risk (RR): 0.95; 95% CI 0.91 to 0.98) with each one step/min increase in step rate. BMD z-score was not a statistically significant risk predictor in the final multivariable model (RR: 0.93, 95% CI 0.85 to 1.03). No other biomechanical variables were found to be associated with BSI risk.

CONCLUSION

Low step rate is an important risk factor for BSI among collegiate cross country runners and should be considered when developing comprehensive programmes to mitigate BSI risk in distance runners.

Factors Influencing Base of Gait During Running: Consideration of Sex, Speed, Kinematics, and Anthropometrics

CONTEXT

A narrow base of gait (BOG), the mediolateral distance between the foot and the body's line of gravity at midstance, during running is a suggested cause of injuries such as iliotibial band syndrome and tibial stress injury. However, an understanding of modifiable and nonmodifiable factors that influence BOG is lacking, which limits the development of corrective strategies.

OBJECTIVE

To determine if BOG varies by sex and running speed and the influence of running kinematics and anthropometrics on BOG.

DESIGN

Cross-sectional study.

SETTING

Record review of routinely collected performance data from a National Collegiate Athletic Association Division I intercollegiate athletic program.

PATIENTS OR OTHER PARTICIPANTS

A total of 166 Division I collegiate athletes (basketball, cross-country, football, soccer).

MAIN OUTCOME MEASURE(S)

Running biomechanics (N = 166) and dual-energy x-ray absorptiometry-derived anthropometric data (n = 68) were extracted. Running variables were BOG, step rate, stride length, foot-inclination angle, center-of-mass vertical displacement, heel-to-center of mass anteroposterior distance, and peak stance-phase angles: hip flexion, hip adduction, pelvic drop, knee flexion, and ankle dorsiflexion. Extracted anthropometric variables were height; leg, femur, and tibia length; and anterior-superior iliac spine, hip-joint, and greater trochanter width. We calculated linear mixed-effects models to assess the influence of sex and running speed on BOG and identify the kinematic and anthropometric variables most associated with BOG.

RESULTS

A significant interaction between sex and running speed on BOG was observed, with males demonstrating a smaller BOG than females at faster speeds and BOG decreasing overall with speed. The kinematic measures most associated with BOG at preferred running speed were foot-inclination angle at initial contact and peak stance-phase hip adduction and ankle dorsiflexion. Anterior-superior iliac spine width was the anthropometric variable most associated with BOG at preferred running speed.

CONCLUSIONS

Sex and running speed must be considered when determining the appropriateness of an individual's BOG. Additionally, BOG was associated with several potentially modifiable kinematic parameters.

Foot Angle and Loading Rate during Running Demonstrate a Nonlinear Relationship

Vertical loading rates are typically found to be lower in forefoot compared to rearfoot strikers, promoting the idea that forefoot striking is desirable and may reduce running injury risk. However, prior work using linear models has shown that foot inclination angle (FIA) at initial contact is a poor predictor of vertical loading rate, suggesting a more complex association exists.

PURPOSE

To determine if a nonlinear model superiorly describes the relationship between FIA and average vertical loading rate (AVLR). Secondary analyses assessed the influence of sex and sport on the association between FIA and AVLR.

METHODS

Whole body kinematics and vertical ground reaction forces were collected for 170 healthy National Collegiate Athletic Association Division I athletes (97 males; 81 cross-country runners) during treadmill running at 2.68, 3.35, and 4.47 m·s. Foot inclination angle and AVLR were calculated for 15 strides and averaged across strides for each limb. Polynomial mixed effects models assessed linear and nonlinear trends in the relationship between FIA and AVLR across the entire sample and accounting for sex and sport participation.

RESULTS

Average vertical loading rate was lowest at the extremes of FIA (i.e., -15°, 20°), whereas greater AVLR were observed between 5° and 10°. The cubic model resulted in a significantly better fit than the linear model (P < 0.001). Average vertical loading rate was also more variable among FIA associated with rearfoot and midfoot strike than forefoot strike. Adding sex to the model did not influence model fit; though, controlling for sport minimally improved model fit.

CONCLUSIONS

The relationship between FIA and AVLR is best represented by a cubic model. Consequently, FIA should be treated as a continuous variable. Reducing FIA into categories may misrepresent the relationship between FIA and other gait variables.