Consequences and Prognosis of Running-Related Knee Injuries Among Recreational Runners

Effect of a tailored exercise programme on kinematics and kinetic knee injury risk during different side-cutting

Despite the high incidence of knee injuries reported in non-professional sports, the implementation of specific training programmes aimed at mitigating the kinematic and kinetic factors associated with these injuries remains limited. To determine the effects of a tailored exercise programme on kinematic and kinetic variables during side-cutting activities. Fifty-seven physically active participants were randomised into control group (CG; n: 28) that received no intervention, and an experimental group (EG; n: 29), that performed an individualised exercise programme that included a combination of strength, neuromuscular, proprioceptive, eccentric training and whole-body vibration (WBV) exercises. Knee, hip and trunk angles, vertical ground reaction force (VGRF), force in the antero-posterior (AP) and medio-lateral (ML) axes, acceleration, contact time and impulse were assessed during three types of side-cutting, two open manoeuvres (30º and 45º - SC30 and SC45 -respectively) and one closed manoeuvre (45º - SC45cl-). After the 12-week intervention, EG participants had lower knee extension during all side-cuttings, shorter contact time and lower acceleration, VGRF and impulse compared to CG during side-cutting manoeuvres. A tailored exercise programme could be an effective neuromuscular and biomechanical strategy to reduce risk factors for knee injury in healthy, physically active young people.

Strategies to prevent and manage running-related knee injuries: a systematic review of randomised controlled trials

OBJECTIVE

To evaluate the effectiveness of interventions to prevent and manage knee injuries in runners.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE, EMBASE, CINAHL, Web of Science and SPORTDiscus up to May 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Randomised controlled trials (RCTs) with a primary aim of evaluating the effectiveness of intervention(s) to prevent or manage running-related knee injury.

RESULTS

Thirty RCTs (18 prevention, 12 management) analysed multiple interventions in novice and recreational running populations. Low-certainty evidence (one trial, 320 participants) indicated that running technique retraining (to land softer) reduced the risk of knee injury compared with control treadmill running (risk ratio (RR) 0.32, 95% CI 0.16 to 0.63). Very low-certainty to low-certainty evidence from 17 other prevention trials (participant range: 24 -3287) indicated that various footwear options, multicomponent exercise therapy, graduated running programmes and online and in person injury prevention education programmes did not influence knee injury risk (RR range: 0.55-1.06). In runners with patellofemoral pain, very low-certainty to low-certainty evidence indicated that running technique retraining strategies, medial-wedged foot orthoses, multicomponent exercise therapy and osteopathic manipulation can reduce knee pain in the short-term (standardised mean difference range: -4.96 to -0.90).

CONCLUSION

There is low-certainty evidence that running technique retraining to land softer may reduce knee injury risk by two-thirds. Very low-certainty to low-certainty evidence suggests that running-related patellofemoral pain may be effectively managed through a variety of active (eg, running technique retraining, multicomponent exercise therapy) and passive interventions (eg, foot orthoses, osteopathic manipulation).

PROSPERO REGISTRATION NUMBER

CRD42020150630.

Machine-learned-based prediction of lower extremity overuse injuries using pressure plates

Although running has many benefits for both the physical and mental health, it also involves the risk of injuries which results in negative physical, psychological and economical consequences. Those injuries are often linked to specific running biomechanical parameters such as the pressure pattern of the foot while running, and they could potentially be indicative for future injuries. Previous studies focus solely on some specific type of running injury and are often only applicable to a gender or running-experience specific population. The purpose of this study is, for both male and female, first-year students, (i) to predict the development of a lower extremity overuse injury in the next 6 months based on foot pressure measurements from a pressure plate and (ii) to identify the predictive loading features. For the first objective, we developed a machine learning pipeline that analyzes foot pressure measurements and predicts whether a lower extremity overuse injury is likely to occur with an AUC of 0.639 and a Brier score of 0.201. For the second objective, we found that the higher pressures exerted on the forefoot are the most predictive for lower extremity overuse injuries and that foot areas from both the lateral and the medial side are needed. Furthermore, there are two kinds of predictive features: the angle of the FFT coefficients and the coefficients of the autoregressive AR process. However, these features are not interpretable in terms of the running biomechanics, limiting its practical use for injury prevention.