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Neuromuscular training strategies for preventing lower limb injuries: what's new and what are the practical implications of what we already know?
  1. Markus Hübscher,
  2. Kathryn M Refshauge
  1. Faculty of Health Sciences, The University of Sydney, Sydney, New South Wales, Australia
  1. Correspondence to Dr Markus Hübscher, Faculty of Health Sciences, The University of Sydney, 75 East St, Lidcombe, NSW 2141, Australia; markus.huebscher{at}sydney.edu.au

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Sports and recreation injuries are now known to be a significant public health problem. Lower limb injuries sustained during childhood and adolescence are associated with increased morbidity, including early development of osteoarthritis and long-term pain and disability;1 ,2 ultimately interfering with work, sports participation and a healthy level of physical activity.

In March 2010, we published a systematic review and meta-analysis (literature search conducted October 2008) on the effectiveness of neuromuscular training for prevention of sports injuries in athletes.3 Seven high-quality studies involving young male and female athletes (12–24 years) were included. Participants were engaged in organised sports, including basketball, volleyball, soccer, team handball, hockey and floorball. The pooled analyses revealed that multi-intervention exercises (comprising balance and agility training, stretching, plyometrics, running exercises, cutting and landing technique, strength training) significantly reduced the relative risk of lower limb injuries (relative risk reduction (RRR)=39%, 95% CI  23% to 51%), acute knee injuries (RRR=54%, 95% CI 24%  to 72%) and ankle sprain injuries (RRR=50%, 95% CI 21% to 69%).

What is new since then?

Since the publication of our review, five key trials have been published that aimed to reduce the incidence of lower limb injuries in young basketball or soccer players (table 1).

View this table:
Table 1

Key findings since publication of our previous systematic review

These studies are well designed with respect to important key criteria of internal validity and risk of bias, such as randomisation, allocation concealment, blinding of outcome assessors, statistical adjustment (eg, clustering and previous …

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