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Measuring only hop distance during single leg hop testing is insufficient to detect deficits in knee function after ACL reconstruction: a systematic review and meta-analysis.

Review written by Stephen King info

Key Points

  1. A symmetrical SLHD (single leg hop for distance) test does not indicate restoration of normal lower-limb kinematics or kinetics.
  2. Achieving >90% hop distance for the ACLR leg compared with the uninjured leg is usually associated with compensatory movements at the hip, ankle and/or knee joints.

BACKGROUND & OBJECTIVE

ACL injuries are often associated with long periods of time out of sport and high recurrence rates. Hop testing is often performed to assess readiness to return to sport post injury. The most common hop testing battery is the limb symmetry index. The limb symmetry index is a battery of four hop tests (single leg hop for distance, triple hop, crossover hop and 6-m timed hop) combined to assess symmetry between the injured and non-injured sides. Traditionally, a LSI of >90% is recommended before returning to sport (1). More recent research indicates that people who have sustained an ACL injury also have deficits on the non-injured side, and that the quality of the movement pattern being used to complete the task may not be optimal.

A limb symmetry index of >90% is recommended before returning to sport after ACLR.
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We need to ensure we assess our clients more thoroughly and take them beyond the traditional orthopaedic approach and assess in all three planes of motion.

METHODS

The authors performed a systematic review and meta-analysis that involved a search of 8 large electronic databases until April 2018 using the key search terms: ACL, Reconstruction, Biomechanics and Hop test. 19 studies were included in the review. The inclusion criteria for this systematic review included studies of males and female with any graft type examining kinematics, kinetics and/or EMG data of the ACLR knee and asymptomatic controls during hop tests. Studies were excluded from the review if they were animal or cadaveric studies and not observational study designs or randomized controlled trials.

RESULTS

Hop testing results were compared in two main ways: 1 - compared to the contralateral leg; and 2 - compared to healthy controls. Most of the results found had strong evidence, but only for small effects.

The results compared to the contralateral leg

Kinematically, they found the following in the ACLR leg:

  • Less peak knee flexion

  • Less knee ROM

  • Less hip flexion ROM

  • Lower peak dorsiflexion and less ROM

  • Lower peak hip abduction and less ROM, and higher hip adduction in landing.

Kinetically, they found:

  • Lower knee flexion moments

The results compared to healthy controls

Kinematically, they found the following in ACLR individuals:

  • Less peak knee flexion and ROM in both take-off and landing

  • Lower knee adduction angles

  • Lower peak knee internal rotation during landing

Kinetically, they found:

  • Lower knee flexion moments

  • Increased peak knee adduction moments

  • Higher peak ankle dorsiflexion moments

LIMITATIONS

All studies regardless of methodological quality were included in the review, which means that low-quality studies may have been included and influenced the results. Furthermore, a lot of the studies used skin-based markers that are affected during high impact tasks, which may impact the quality of the data collected.

CLINICAL IMPLICATIONS

Hop testing has gained popularity in making better return to sport decisions (2). This has been a mainstay of my own practice for quite some time and this research displays some observations I’ve made when ACLR clients are performing hop tests. We need to ensure we assess our clients more thoroughly and take them beyond the traditional orthopaedic approach and assess in all three planes of motion. Just because ‘they can get it in done’, does not mean they’re getting it done efficiently or the same side to side.

The movement differences that were seen in this review are often only subtle changes. In this study, there was typically around four degrees difference between sides, which is difficult to assess with the technology used in these studies reliably, let alone the naked eye.

In practice, a useful bit of technology that can be used to slow down these movements is a smart device (and pair it up with a TV) with an application like Hudl Technique or Spark Motion. Whilst not at the same standard as a University biomechanics lab, it can provide some useful clinical information and allow you to assess the qualitative aspects of movement quantitively in a very quick and easy manner.

Technology is vital to getting better outcomes with ACL injuries. To get a better understanding of these types of movements, other technology such as force plates can be useful to provide quick data about movements likes hops and measure things you cannot see visually or assess in any other way.

The reason for side-to-side differences in hop testing likely differs between individuals. However, if you perform a thorough qualitative and quantitate assessment of your individual client and assess all of the physical capacities required to achieve their goals (e.g. other movement patterns, balance/proprioception, speed and agility, fitness, strength, power and flexibility), you will be able to make better informed decisions and program optimally for the individual.

+STUDY REFERENCE

Kotsifaki A, Korakakis V, Whiteley R, Van Rossom S and Jonkers I (2019) Measuring only hop distance during single leg hop testing is insufficient to detect deficits in knee function after ACL reconstruction: a systematic review and meta-analysis. British Journal of Sports Medicine, pp.bjsports-2018-099918.

SUPPORTING REFERENCE

  1. Oberländer KD, Brüggemann G-P, Höher J, et al. Altered landing mechanics in ACLreconstructed patients. Med Sci Sports Exerc 2013;45:506–13.
  2. Samaan MA, Ringleb SI, Bawab SY, et al. Altered lower extremity joint mechanics occur during the StAR excursion balance test and single leg hop after ACLreconstruction in a collegiate athlete. Comput Methods Biomech Biomed Engin 2018;21:344–58