Isokinetic conference 2015 London strength as a risk factor for hamstring injury
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A summarized version of my presentation Is strength a risk factor for hamstring strain injury (Isokinetic Conference 2015: Football Medicine Strategies for Player Care)
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Isokinetic conference 2015 London strength as a risk factor for hamstring injury
- 1. STRENGTH AS A RISK FACTOR FOR HAMSTRING STRAIN INJURY - Is it still a piece of the puzzle? Nicol van Dyk Rehabilitation Department
- 3. Contributing Authors – Rod Whiteley – Cristiano Eirale – Bhavesh Kumar – Bruce Hamilton – Hans Tol – Roald Bahr – Erik Witvrouw
- 4. • Hamstring Strain Injuries (HSI) remain the most common muscle injury in football (Hagglund et al 2013, Ekstrand et al 2011, Eirale et al 2013) Introduction
- 5. • Incidence 12-15% (Opar et al 2012) • 37% of all muscle injuries (Ekstrand et al 2011) Introduction
- 6. Introduction Fatigue Core Stability Neuromuscular Control Flexibility Strength Multifactorial Nature of HSI (Mendiguchia et al 2012) Psychological Factors Architecture
- 7. Introduction
- 8. Aim Can Strength be identified as a risk factor for Hamstring Injury?
- 9. All Teams in Qatar Stars League (n=14 teams) 2010-2014 No isokinetic tests performed (n=52 subjects) Isokinetic Tests during Periodic Health Evaluation (n=617 subjects) mean follow up of 2.24 years Q Con 60°/s (n= 556) H Con 60°/s (n= 555) Q Con 300°/s (n= 556) H Con 300°/s (n=556) H Ecc 60°/s (n=562) Materials & Methods 1050 Isokinetic Tests performed Total Injuries 187 1st time injuries 131 617 subjects 187 injuries
- 10. • Clustered Logistic Regression Analysis with repeated measures Confounding Variables Strength Variables Statistical Analysis Season Q Con 60 BW H Ecc 60 BW H Con 60 BW Q Con 300 BW Q Con 60/ H Con 60 Q Con 300/ H Con 300 H Con 60/ H Ecc 60 Q Con 300/ H Ecc 60 H Con 300 BW Position Previous HSI
- 11. Results Age 24.7 ± 4.7 Height 176.5cm ± 6.7 Weight 71.8 ± 9.1
- 12. Odds Ratio p-value 95% CI Q Con 60 0.99 0.06 0.99 - 1.00 H Con 60 0.99 0.17 0.99 - 1.00 Q Con 300 0.99 0.97 0.99 - 1.00 H Con 300 0.99 0.20 0.99 - 1.00 H Ecc 60 0.99 0.12 0.99 - 1.00 Q Con 60 BW 0.71 0.03* 0.52 - 0.97 H Con 60 BW 0.75 0.29 0.43 -1.29 Q Con 300BW 1.10 0.87 0.56 - 1.89 H Con 300 BW 0.75 0.29 0.43 - 1.29 H Ecc 60 BW 0.73 0.04* 0.54 - 0.99 Q Con 60/ H Con 60 0.76 0.32 0.44 - 1.32 H Con 60/ H Ecc 60 1.08 0.90 0.34 - 3.40 Q Con 300/ H Con 300 1.46 0.26 0.76 - 2.79 Q Con 300/ H Ecc 60 1.46 0.35 0.66 - 3.25 Q Con 60 BW 0.71 0.03* 0.52 - 0.97 H Ecc 60 BW 0.73 0.04* 0.54 - 0.99 Results
- 13. Limitations Population Specific No player exposure
- 14. Discussion Hamstrings Eccentric Quadriceps Concentric are risk factors for HAMSTRING STRAIN INJURIES
- 15. Discussion Q Con 60 234 H Ecc 60 186 15% Q Con 60 227 H Ecc 60 186 41% Q Con 60 234 H Ecc 60 179 36% P(x)= 1 1+𝑒 _ 𝑧Probability of developing HSI Q Con 60 227 H Ecc 60 179 51%
- 16. Take Home Message www.uwrf.edu Quadriceps Concentric Strength Can Strength be identified as a risk factor for HSI? Hamstrings Eccentric
- 17. Thank you
Editor's Notes
- Thank you to the organizers and scientific committee for the opportunity… Fot those interested in this presentation, I will put these slides up on slideshare and post a link on twitter.
- Retrospective – effect not cause, Prospective contradictory results – small sample size, low number of injuries. Can strength be id as a RF for HSIAnd, which of the strength variables/characteristics, and when I say characteristics, I refer to isokinetic testing identifying type and speed
- Retrospective – effect not cause, Prospective contradictory results – small sample size, low number of injuries. Can strength be id as a RF for HSIAnd, which of the strength variables/characteristics, and when I say characteristics, I refer to isokinetic testing identifying type and speed
- Now, one of the interesting factors we had to consider was the multiple baseline tests we had collected. So we needed to find a model that would allow for these multiple measures. We there performed a Clustered logistic regression analysis with repeated measures robust analysis with population average approach
- So each of the variables were included in the regression model, which took into account the confounding variables that was identified in the analysis. Mention Limitations – could not control for exposure
- So each of the variables were included in the regression model, which took into account the confounding variables that was identified in the analysis. Mention Limitations – could not control for exposure