Download PDF
Int J Sports Med 2023; 44(01): 3-8
DOI: 10.1055/a-1847-7108
Review

Preseason Prognostic Factors for Injuries and Match Loss in Collision Sports: A Systematic Review

Kento Watanabe
1   Graduate school of Rehabilitation Science, Saitama Prefectural University, Koshigaya, Japan
,
Tomoya Kitamura
2   Department of Physical Therapy, Saitama Prefectural University, Koshigaya, Japan
,
Hiroshi Takasaki
2   Department of Physical Therapy, Saitama Prefectural University, Koshigaya, Japan
› Author Affiliations
› Further Information
Also available at
    Permissions and Reprints

Abstract

This study aimed to identify which preseason factors had strong evidence of risks for physical injury during the season of collision sports including rugby, American football, and Australian rules football using qualitative synthesis. Pubmed, EMBASE, MEDLINE, SPORTDiscus, Scopus, and the Cochrane Library were reviewed. Eligibility criteria for selecting studies were: studies involving the collision sports; prospective cohort studies; and studies with outcomes of relative risks, odds ratios, and correlations between players’ preseason conditions and injury during the season. The risk of bias based on the Scottish Intercollegiate Guidelines Network quality checklists for cohort studies was assessed in 57 studies. The current study identified strong evidence that 1) anthropometric characteristics (body mass index and estimated mass moment of inertia of the body around a horizontal axis through the ankle), which are calculated with weight and height; 2) physical function, in particular for the trunk and lower limb (trunk-flexion hold and wall-sit hold); and 3) Oswestry Disability Index disability, which is a patient-reported outcome measure for disability due to low back pain, were positive prognostic factors for injury during the collision sports season, regardless of playing experience.

Key words

athletic injuries - cohort studies - preventive medicine - risk factor - preseason - rugby


Publication History

Received: 09 August 2021

Accepted: 21 April 2022

Article published online:
05 September 2022

© 2022. Thieme. All rights reserved.

Georg Thieme Verlag
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Ivarsson A, Johnson U, Andersen MB. et al. Psychosocial factors and sport injuries: meta-analyses for prediction and prevention. Sports Med 2017; 47: 353-365
    CrossrefPubMedGoogle Scholar
  • 2 Wiese-Bjornstal DM. Psychology and socioculture affect injury risk, response, and recovery in high-intensity athletes: a consensus statement. Scand J Med Sci Sports 2010; 20: 103-111
    CrossrefPubMedGoogle Scholar
  • 3 Johnson U, Tranaeus U, Ivarsson A. Current status and future challenges in psychological research of sport injury prediction and prevention: a methodological perspective. Revista De Psicologia Del Deporte 2014; 23: 401-409
    PubMedGoogle Scholar
  • 4 Johnson U, Ivarsson A. Psychosocial factors and sport injuries: prediction, prevention and future research directions. Curr Opin Psychol 2017; 16: 89-92
    CrossrefPubMedGoogle Scholar
  • 5 Brooks JH, Fuller CW, Kemp SP. et al. Epidemiology of injuries in English professional rugby union: Part 1 match injuries. Br J Sports Med 2005; 39: 757-766
    CrossrefPubMedGoogle Scholar
  • 6 Williams S, Trewartha G, Kemp SP. et al. Time loss injuries compromise team success in Elite Rugby Union: a 7-year prospective study. Br J Sports Med 2016; 50: 651-656
    CrossrefPubMedGoogle Scholar
  • 7 West SW, Williams S, Kemp SP. et al. Training load, injury burden, and team success in professional rugby union: risk versus reward. J Athl Train 2020; 55: 960-966
    CrossrefPubMedGoogle Scholar
  • 8 Bagordo A, Ciletti K, Kemp-Smith K. et al. Isokinetic dynamometry as a tool to predict shoulder injury in an overhead athlete population: a systematic review. Sports (Basel) 2020; 8: 124
    CrossrefPubMedGoogle Scholar
  • 9 Pozzi F, Plummer HA, Shanley E. et al. Preseason shoulder range of motion screening and in-season risk of shoulder and elbow injuries in overhead athletes: systematic review and meta-analysis. Br J Sports Med 2020; 54: 1019-1027
    CrossrefPubMedGoogle Scholar
  • 10 Green B, Bourne MN, Pizzari T. Isokinetic strength assessment offers limited predictive validity for detecting risk of future hamstring strain in sport: a systematic review and meta-analysis. Br J Sports Med 2018; 52: 329-336
    CrossrefPubMedGoogle Scholar
  • 11 Scottish Intercollegiate Guidelines Network (SIGN). Methodology checklist 3: cohort studies. Edinburgh: SIGN; 2012 [updated November/20/2012]. Version 3. Available from: https://www.sign.ac.uk/what-we-do/methodology/checklists/ Accessed: May 12, 2021
    PubMed
  • 12 Zeng X, Zhang Y, Kwong JS. et al. The methodological quality assessment tools for preclinical and clinical studies, systematic review and meta-analysis, and clinical practice guideline: a systematic review. J Evid Based Med 2015; 8: 2-10
    CrossrefPubMedGoogle Scholar
  • 13 Altman DG. Practical Statistics for Medical Research. London, UK: Chapman & Hall; 1991
    Google Scholar
  • 14 Andresen EM. Criteria for Assessing the Tools of Disability Outcomes Research. Arch Phys Med Rehabil 2000; 81: S15-S20
    CrossrefPubMedGoogle Scholar
  • 15 Zaal IJ, Devlin JW, Peelen LM. et al. A systematic review of risk factors for delirium in the ICU. Crit Care Med 2015; 43: 40-47
    CrossrefPubMedGoogle Scholar
  • 16 Johnston W, O’Reilly M, Duignan C. et al. Association of dynamic balance with sports-related concussion: a prospective cohort study. Am J Sports Med 2019; 47: 197-205
    CrossrefPubMedGoogle Scholar
  • 17 Gabbe B, Bennell K, Finch C. et al. Predictors of hamstring injury at the elite level of Australian football. Scand J Med Sci Sports 2006; 16: 7-13
    CrossrefPubMedGoogle Scholar
  • 18 Summers K, Snodgrass S, Callister R. Predictors of calf cramping in rugby league. J Strength Cond Res 2014; 28: 774-783
    CrossrefPubMedGoogle Scholar
  • 19 Thompson NJ, Morris RD. Predicting injury risk in adolescent football players: the importance of psychological variables. J Pediatr Psychol 1994; 19: 415-429
    CrossrefPubMedGoogle Scholar
  • 20 Gabbe BJ, Finch CF, Bennell KL. et al. Risk factors for hamstring injuries in community level Australian football. Br J Sports Med 2005; 39: 106-110
    CrossrefPubMedGoogle Scholar
  • 21 Freckleton G, Cook J, Pizzari T. The predictive validity of a single leg bridge test for hamstring injuries in Australian rules football players. Br J Sports Med 2014; 48: 713-717
    CrossrefPubMedGoogle Scholar
  • 22 Gabbett TJ, Domrow N. Risk factors for injury in subelite rugby league players. Am J Sports Med 2005; 33: 428-434
    CrossrefPubMedGoogle Scholar
  • 23 Summers KM, Snodgrass SJ, Callister R. et al. An initial prospective exploratory investigation to identify predictors of calf cramping in rugby league players. J Sci Med Sport 2011; 14: e113
    CrossrefPubMedGoogle Scholar
  • 24 Gabbe BJ, Finch CF, Wajswelner H. et al. Predictors of lower extremity injuries at the community level of Australian Football. Clin J Sport Med 2004; 14: 56-63
    CrossrefPubMedGoogle Scholar
  • 25 Gastin PB, Meyer D, Huntsman E. et al. Increase in injury risk with low body mass and aerobic-running fitness in elite Australian football. Int J Sports Physiol Perform 2015; 10: 458-463
    CrossrefPubMedGoogle Scholar
  • 26 Bourne MN, Opar DA, Williams MD. et al. Eccentric knee flexor strength and risk of hamstring injuries in rugby union: a prospective study. Am J Sports Med 2015; 43: 2663-2670
    CrossrefPubMedGoogle Scholar
  • 27 Langdon E, Snodgrass S, Young J. et al. Posture of rugby league players and its relationship to non-contact lower limb injury: a prospective cohort study. Phys Ther Sport 2019; 40: 27-32
    CrossrefPubMedGoogle Scholar
  • 28 Quarrie KL, Alsop JC, Waller AE. et al. The New Zealand rugby injury and performance project. VI. A prospective cohort study of risk factors for injury in rugby union football. Br J Sports Med 2001; 35: 157-166
    CrossrefPubMedGoogle Scholar
  • 29 Burke TM, Lisman PJ, Maguire K. et al. Examination of sleep and injury among college football athletes. J Strength Cond Res 2020; 34: 609-616
    CrossrefPubMedGoogle Scholar
  • 30 Hagel B. Hamstring injuries in Australian football. Clin J Sport Med 2005; 15: 400
    CrossrefPubMedGoogle Scholar
  • 31 Hides J, Franettovich Smith MM, Mendis MD. et al. Self-reported concussion history and sensorimotor tests predict head/neck injuries. Med Sci Sports Exerc 2017; 49: 2385-2393
    CrossrefPubMedGoogle Scholar
  • 32 Chalmers S, Magarey ME, Esterman A. et al. The relationship between pre-season fitness testing and injury in elite junior Australian football players. J Sci Med Sport 2013; 16: 307-311
    CrossrefPubMedGoogle Scholar
  • 33 Gabbe B, Bennell K, Finch C. Why are older Australian football players at greater risk of hamstring injury? (Abstract). J Sci Med Sport 2006; 9: 14
    CrossrefPubMedGoogle Scholar
  • 34 Wilkerson GB, Colston MA. A refined prediction model for core and lower extremity sprains and strains among collegiate football players. J Athl Train 2015; 50: 643-650
    PubMedGoogle Scholar
  • 35 Wilkerson GB, Giles JL, Seibel DK. Prediction of core and lower extremity strains and sprains in collegiate football players: a preliminary study. J Athl Train 2012; 47: 264-272
    PubMedGoogle Scholar
  • 36 McDonald AA, Wilkerson GB, McDermott BP. et al. Risk factors for initial and subsequent core or lower extremity sprain or strain among collegiate football players. J Athl Train 2019; 54: 489-496
    CrossrefPubMedGoogle Scholar
  • 37 Maddison R, Prapavessis H. A psychological approach to the prediction and prevention of athletic injury. J Sport Exerc Psychol 2005; 27: 289-310
    CrossrefPubMedGoogle Scholar
  • 38 Hides JA, Smith MMF, Mendis MD et al. Self-reported concussion history and sensorimotor tests predict head/neck injuries. Med Sci Sports Exerc 2017; 49: 2385–2393
    PubMed
  • 39 Gómez JE, Ross SK, Calmbach WL. et al. Body fatness and increased injury rates in high school football linemen. Clin J Sport Med 1998; 8: 115-120
    CrossrefPubMedGoogle Scholar
  • 40 Almăjan-Guţă B, Rusu AM, Nagel A. et al. Injury frequency and body composition of elite Romanian rugby players. Timisoara Physical Education and Rehabilitation Journal 2015; 8: 17-21
    CrossrefPubMedGoogle Scholar
  • 41 Schwab LM, McGhee D, Franettovich Smith MM. et al. Pre-season screening of the upper body and trunk in Australian football players: a prospective study. Phys Ther Sport 2020; 46: 120-130
    CrossrefPubMedGoogle Scholar
  • 42 Roy A, Rivaz H, Rizk A. et al. Seasonal changes in lumbar multifidus muscle in university rugby players. Med Sci Sports Exerc 2021; 53: 749-755
    CrossrefPubMedGoogle Scholar
  • 43 Hides J, Stanton WR, Mendis MD. et al. Small multifidus muscle size predicts football injuries. Orthop J Sports Med 2014; 2 2325967114537588
    PubMedGoogle Scholar
  • 44 Ras J, Puckree T. Injury profiles in junior rugby academy players. African Journal for Physical Activity and Health Sciences 2014; 20: 626-635
    PubMedGoogle Scholar
  • 45 Sman AD, Hiller CE, Rae K. et al. Predictive factors for ankle syndesmosis injury in football players: a prospective study. J Sci Med Sport 2014; 17: 586-590
    CrossrefPubMedGoogle Scholar
  • 46 Booth M, Cobley S, Orr R. Does a higher training age attenuate injury risk in junior elite rugby league players?. J Sci Med Sport 2019; 22: S28-S29
    CrossrefPubMedGoogle Scholar
  • 47 Hides J, Mendis MD, Franettovich Smith MM. et al. Association between altered motor control of trunk muscles and head and neck injuries in elite footballers – an exploratory study. Man Ther 2016; 24: 46-51
    CrossrefPubMedGoogle Scholar
  • 48 Hides J, Frazer C, Blanch P. et al. Clinical utility of measuring the size of the lumbar multifidus and quadratus lumborum muscles in the Australian football league setting: a prospective cohort study. Phys Ther Sport 2020; 46: 186-193
    CrossrefPubMedGoogle Scholar
  • 49 Hides J, Frazer C, Trojman A. et al. What is the clinical utility of measuring lumbar multifidus muscle size in a professional AFL setting? A prospective clinical study. J Sci Med Sport 2019; 22: S28
    CrossrefPubMedGoogle Scholar
  • 50 Luedke LE, Geisthardt TW, Rauh MJ. Y-balance test performance does not determine non-contact lower quadrant injury in collegiate American football players. Sports (Basel) 2020; 8: 27
    CrossrefPubMedGoogle Scholar
  • 51 Smith NA, Franettovich Smith MM, Bourne MN. et al. A prospective study of risk factors for hamstring injury in Australian football league players. J Sports Sci 2021; 39: 1395-1401
    PubMedGoogle Scholar
  • 52 Wilkerson GB, Gupta A, Colston MA. Mitigating sports injury risks using Internet of things and analytics approaches. Risk Anal 2018; 38: 1348-1360
    CrossrefPubMedGoogle Scholar
  • 53 Hulin BT, Gabbett TJ, Pickworth NJ. et al. Relationships among player load, high-intensity intermittent running ability, and injury risk in professional rugby league players. Int J Sports Physiol Perform 2019; 15: 423-429
    CrossrefPubMedGoogle Scholar
  • 54 Wilkerson GB. Neurocognitive reaction time predicts lower extremity sprains and strains. Int J Athl Ther Train 2012; 17: 4-9
    CrossrefPubMedGoogle Scholar
  • 55 Pontillo M, Spinelli BA, Sennett BJ. Prediction of in-season shoulder injury from preseason testing in division I collegiate football players. Sports Health 2014; 6: 497-503
    CrossrefPubMedGoogle Scholar
  • 56 Oddy C, Johnson MI, Jones G. The effect of generalised joint hypermobility on rate, risk and frequency of injury in male university-level rugby league players: A prospective cohort study. BMJ Open Sport Exerc Med 2017; 2: e000177
    CrossrefPubMedGoogle Scholar
  • 57 Attwood MJ, Roberts SP, Trewartha G. et al. Association of the Functional Movement Screen with match-injury burden in men’s community rugby union. J Sports Sci 2019; 37: 1365-1374
    CrossrefPubMedGoogle Scholar
  • 58 Wiese BW, Boone JK, Mattacola CG. et al. Determination of the Functional Movement Screen to predict musculoskeletal injury in intercollegiate athletics. Athl Train Sports Health Care 2014; 6: 161-169
    CrossrefPubMedGoogle Scholar
  • 59 Duke SR, Martin SE, Gaul CA. Preseason Functional Movement Screen predicts risk of time-loss injury in experienced male rugby union athletes. J Strength Cond Res 2017; 31: 2740-2747
    CrossrefPubMedGoogle Scholar
  • 60 Kiesel K, Plisky PJ, Voight ML. Can serious injury in professional football be predicted by a preseason Functional Movement Screen?. N Am J Sports Phys Ther 2007; 2: 147-158
    PubMedGoogle Scholar
  • 61 Armstrong R, Greig M. Injury identification: the efficacy of the Functional Movement Screen in female and male rugby union players. Int J Sports Phys Ther 2018; 13: 605-617
    CrossrefPubMedGoogle Scholar
  • 62 Armstrong R. Functional Movement Screening as a predictor of injury in male and female university rugby union players. Physiotherapy 2016; 102: e178-e179
    CrossrefPubMedGoogle Scholar
  • 63 Hajek M, Williams MD, Bourne MN. et al. Predicting noncontact lower limb injury using lumbar morphology in professional Australian football and rugby league players. Med Sci Sports Exerc 2022; 54: 814-850
    CrossrefPubMedGoogle Scholar
  • 64 Hrysomallis C, McLaughlin P, Goodman C. Balance and injury in elite Australian footballers. Int J Sports Med 2007; 28: 844-847
    Article in Thieme ConnectPubMedGoogle Scholar
  • 65 MacMillan C, Olivier B, Benjamin-Damons N. Sport Science Lab screening Protocol: the association between physical fitness parameters and injury among elite rugby players. Phys Ther Sport 2021; 52: 272-279
    CrossrefPubMedGoogle Scholar
  • 66 Opar DA, Ruddy JD, Williams MD. et al. Screening hamstring injury risk factors multiple times in a season does not improve the identification of future injury risk. Med Sci Sports Exerc 2022; 54: 321-329
    CrossrefPubMedGoogle Scholar
  • 67 Smith NA, Cameron M, Treleaven J. et al. Lower limb joint position sense and prospective hamstring injury. Musculoskelet Sci Pract 2021; 53: 102371
    CrossrefPubMedGoogle Scholar
  • 68 Smith NA, Smith MMF, Bourne MN. et al. A prospective study of risk factors for hamstring injury in Australian football league players. J Sports Sci 2021; 39: 1395-1401
    CrossrefPubMedGoogle Scholar
  • 69 Tee JC, Klingbiel JF, Collins R. et al. Preseason Functional Movement Screen component tests predict severe contact injuries in professional rugby union players. J Strength Cond Res 2016; 30: 3194-3203
    CrossrefPubMedGoogle Scholar
  • 70 Wilkerson GB, Bruce JR, Wilson AW. et al. Perceptual-motor efficiency and concussion history are prospectively associated with injury occurrences among high school and collegiate american football players. Orthop J Sports Med 2021; 9 23259671211051722
    PubMedGoogle Scholar
  • 71 Hughes R, Cross M, Stokes K. et al. Novel biomechanical injury risk score demonstrates correlation with lower limb posterior chain injury in 50 elite-level rugby union athletes. BMJ Open Sport Exerc Med 2021; 7: e001062
    CrossrefPubMedGoogle Scholar
  • 72 Ogaki R, Takemura M, Iwai K. et al. Risk factors for shoulder injuries with or without past history in collegiate rugby players. J Phys Fit Sports Med 2014; 63: 189-196
    CrossrefPubMedGoogle Scholar
  • 73 Wilkerson GB, Colston MA. A refined prediction model for core and lower extremity sprains and strains among collegiate football players. J Athl Train 2015; 50: 643-650
    CrossrefPubMedGoogle Scholar
  • 74 Wilkerson GB, Giles JL, Seibel DK. Prediction of core and lower extremity strains and sprains in collegiate football players: a preliminary study. J Athl Train 2012; 47: 264-272
    CrossrefPubMedGoogle Scholar
  • 75 Tonosu J, Takeshita K, Hara N. et al. The normative score and the cut-off value of the Oswestry Disability Index (ODI). Eur Spine J 2012; 21: 1596-1602
    CrossrefPubMedGoogle Scholar
  • 76 Jeong J, Choi DH, Shin CS. Core strength training can alter neuromuscular and biomechanical risk factors for anterior cruciate ligament injury. Am J Sports Med 2021; 49: 183-192
    CrossrefPubMedGoogle Scholar
  • 77 Sasaki S, Tsuda E, Yamamoto Y. et al. Core-muscle training and neuromuscular control of the lower limb and trunk. J Athl Train 2019; 54: 959-969
    CrossrefPubMedGoogle Scholar
  • 78 Pérez-Gómez J, Adsuar JC, Alcaraz PE. et al. Physical exercises for preventing injuries among adult male football players: a systematic review. J Sport Health Sci 2022; 11: 115-122
    CrossrefPubMedGoogle Scholar
  • 79 Loose O, Achenbach L, Fellner B. et al. Injury prevention and return to play strategies in elite football: no consent between players and team coaches. Arch Orthop Trauma Surg 2018; 138: 985-992
    CrossrefPubMedGoogle Scholar