The study authors created a modification of the Physiotherapy Evidence Database (PEDro) scale,21,22 a quality assessment tool based on the Delphi list of criteria for quality assessment of randomized clinical trials for conducting systematic reviews (Table 3).23 Original items 2 and 3 pertained to subject allocation, which is not relevant to studies of prospective injury risk factors. Our modified item 2 pertained to prospective collection of all baseline study data, and our modified item 3 pertained to performing a power analysis to ensure an adequate sample size, which is inconsistently reported in sports medicine studies. The language of original item 4 was changed to modified item 5 to reflect an expected difference in some baseline factors in injured versus noninjured study participants. Original items 5 and 6 were combined into modified item 6, as blinding of athletic trainers, athletes, and coaches would be necessary to prevent intentional modification of a perceived injury risk factor (eg, coaches encouraging athletes with low flexibility scores to stretch more often in an effort to reduce injury risk). Finally, original item 9 pertained to correct allocation to treatment or control groups, which was not relevant to prospective injury risk studies; our modified item 9 pertained to accounting for exposure time in matches or practice sessions, thereby allowing for report of injury risk per unit time in addition to absolute risk.
Reliability of Modified PEDro Scale
The final list of 9 studies was circulated among the study authors for blinded quality assessment. Specifically, each blinded reviewer (JRB and AMWC) independently evaluated the 9 studies with the modified PEDro scale and submitted scoring data directly to a designated unblinded study author (JAO). The blinded authors were instructed not to discuss the studies or their scoring results until all blinded reviewers had submitted scores. After the blinded review, the 2 senior authors (TMB and JAO) performed an unblinded review of the 9 studies. Specifically, each discrepantly scored item among the blinded reviewers was reviewed and the unblinded authors assigned a final “gold standard” score after critically appraising the body of the study article. The blinded scores were nonnormally distributed (P = 0.003 Shapiro–Wilk W), and we therefore used nonparametric reliability tests. Inter-rater reliability of individual blinded reviewers was calculated as Spearman rho, and inter-rater reliability of individual items among blinded reviewers was assessed with Fleiss kappa.
Data Collection and Reporting
The primary purpose, length of time, sample size, age and sex of participants, level of competition, and included sports were reported for all included studies (Table 2). Because the purpose of this review is to assess risk factors for lower extremity injury that are identifiable by examination, we have limited our report of study measures and results to risk factors identifiable in a clinical examination setting with limited equipment (Table 2). Measures of estimated effect size and variability were reported as available. We did not perform any secondary statistical tests on the reported data, and the heterogeneity of reporting methods and experimental design among the included studies was such that we could not perform a meta-analysis or similar method of pooled data analysis. Finally, we documented additional specific strengths and weaknesses of the individual studies that were not directly assessed by the modified PEDro scale but are of potential relevance to interpreting the study findings.
After our screening process was completed, 9 prospective cohort studies including high school age athletes were identified (Table 2). One study was specific to soccer players,13 3 studies were specific to track and field or running,12,14,15 2 were specific to basketball,18,20 1 was specific to American football,19 and 2 included multiple sports.16,17 Three were limited to male athletes,13,15,19 1 was limited to female athletes,17 and 5 included both sexes. Sample size ranged from 4220 to 155817 athletes, and athletes were followed 2 to 4 sports seasons in 4 studies15–17,19 and a single season for the remaining 5 studies.12–14,18,20 The overall injury prevalence in the reported studies ranged from 1.2% for anterior cruciate ligament (ACL) tears among female high school athletes17 to 43% for ankle injuries among soccer players.20 The most common definition of injury included missed practice or game time (6 of 9 studies).13,15,16,18–20 Injury severity was reported based on time lost in 2 studies15,20 and by a clinical scoring system in 1 study.16 Five studies required clinical evaluation by an athletic trainer, physical therapist, or physician,12,14–16,20 1 study allowed injury report by the coach or athletic trainer,18 and 1 study required diagnostic imaging or arthroscopic visualization.17
Methodological Quality and Modified PEDro Score Reliability
The mean modified PEDro score for the included studies was 6.0 ± 1.5 (Table 3) for the gold standard review, which was not significantly different from the distribution of unblinded scores (median, 8; interquartile range, 6-8; P = 0.95 Wilcoxon rank sum). None of the studies fulfilled all criteria in the modified PEDro scale (modified PEDro score of 10). However, 2 of 9 studies attained a high score of 8 of 10,17,18 and 2 of 9 studies attained a low score of 4 of 10.12,20 Of the individual factors on the modified PEDro scale, item 3 had the lowest percentage of studies that met the specified criteria (1/9 or 11%),16 which was use of a power analysis to determine appropriate sample size. There was moderate correlation among blinded reviewers for both the total study score (Spearman rho = 0.63) and item-specific responses (Fleiss kappa = 0.46).
Identified Clinical Exam Injury Risk Factors
No prospective studies that met our inclusion criteria were identified that included evaluation of all or part of the functional examination recommended in the PPE fourth ed. (the duck walk or single-leg hop).2 Our review identified several clinical examination modalities that have at least preliminary evidence to suggest efficacy in stratifying future lower extremity injury risk. Identified risk factors fell into 7 basic categories: balance,18,20 anatomy,12,13 strength,14 physical maturation status,15 weight,16 and ligamentous laxity.17 Modalities such as the Star Excursion Balance Test (SEBT) and assessment of physical maturation are broadly associated with increased injury risk,15,18 whereas most assessments included in this review are specific to individual injuries.12–20 Our assessments of these risk factors are as follows:
Physical Maturation Status
Delayed physical maturation status is associated with increased acute lower extremity injury in school-aged athletes.24–26 Only 1 study examined the relationship between physical maturation status and overuse lower extremity injury but found that boys under the age of 14 were more likely to get injured.25 This study evaluated physical maturation by comparing participants' skeletal maturity assessed through radiographs with their chronological ages.25 An early maturer was defined as an individual with a skeletal age 1 year above their chronological age and a late maturer was defined as an individual with a skeletal age 1 year below their chronological age.25 However, determination of maturation status by comparing skeletal maturity and chronological age is problematic for general screening because of the required radiographs. Fourchet et al15 presents an interesting association between age of peak height velocity and overall injury risk in a study population that includes track and field athletes that participate in a variety of events. Age of peak height velocity as a surrogate measure of maturation status can be calculated based on serial height measurements and has the potential for incorporation into a clinical injury risk assessment. One requirement for this type of assessment is either continual yearly access to the same primary care provider or an electronic medical record system that is accessible to allow parents and children to track and maintain their yearly physical maturation information.
Based on our review, poor balance seems to be a likely risk factor for ankle sprain in high school-aged athletes in sports with a high incidence of ankle injuries, as 2 included studies had positive findings18,20 and 1 had negative findings.16 However, the methodology of each balance testing procedure varied significantly, and differences in study populations limit direct comparison of test results. McHugh et al16 examined frontal plane excursion (uniplanar balance) on a tilt board as measure of percent time out of balance, Wang et al20 used degree of postural sway (multidirectional balance) on a force plate, and Plisky et al18 used a clinical exam (SEBT) of reach distance in multiple planes before losing balance (multidirectional balance). The SEBT relies on minimal equipment and seems to be conducive to a clinical setting. Although Plisky et al reported increased overall lower extremity (LE) injury risk based on SEBT results, injury data regarding anatomic distribution (knee vs ankle vs hip) was not reported and limited the specificity of his results.
Four studies in this review examined anatomic injury risk factors, particularly leg length asymmetry and foot morphology. Leg length asymmetry is proposed to result in asymmetrical gait and postural changes with compensatory imbalances in muscle strength and flexibility,30,31 with some promise as a predictive tool for stress fractures in select populations such as track and field athletes.32 Limb length discrepancy is measured most accurately with radiographic methods,30 which may be inappropriate for general screening in a pediatric population. Finnoff et al14 reported negative findings regarding length discrepancy as a risk factor for patellofemoral pain syndrome (PFPS); however, this measure has not been previously associated with PFPS and seemed to be a secondary aspect of their overall study design. Both excessive foot pronation and supination have also been proposed to increase lower extremity injury risk33–35; correspondingly, a pronatory foot type as measured through navicular drop was associated with increased risk of medial tibial stress syndrome (MTSS) by Bennet et al12 and Cain et al13 reported that supination as measured by the Foot Posture Index was associated with ankle overuse injury. However, the small sample size, single sport design, narrow injury definition, and varied methods of determining foot type in these studies again limit the applicability of this screening modality to a general athletic population.
Based on our review, maximum isometric strength was not a risk factor for injury but strength ratios between agonistic and antagonistic muscle groups were predictive of injury. Specifically, Wang et al and McHugh et al found no association between ankle injury and leg strength.16,20 In a more generalized model, Turbeville et al19 used hand grip strength as a surrogate measure of overall strength and also found no association with injury of any type among football players. However, when examining strength imbalance, Finnoff et al14 noted a protective effect from a low external rotation (ER): internal rotation (IR) hip strength ratio and an increased risk of PFPS at higher ratios in runners. The narrow scope of this study, both in athlete population and injury of interest, limits the applicability of their findings, and future research of strength imbalance as an injury assessment tool in a multisports setting with a broader definition of injury may be warranted.
Myer et al17 was the only study to assess joint laxity in our review, which is a known risk factor for ACL injury.36,37 The authors conclude that screening of ligamentous laxity may effectively identify high school female athletes at increased risk of ACL injury who participate in soccer and basketball.17
Injury risk assessment in high school athletes has been a long-standing goal of sports medicine practitioners. One of the challenges of developing an assessment tool to determine relative injury risk is the large range of activities performed by athletes even within a given sport and the wide variation in physical maturity within this age group. Accordingly, multiple assessment strategies have been proposed with varying degrees of specificity to a given population, yielding equally varied results. After extensive review of the literature, we found no evidence to support or refute use of the PPE fourth ed. format for prospective musculoskeletal injury risk assessment in high school-aged athletes. There seems to be a moderate level of evidence supporting several physical examination findings, including ligamentous laxity,17 strength imbalance,14 excessive foot pronation or supination,12,13 physical maturation status,15 and multidirectional balance18,20 in high school-aged athletes as risk factors for future injury, although their utility is often limited to a narrow spectrum of sports or to prediction of specific injuries.
One of the stated goals of the PPE is to identify those at risk for injury. Although self-report of previous injuries38 or the presence of persistent functional deficits28,29,39 are risk factors for future injury, the results of this review demonstrate that there is no objective evidence that the recommended components of the MSK examination portion of the PPE provide relevant prospective risk assessment data in high school-aged athletes. In addition to the general MSK examination, a functional assessment of 2 movements, the duck walk and single-leg hop, is recommended.2 Based on our systematic search of the literature, there are no reported prospective injury risk assessment studies in high school-aged athletes that include evaluation of these movements. However, evidence-based assessments were identified that could replace these qualitative assessments in a clinical setting. In particular, both the SEBT and age of peak height velocity as a measure of physical maturation status are both easily reproducible and associated with overall lower extremity injury risk.15,18 These types of assessments can easily be performed in a primary care provider's standard office setting and requires minimal training for reliable data collection. One limitation is nonstandard reporting of data (no odds ratio or correlation coefficients reported) and an overly broad definition of injury severely limits the interpretability of peak height velocity for lower extremity injury risk assessment. Future studies that clearly report relative risk and injury data are needed to determine the reliability of age of peak height velocity as an injury risk factor. However, this information does highlight the use of serial type measurements and the importance of primary care provider yearly access to help make better informed decisions using longitudinal tracking on an individual basis. Future studies are indicated to develop a more comprehensive evidence-based examination, but it is clear that sufficient evidence exists to at least moderately improve on the currently recommended assessment process.
Quantitative analysis of knee hyperextension as a surrogate for joint laxity may provide some insight into lower extremity injury risk (ie, ACL injury), which can be readily accomplished in a clinical examination setting, it is likely inappropriate for general screening because of the low overall incidence of ACL injury, but it may be more appropriate as a future component of the PPE for female athletes in high ACL injury risk sports (eg, soccer and basketball). Sport specific PPE testing may not be time efficient, but discussions between primary care providers and their patients will help them discern which specialized tests may be warranted based on an individual's values and physical activity goals. One generalized risk assessment tool that has had promising results in 2 recent prospective studies of collegiate and professional level athletes is the Functional Movement Screen (FMS).40,41 This screening tool was developed under the premise that functional testing of movements that simultaneously integrate aspects of neuromuscular coordination, balance, strength, and flexibility can effectively determine injury risk because of the likely multifactorial etiology of acute sports injuries.27,42–45 The FMS requires qualitative evaluation of the controlled execution of several movements of varying complexity (deep squat, shoulder mobility, hurdle step, lunge, straight leg raise, push-up, and rotary stability).44,46 With high inter-rater reliability (0.7-0.9)47,48 and minimal equipment needed to perform this screening tool, additional study of the FMS as a generalized lower extremity risk assessment tool in high school athletes is merited.
In an effort to facilitate improved design of future sports injury risk assessment studies and evaluation of methodological quality of previous injury risk studies, the authors have presented our initial experiences with the modified PEDro scale. Our results indicate that this scale provides a reasonable general assessment of study quality. However, it is not meant to substitute well-defined inclusion criteria for a systematic review. Several components of prospective study design were emphasized in our modified scale that are inconsistently present in this field of research, namely participant blinding, sample size estimation, and report of sports exposure hours. We believe that the importance of blinding study participants from the results of risk assessment tools is under-appreciated. Athletes, coaches, and clinicians alike are motivated to keep participants healthy, and blinding is necessary to minimize the likelihood of active attempts to modify the perceived risk factor (even if it is a spurious assumption) in an attempt to prevent injury. In addition, sports exposure is an essential component of injury risk, and it has been well-established that playing time during sporting events confers a higher risk of injury than training hours.49–53 Even if an injury risk assessment study had adequate sample size, it would be underpowered if the enrolled athletes did not have sufficient sports exposure to sustain the anticipated number of injuries.
Limitations of this review are related to the heterogeneity of the selected studies in addition to assumptions of overall study quality made by our modified PEDro score. Our modified scale and the original PEDro are designed to determine the quality of the study design as it is reported in the article, which does not take into account possible discordance in study report and actual study design.22 In addition, because our review centers on risk assessment in a relatively broad athlete population, the studies that met our inclusion criteria had respectively varied study populations, precluding direct comparison between risk assessment tools. The lack of clarity between risk factors for acute and chronic injuries created an additional limitation.
It is possible that some risk factors are different for acute and chronic injuries and because the research reviewed did not consistently distinguish between acute and chronic injuries the results of this review would not clearly identify risk factors that may be indicative of certain types of injury. Finally, because most of sport injury risk assessment studies that met our criteria focused on a given sport or a specific injury, there is a paucity of studies that broadly evaluate a given risk assessment tool for general screening in a setting such as the sports preparticipation evaluation (PPE). There were several common methodological limitations in the identified studies that undoubtedly introduced a bias toward negative findings. There was typically a lack of reported power analyses to determine adequate sample size, despite an abundance of epidemiologic reports from which to draw incidence and prevalence data for acute high school sports injuries when estimating sample size for study design.3–5,54–69 Only one of the studies in this review had a reported method of sample size estimation,16 and athlete exposure hours was only reported in 2/9 studies.15,17 Additionally, injuries were reported in a nonstandard manner ranging from self-report of symptoms to missed practice time to diagnosis by a sports medicine provider. Therefore, to improve efforts at identifying reliable sports injury risk assessment tools, it is imperative that future risk assessment studies demonstrate adequate sample size, report injury risk in a standard manner, record sport exposure time, and use a reliable working injury definition.
In conclusion, no prospective studies were identified in this review that support or refute use of the functional MK examination portion of the currently recommended sports preparticipation evaluation to assess injury risk in high school-aged athletes. There is some prospective evidence to support generalized use of the SEBT and assessment of physical maturation status by age of peak height velocity to prospectively determine lower extremity injury risk. Several injury-specific risk assessment tools, such as the FMS, hip muscle strength ratios, foot pronation measurements, ankle dorsiflexion range of motion, and dynamic functional hop tests may yield improved benefit for prospectively evaluating lower extremity injury risk for high school athletes entering specific sports or positions of increased lower extremity risk exposure.
1. AMA. Medical Evaluation of the Athlete: A Guide. Chicago, IL: American Medical Association; 1976.
2. Bernhardt DT, Roberts WO, eds. PPE Preparticipation Physical Evaluation. 4th ed. Elk Grove Village, IL: American Academy of Family Physicians, American Academy of Pediatrics, American College of Sports Medicine, American Medical Society for Sports Medicine, American Orthopaedic Society for Sports Medicine, and American Osteopathic Academy of Sport Medicine; 2010.
3. Rechel JA, Collins CL, Comstock RD. Epidemiology of injuries requiring surgery among high school athletes in the United States, 2005 to 2010. J Trauma. 2011;71:982–989.
4. Swenson DM, Yard EE, Fields SK, et al. Patterns of recurrent injuries among US high school athletes, 2005–2008. Am J Sports Med. 2009;37:1586–1593.
5. Fernandez WG, Yard EE, Comstock RD. Epidemiology of lower extremity injuries among U.S. high school athletes. Acad Emerg Med. 2007;14:641–645.
6. Scheidt PC, Harel Y, Trumble AC, et al. The epidemiology of nonfatal injuries among US children and youth. Am J Public Health. 1995;85:932–938.
7. Garrick JG. Preparticipation orthopedic screening evaluation. Clin J Sport Med. 2004;14:123–126.
8. Gomez JE, Landry GL, Bernhardt DT. Critical evaluation of the 2-minute orthopedic screening examination. Am J Dis Child. 1993;147:1109–1113.
9. Best TM. The preparticipation evaluation: an opportunity for change and consensus. Clin J Sport Med. 2004;14:107–108.
10. National Federation of State High School Associations. 2013–2014 High School Athletics Participation Survey. Indianapolis, IN. 2015.
11. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009;62:e1–e34.
12. Bennett JE, Reinking MF, Pluemer B, et al. Factors contributing to the development of medial tibial stress syndrome in high school runners. J Orthop Sports Phys Ther. 2001;31:504–510.
13. Cain L, Nicholson L, Adams R, et al. Foot morphology and foot/ankle injury in indoor football. J Sci Med Sport. 2007;10:311–319.
14. Finnoff JT, Hall MM, Kyle K, et al. Hip strength and knee pain in high school runners: a prospective study. PM R. 2011;3:792–801.
15. Fourchet F, Horobeanu C, Loepelt H, et al. Foot, ankle, and lower leg injuries in young male track and field athletes. Int J Athl Ther Train. 2010;16:19–23.
16. McHugh MP, Tyler TF, Tetro DT, et al. Risk factors for noncontact ankle sprains in high school athletes: the role of hip strength and balance ability. Am J Sports Med. 2006;34:464–470.
17. Myer GD, Ford KR, Paterno MV, et al. The effects of generalized joint laxity on risk of anterior cruciate ligament injury in young female athletes. Am J Sports Med. 2008;36:1073–1080.
18. Plisky PJ, Rauh MJ, Kaminski TW, et al. Star Excursion Balance Test as a predictor of lower extremity injury
in high school basketball players. J Orthop Sports Phys Ther. 2006;36:911–919.
19. Turbeville SD, Cowan LD, Owen WL, et al. Risk factors for injury in high school football players. Am J Sports Med. 2003;31:974–980.
20. Wang HK, Chen CH, Shiang TY, et al. Risk-factor analysis of high school basketball player ankle injuries: a prospective controlled cohort study evaluating postural sway, ankle strength, and flexibility. Arch Phys Med Rehabil. 2006;87:821–825.
21. Blobaum P. Physiotherapy evidence database (PEDro). J Med Libr Assoc. 2006;94:477.
22. Maher CG, Sherrington C, Herbert RD, et al. Reliability of the PEDro scale for rating quality of randomized controlled trials. Phys Ther. 2003;83:713–721.
23. Verhagen AP, de Vet HCW, de Bie RA, et al. The Delphi list: a criteria list for quality assessment of randomized clinical trials for conducting systematic reviews developed by Delphi consensus. J Clin Epidemiol. 1998;51:1235–1241.
24. Backous DD, Friedl KE, Smith NJ, et al. Soccer injuries and their relation to physical maturity. Am J Dis Child. 1988;142:839–848.
25. Johnson A, Doherty PJ, Freemont A. Investigation of growth, development, and factors associated with injury in elite schoolboy footballers: prospective study. BMJ. 2009;338:b490.
26. Le Gall F, Carling C, Reilly T. Biological maturity and injury in elite youth football. Scand J Med Sci Sports. 2007;17:564–572.
27. Baumhauer JF, Alosa DM, Renstrom AF, et al. A prospective study of ankle injury risk factors. Am J Sports Med. 1995;23:564–570.
28. McGuine TA, Greene JJ, Best T, et al. Balance as a predictor of ankle injuries in high school basketball players. Clin J Sport Med. 2000;10:239–244.
29. Tropp H, Ekstrand J, Gillquist J. Stabilometry in functional instability of the ankle and its value in predicting injury. Med Sci Sports Exerc. 1984;16:64–66.
30. McCaw ST, Bates BT. Biomechanical implications of mild leg length inequality. Br J Sports Med. 1991;25:10–13.
31. Neely FG. Biomechanical risk factors for exercise-related lower limb injuries. Sports Med. 1998;26:395–413.
32. Bennell KL, Malcolm SA, Thomas SA, et al. Risk factors for stress fractures in track and field athletes: a twelve-month prospective study. Am J Sports Med. 1996;24:810–818.
33. Kaufman KR, Brodine SK, Shaffer RA, et al. The effect of foot structure and range of motion on musculoskeletal overuse injuries. Am J Sports Med. 1999;27:585–593.
34. Murphy DF, Connolly DAJ, Beynnon BD. Risk factors for lower extremity injury
: a review of the literature. Br J Sports Med. 2003;37:13–29.
35. Razeghi M, Batt ME. Foot type classification: a critical review of current methods. Gait Posture. 2002;15:282–291.
36. Ramesh R, Von Arx O, Azzopardi T, et al. The risk of anterior cruciate ligament rupture with generalised joint laxity. J Bone Joint Surg Br. 2005;87:800–803.
37. Uhorchak JM, Scoville CR, Williams GN, et al. Risk factors associated with noncontact injury of the anterior cruciate ligament: a prospective four-year evaluation of 859 West Point cadets. Am J Sports Med. 2003;31:831–842.
38. Steffen K, Myklebust G, Andersen TE, et al. Self-reported injury history and lower limb function as risk factors for injuries in female youth soccer. Am J Sports Med. 2008;36:700–708.
39. Croisier JL, Ganteaume S, Binet J, et al. Strength imbalances and prevention of hamstring injury in professional soccer players. Am J Sports Med. 2008;36:1469–1475.
40. 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.
41. Chorba RS, Chorba DJ, Bouillon LE, et al. Use of a functional movement screening tool to determine injury risk in female collegiate athletes. N Am J Sports Phys Ther. 2010;5:47–54.
42. Bahr R, Krosshaug T. Understanding injury mechanisms: a key component of preventing injuries in sport. Br J Sports Med. 2005;39:324–329.
43. Meeuwisse WH. Assessing causation in sport injury: a multifactorial model. Clin J Sport Med. 1994;4:166.
44. Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function-part 1. N Am J Sports Phys Ther. 2006;1:62–72.
45. Meeuwisse WH, Tyreman H, Hagel B, et al. A dynamic model of etiology in sport injury: the recursive nature of risk and causation. Clin J Sport Med. 2007;17:215–219.
46. Foran B. High-Performance Sports Conditioning. Champaign, IL: Human Kinetics Publishers; 2001.
47. Gribble P, Brigle J, Pietrosimone B, et al. Intrarater reliability of the functional movement screen. J Strength Cond Res. 2013;27:978–981.
48. Teyhen DS, Shaffer SW, Lorenson CL, et al. Functional movement screen: a reliability study. J Orthop Sports Phys Ther. 2012;42:530–540.
49. Brito J, Malina RM, Seabra A, et al. Injuries in portuguese youth soccer players during training and match play. J Athl Train. 2012;47:191–197.
50. Ekstrand J, Gillquist J, Moller M, et al. Incidence of soccer injuries and their relation to training and team success. Am J Sports Med. 1983;11:63–67.
51. Gabbett TJ. Incidence of injury in semi-professional rugby league players. Br J Sports Med. 2003;37:36–44.
52. Hagglund M, Walden M, Ekstrand J. Previous injury as a risk factor for injury in elite football: a prospective study over two consecutive seasons. Br J Sports Med. 2006;40:767–772.
53. Peterson L, Junge A, Chomiak J, et al. Incidence of football injuries and complaints in different age groups and skill-level groups. Am J Sports Med. 2000;28:S51–S57.
54. Borowski LA, Yard EE, Fields SK, et al. The epidemiology of US high school basketball injuries, 2005–2007. Am J Sports Med. 2008;36:2328–2335.
55. Collins CL, Comstock RD. Epidemiological features of high school baseball injuries in the United States, 2005–2007. Pediatrics. 2008;121:1181–1187.
56. Comstock RD. Epidemiology of knee injuries in adolescents: a review. Clin J Sport Med. 2009;19:153–154.
57. Cuff S, Loud K, O'Riordan MA. Overuse injuries in high school athletes. Clin Pediatr. 2010;49:731–736.
58. Gaunt T, Maffulli N. Soothing suffering swimmers: a systematic review of the epidemiology, diagnosis, treatment and rehabilitation of musculoskeletal injuries in competitive swimmers. Br Med Bull. 2012;103:45–88.
59. Kerr ZY, Collins CL, Fields SK, et al. Epidemiology of player–player contact injuries among US high school athletes, 2005–2009. Clin Pediatr. 2011;50:594–603.
60. Kerr ZY, Collins CL, Pommering TL, et al. Dislocation/separation injuries among US high school athletes in 9 selected sports: 2005–2009. Clin J Sport Med. 2011;21:101–108.
61. Krajnik S, Fogarty KJ, Yard EE, et al. Shoulder injuries in US high school baseball and softball athletes, 2005–2008. Pediatrics. 2010;125:497–501.
62. Leininger RE, Knox CL, Comstock RD. Epidemiology of 1.6 million pediatric soccer-related injuries presenting to US emergency departments from 1990 to 2003. Am J Sports Med. 2007;35:288–293.
63. Marar M, McIlvain NM, Fields SK, et al. Epidemiology of concussions among United States high school athletes in 20 sports. Am J Sports Med. 2012;40:747–755.
64. Nation AD, Nelson NG, Yard EE, et al. Football-related injuries among 6- to 17-year-olds treated in US emergency departments, 1990–2007. Clin Pediatr. 2011;50:200–207.
65. Nelson AJ, Collins CL, Yard EE, et al. Ankle injuries among United States high school sports
athletes, 2005–2006. J Athl Train. 2007;42:381–387.
66. Swenson DM, Collins CL, Best TM, et al. Epidemiology of knee injuries among US high school athletes, 2005/06–2010/11. Med Sci Sports Exerc. 2013;45:462–469.
67. Swenson DM, Yard EE, Collins CL, et al. Epidemiology of US high school sports
-related fractures, 2005–2009. Clin J Sport Med. 2010;20:293–299.
68. Yard E, Comstock D. Injury patterns by body mass index in US high school athletes. J Phys Act Health. 2011;8:182–191.
69. Yard EE, Schroeder MJ, Fields SK, et al. The epidemiology of United States high school soccer injuries, 2005–2007. Am J Sports Med. 2008;36:1930–1937.
Keywords:Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.
preparticipation exam; lower extremity injury; high school sports; injury risk assessment