National Urban League

The Team Physician Consensus Statement delineates qualifications, duties, and responsibilities of the team physician and provides guidelines to individuals and organizations in selecting team physicians. These delineations and guidelines provide a foundation for best practices in the medical care of athletes and teams. The team physician's education, training, and experience uniquely qualify them to provide the best medical care for the athlete. This document is not intended as a standard of care and should not be interpreted as such. It is only a guide and, as such, is of a general nature, consistent with the reasonable, objective practice of the healthcare profession. Adequate insurance should be in place to help protect the physician, the athlete, and the sponsoring organization. This document was originally developed as the first in the team physician consensus series, representing an ongoing project-based alliance of the major professional associations concerned about clinical sports medicine issues. The organizations are as follows: American Academy of Family Physicians, American Academy of Orthopedic Surgeons, American College of Sports Medicine, American Medical Society for Sports Medicine, American Orthopedic Society for Sports Medicine, and the American Osteopathic Academy of Sports Medicine.

The Team Physician Consensus Statement delineates qualifications, duties, and responsibilities of the team physician and provides guidelines to individuals and organizations in selecting team physicians. These delineations and guidelines provide a foundation for best practices in the medical care of athletes and teams. The team physician's education, training, and experience uniquely qualify them to provide the best medical care for the athlete.This document is not intended as a standard of care and should not be interpreted as such. It is only a guide and, as such, is of a general nature, consistent with the reasonable, objective practice of the healthcare profession. Adequate insurance should be in place to help protect the physician, the athlete, and the sponsoring organization. This document was originally developed as the first in the team physician consensus series, representing an ongoing project-based alliance of the major professional associations concerned about clinical sports medicine issues. The organizations are as follows: American Academy of Family Physicians, American Academy of Orthopedic Surgeons, American College of Sports Medicine, American Medical Society for Sports Medicine, American Orthopedic Society for Sports Medicine, and the American Osteopathic Academy of Sports Medicine.

Sudden cardiac death is the leading medical cause of death among football players. Determining the optimal cardiac screening, the use of carefully selected medical assessments to detect underlying cardiovascular conditions associated with sudden cardiac arrest/death, is a desired objective of the Fédération Internationale de Football Association (FIFA) for football players of all ages. To date, cardiac screening recommendations in football have primarily focused on adult competitive players. Acknowledging its responsibility for player health worldwide, FIFA convened an international working group of cardiology and sports medicine experts to develop cardiac screening recommendations for youth football players. This group performed structured literature reviews and ultimately congregated in January of 2024, when recommendations were presented, scrutinised and judged using a systematic process. The final FIFA recommendations for youth cardiac screening include personal medical history, family medical history, focused physical examination and resting 12-lead electrocardiography. This document provides detailed rationale and clinical recommendations for youth cardiac screening and emphasises the importance of emergency action planning.

ABSTRACT There is a lack of epidemiological research on knee injuries and Anterior Cruciate Ligament (ACL) tears among National Collegiate Athletic Association (NCAA) soccer athletes. To describe the epidemiology of knee injuries and ACL tears in NCAA soccer. We analyzed data captured within the NCAA Injury Surveillance Program during 2009/10–2018/19. We examined injury frequencies and rates by event type, division, and sex, and knee injury distributions by injury diagnosis, mechanism, history, playing position, and activity at the time of injury. We used injury rate ratios (IRRs) to assess differences in injury rates and injury proportion ratios (IPRs) to assess the differential distribution of injuries across explanatory variables of interest. Random effects Poisson regressions were used to identify factors associated with recovery. Knee injury and ACL tear rates generally centered around comparable values across the study period. Overall knee injury (IRR = 1.38; 95%CI=[1.24, 1.53]) and ACL tear (IRR = 3.10; 95%CI=[2.20, 4.35]) rates were higher in women’s soccer, as compared with men’s soccer. Competition-related knee injury rates were higher than practice rates in both groups. Knee injuries in men’s (36.7%) and women’s (38.7%) soccer were most often classified as sprains, and most commonly attributed to blocking/defending activities (Men’s soccer: 15.4%; Women’s soccer: 15.5%). Findings indicate a higher rate of knee injuries and ACL tears in competitions than in practices. Coupled with the results observed in women’s soccer, these findings suggest that the risk of knee injuries and ACL tears in competitions and in women’s soccer merit attention.

Service academy members are at high risk for concussions as a result of participation in both sports and military-specific training activities. Approximately 17% of active duty service members are female, and they face unique challenges in achieving timely recovery from concussions. Understanding the unique characteristics affecting return to unrestricted activity (RTA) among female service academy members is imperative for the ever-growing proportion of females across the U.S. military. The goal of this analysis was to determine how specific injury and individual characteristics of concussion affect 2 RTA protocol events in female service academy members: time to protocol initiation and time to protocol completion. All data were collected as part of the National Collegiate Athletic Association (NCAA) and the DoD Concussion Assessment, Research and Education Consortium. We examined data from female U.S. military service academy members at the 4 U.S. Service Academy sites who sustained a concussion between Fall 2014 and Spring 2020 (N = 752). Return to unrestricted activity protocol initiation time was defined as the time from injury to when cadets were cleared to begin gradual RTA, while RTA protocol completion time was defined as the time from injury to when cadets were cleared to RTA. Multivariable Cox regression analyses were used to determine the effect of 4 characteristics on RTA event times: (1) service academy members' NCAA status (e.g., student athlete), (2) prior history of concussion, (3) reporting time of concussion, and (4) sport-related concussion (SRC) or non-SRC. Because of missing data, 520 cadets were included in the model of RTA protocol initiation and 556 were included in the model of RTA protocol completion. Chi-squared analyses assessed interactions between reporting time, NCAA status, and SRC or non-SRC. Service academy members who were NCAA athletes (hazard ratio [95% CI](HR [95% CI]): 1.58 [1.32, 1.90]), immediately reported their injury (HR [95% CI]: 1.40 [1.18, 1.67]), or had an SRC (HR [95% CI]: 1.29 [1.08, 1.54]) were significantly more likely to have initiated or completed the RTA protocol on any given day post-concussion compared to those who were not NCAA athletes, delayed reporting their injury, or had a non-SRC, respectively. We observed that among those with SRCs, a greater proportion of NCAA service academy members immediately reported their injury (53.9%) compared to non-NCAA (37.3%, P < .001); there was no difference in the proportion of NCAA and non-NCAA service academy members with non-SRCs who immediately reported their injury (P = .18). A greater proportion of female service academy members who sustained SRCs and were NCAA athletes reported their injuries immediately, which was associated with a greater likelihood of RTA protocol initiation and completion on any given day after injury. This may be attributable to easy and timely access to medical personnel (e.g., athletic trainers) or the presence of individuals trained in identifying concussion (e.g., coaches). Future initiatives among female service academy members should include improved access to medical care across a variety of injury settings and education on the importance of early reporting after concussion.

The identification of concussion risk factors, such as visible signs and mechanisms of injury, improves concussion identification. Exploring individual risk factors, such as concussion history, may help to improve existing concussion risk models and algorithms. The primary aim of the current study was to use machine learning techniques to develop a comprehensive, prospectively coded concussion risk model in professional hockey among players exhibiting visible signs. The secondary aim was to examine whether including concussion history improves model performance. Data from the National Hockey League (NHL) spotter program, including coded visible signs and mechanisms of injury associated with possible concussive events, were extracted from the 2018-2019 to the 2021-2022 seasons. Each unique spotter event was matched with data extracted from the medical record to determine whether the event was associated with a subsequent physician diagnosed concussion. We compared the ability of three machine learning-based approaches to identify the likelihood of physician diagnosed concussion: conditional inference tree, conditional inference random forest, and logistic regression. A total of 1563 unique events with visible signs were identified by spotters (183 leading to a concussion diagnosis). A randomly selected training sample had 1250 events (146 concussions) and the remaining set-aside test sample had 313 events (37 concussions). The obtained models performed at a high level with large effects in the training [area under the receiver operating characteristic curve (AUC) = 0.79] and set-aside test data (AUC = 0.82). Concussion history was retained in the tree and logistic regression models, with each additional prior concussion associated with a 1.32 times increased odds of concussion diagnosis. We present simple tree and logistic algorithms for concussion screening and as diagnostic aids. Our results show that player concussion history can explain additional risk above and beyond that explained by visible signs and mechanisms of injury alone.