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Deciding when to return to sport after injury is complex and multifactorial—an exercise in risk management. Return to sport decisions are made every day by clinicians, athletes and coaches, ideally in a collaborative way. The purpose of this consensus statement was to present and synthesise current evidence to make recommendations for return to sport decision-making, clinical practice and future research directions related to returning athletes to sport. A half day meeting was held in Bern, Switzerland, after the First World Congress in Sports Physical Therapy. 17 expert clinicians participated. 4 main sections were initially agreed upon, then participants elected to join 1 of the 4 groups—each group focused on 1 section of the consensus statement. Participants in each group discussed and summarised the key issues for their section before the 17-member group met again for discussion to reach consensus on the content of the 4 sections. Return to sport is not a decision taken in isolation at the end of the recovery and rehabilitation process. Instead, return to sport should be viewed as a continuum, paralleled with recovery and rehabilitation. Biopsychosocial models may help the clinician make sense of individual factors that may influence the athlete's return to sport, and the Strategic Assessment of Risk and Risk Tolerance framework may help decision-makers synthesise information to make an optimal return to sport decision. Research evidence to support return to sport decisions in clinical practice is scarce. Future research should focus on a standardised approach to defining, measuring and reporting return to sport outcomes, and identifying valuable prognostic factors for returning to sport.

Training in the medical specialty of sport and exercise medicine (SEM) is available in many, but not all countries. In 2015, an independent Delphi group, the International Syllabus in Sport and Exercise Medicine Group (ISSEMG), was formed to create a basic syllabus for this medical specialty. The group provided the first part of this syllabus, by identifying 11 domains and a total of 80 general learning areas for the specialty, in December 2017. The next step in this process, and the aim of this paper was to determine the specific learning areas for each of the 80 general learning areas. A group of 26 physicians with a range of primary medical specialty qualifications including, Sport and Exercise Medicine, Family Medicine, Internal Medicine, Cardiology, Rheumatology and Anaesthetics were invited to participate in a multiple round online Delphi study to develop specific learning areas for each of the previously published general learning areas. All invitees have extensive clinical experience in the broader sports medicine field, and in one or more components of sports medicine governance at national and/or international level. SEM, Family Medicine, Internal Medicine, Cardiology, Rheumatology and Anaesthetics were invited to participate in a multiple round online Delphi study to develop specific learning areas for each of the previously published general learning areas. All invitees have extensive clinical experience in the broader sports medicine field, and in one or more components of sports medicine governance at national and/or international level. The hierarchical syllabus developed by the ISSEMG provides a useful resource in the planning, development and delivery of specialist training programmes in the medical specialty of SEM.

Hamstrings strains are common and debilitating injuries in many sports. Most hamstrings exercises are performed at an inadequately low hip-flexion angle because this angle surpasses 70° at the end of the sprinting leg's swing phase, when most injuries occur. To evaluate the influence of various hip-flexion angles on peak torques of knee flexors in isometric, concentric, and eccentric contractions and on the hamstrings-to-quadriceps ratio. Descriptive laboratory study. Research laboratory. Ten national-level sprinters (5 men, 5 women; age = 21.2 ± 3.6 years, height = 175 ± 6 cm, mass = 63.8 ± 9.9 kg). For each hip position (0°, 30°, 60°, and 90° of flexion), participants used the right leg to perform (1) 5 seconds of maximal isometric hamstrings contraction at 45° of knee flexion, (2) 5 maximal concentric knee flexion-extensions at 60° per second, (3) 5 maximal eccentric knee flexion-extensions at 60° per second, and (4) 5 maximal eccentric knee flexionextensions at 150° per second. Hamstrings and quadriceps peak torque, hamstrings-to-quadriceps ratio, lateral and medial hamstrings root mean square. We found no difference in quadriceps peak torque for any condition across all hip-flexion angles, whereas hamstrings peak torque was lower at 0° of hip flexion than at any other angle (P < .001) and greater at 90° of hip flexion than at 30° and 60° (P < .05), especially in eccentric conditions. As hip flexion increased, the hamstrings-to-quadriceps ratio increased. No difference in lateral or medial hamstrings root mean square was found for any condition across all hip-flexion angles (P > .05). Hip-flexion angle influenced hamstrings peak torque in all muscular contraction types; as hip flexion increased, hamstrings peak torque increased. Researchers should investigate further whether an eccentric resistance training program at sprint-specific hip-flexion angles (70° to 80°) could help prevent hamstrings injuries in sprinters. Moreover, hamstrings-to-quadriceps ratio assessment should be standardized at 80° of hip flexion.

This study aims to model training adaptation using Artificial Neural Network (ANN) geometric optimisation. Over 26 weeks, 38 swimmers recorded their training and recovery data on a web platform. Based on these data, ANN geometric optimisation was used to model and graphically separate adaptation from maladaptation (to training). Geometric Activity Performance Index (GAPI), defined as the ratio of the adaptation to the maladaptation area, was introduced. The techniques of jittering and ensemble modelling were used to reduce overfitting of the model. Correlation (Spearman rank) and independence (Blomqvist β) tests were run between GAPI and performance measures to check the relevance of the collected parameters. Thirteen out of 38 swimmers met the prerequisites for the analysis and were included in the modelling. The GAPI based on external load (distance) and internal load (session-Rating of Perceived Exertion) showed the strongest correlation with performance measures. ANN geometric optimisation seems to be a promising technique to model training adaptation and GAPI could be an interesting numerical surrogate to track during a season.

[...]in a number of countries, a key factor influencing the recognition of SEM as a stand-alone medical specialty was the impact of SEM on disease management, quality of life and healthcare costs.3 SEM education: heterogeneous journeys to the grail Following the pioneer countries of Australia, New Zealand and the UK, several countries introduced a stand-alone SEM specialty for physicians (Argentina, Brazil, Latvia, Portugal, the Netherlands, Turkey, South Africa, Sri Lanka and Singapore). [...]young physicians desiring to pursue a career in SEM must combine full clinical training in another specialty before additional training in SEM. Unfortunately, sport physiotherapy is not a protected title in every country, often due to a lack of recognition by local health or sport authorities. [...]a sport physiotherapy title may not increase professional responsibility or earnings. [...]SEM should be more visible in the health-based undergraduate curricula.8 9 This exposure would contribute to raising awareness and unveiling vocation among students.