Comprehensive Return to Competitive Distance Running: A Clinical Commentary

KeepRunning: A MoCap-Based Rapid Test to Prevent Musculoskeletal Running Injuries

The worldwide popularisation of running as a sport and recreational practice has led to a high rate of musculoskeletal injuries, usually caused by a lack of knowledge about the most suitable running technique for each runner. This running technique is determined by a runner's anthropometric body characteristics, dexterity and skill. Therefore, this study aims to develop a motion capture-based running analysis test on a treadmill called KeepRunning to obtain running patterns rapidly, which will aid coaches and clinicians in assessing changes in running technique considering changes in the study variables. Therefore, a review and proposal of the most representative events and variables of analysis in running was conducted to develop the KeepRunning test. Likewise, the minimal detectable change (MDC) in these variables was obtained using test-retest reliability to demonstrate the reproducibility and viability of the test, as well as the use of MDC as a threshold for future assessments. The test-retest consisted of 32 healthy volunteer athletes with a running training routine of at least 15 km per week repeating the test twice. In each test, clusters of markers were placed on the runners' body segments using elastic bands and the volunteers' movements were captured while running on a treadmill. In this study, reproducibility was defined by the intraclass correlation coefficient (ICC) and MDC, obtaining a mean value of ICC = 0.94 ± 0.05 for all variables and MDC = 2.73 ± 1.16° for the angular kinematic variables. The results obtained in the test-retest reveal that the reproducibility of the test was similar or better than that found in the literature. KeepRunning is a running analysis test that provides data from the involved body segments rapidly and easily interpretable. This data allows clinicians and coaches to objectively provide indications for runners to improve their running technique and avoid possible injury. The proposed test can be used in the future with inertial motion capture and other wearable technologies.

How Advancement in Bone Science Should Inform the Examination and Treatment of Femoral Shaft Bone Stress Injuries in Running Athletes

Stress fractures likely have a 1-2% incidence in athletes in general. In runners, a more vulnerable population, incidence rates likely range between 3.2 and 21% with female runners having greater susceptibility. The incidence of femoral shaft stress fractures is less well known. New basic and translational science research may impact the way clinicians diagnose and treat femoral stress fractures. By using a fictitious case study, this paper applies bone science to suggest new approaches to evaluating and treating femoral shaft stress fractures in the running population.

Are models of plantar heel pain suitable for competitive runners? A narrative review

Background

Plantar heel pain (PHP), or plantar fasciopathy, is a common condition in active and sedentary populations, contributing to short- and long-term reductions in quality of life. The condition's aetiology and pathophysiology are the subjects of a significant body of research. However, much of this research has been conducted with sedentary participants, and comparatively little research exists in a population of highly-trained athletes focused on performance outcomes. Models for PHP and proposed mechanisms, such as high body mass index or systemic disease, are mostly absent from an athletic population. Even less is known about the origins of pain in PHP. Pain is believed to be a complex multifactorial process and may be experienced differently by sedentary and highly active populations, particularly endurance athletes. Consequently, conservative through to surgical treatment for athletes is informed by literature for a different population, potentially hindering treatment outcomes.

Aims

The aim of this review, therefore, is to summarise what is known about PHP in athletic populations and propose potential directions for future research.

Methods

Embase, PubMed, and Scopus using MeSH search terms for PHP and competitive sport and common synonyms.

Discussion

Two explanatory models for PHP were found. These primarily propose mechanical factors for PHP. It remains unclear how gait, body composition, and psychological factors may differ in an athletic population with and without PHP. Therefore, research in these three areas is needed to inform clinical and training interventions for this population.