Overtraining Syndrome (OTS) and Relative Energy Deficiency in Sport (RED-S): Shared Pathways, Symptoms and Complexities

Stellingwerff, Trent; Heikura, Ida A.; Meeusen, Romain; Bermon, Stéphane; Seiler, Stephen; Mountjoy, Margo; Burke, Louise M.

doi:10.1007/s40279-021-01491-0

Cited by 76 publications

(103 citation statements)

References 256 publications

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“…Furthermore, as shown in this study and other studies of exercising females, report of regular menstrual cycles may belie subtle menstrual hormone dysfunction [16]. Low energy availability is caused by a mismatch of energy intake and energy expenditure which can be intentional or unintentional [17]. Objective endocrine assessment of this situation is of clinical value.…”

Section: Monitoring Female Hormone Network Function: Artificial Intelligencesupporting

confidence: 53%

Clinical application of monitoring indicators of female dancer health, including application of artificial intelligence in female hormone networks

Keay

Lanfear

Francis³

2021

Preprint

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Objectives The purpose of this study was to assess the effectiveness of monitoring professional female dancer health with a variety of subjective and objective monitoring methods, including application of artificial intelligence (AI) techniques to modelling menstrual cycle hormones and delivering swift personalised clinical advice. Methods Female dancers from a ballet company completed a published online dance-specific health questionnaire. Over the study period, dancers recorded wellbeing and training metrics, with menstrual cycle tracking and blood tests. For menstrual cycle hormones AI-based techniques modelled hormone variation over a cycle, based on capillary blood samples taken at two time points. At regular, virtual, clinical interviews with each dancer, findings were discussed, and personalised advice given. Results 14 female dancers (mean age 25.5 years, SD 3.7) participated in the study. 10 dancers recorded positive scores on the dance health questionnaire, suggesting a low risk of relative energy deficiency in sport (RED-S). 2 dancers were taking hormonal contraception. Apart from 1 dancer, those not on hormonal contraception reported current eumenorrhoeic status. The initiative of monitoring menstrual cycles and application of AI to model menstrual cycle hormones found that subclinical hormone disruption was occurring in 6 of the 10 dancers reporting regular cycles. 4 of the 6 dancers who received personalised advice, showed improved menstrual hormone function, including one dancer who had planned pregnancy. Conclusions Multimodal monitoring facilitated delivery of prompt personalised clinical medical feedback specific for dance. This strategy enabled the early identification and swift management of emergent clinical issues. These innovations received positive feedback from the dancers.

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Section: Monitoring Female Hormone Network Function: Artificial Intelligencesupporting

confidence: 53%

Clinical application of monitoring indicators of female dancer health, including application of artificial intelligence in female hormone networks

Keay

Lanfear

Francis³

2021

Preprint

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“…It is a well-known fact that physical effort increases prolactin (PRL) levels as well as other hypothalamic-pituitary-adrenal axis hormones (ACTH and growth hormone GH) [77,78]. In more than half of the athletes, high levels of prolactin are observed [79].…”

Section: Other Considerationsmentioning

confidence: 99%

“…High-performing female and male athletes may also be affected by the RED-S syndrome (relative energy deficiency in sports), defined by the International Olimpic Committee in 2014 as a syndrome of health and performance impairment resulting from insufficient caloric intake and/or excessive energy expenditure [83]. The RED-S syndrome was adapted from a previous model, the female athlete triad, characterized by low-energy availability, which negatively impacts reproductive and bone health [78]. This condition may also affect hematologic parameters, immunity, metabolism, protein synthesis, growth and development, endocrine, digestive, cardiovascular, and psychologic functions [83].…”

Section: Other Considerationsmentioning

confidence: 99%

“…This condition may also affect hematologic parameters, immunity, metabolism, protein synthesis, growth and development, endocrine, digestive, cardiovascular, and psychologic functions [83]. RED-S has similarities with Overtraining Syndrome (OTS), both having a hypothalamic-pituitary origin and being influenced by low carbohydrate and energy availability [78]. Low energy availability may be partially induced and may contribute to iron deficiency [84].…”

Section: Other Considerationsmentioning

confidence: 99%

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Anemia in Sports: A Narrative Review

Damian

Vulturar

et al. 2021

Life

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Recent years have brought about new understandings regarding the pathogenesis of anemia in sports. From hemodilution and redistribution considered to contribute to the so-called “sports anemia” to iron deficiency caused by increased demands, dietary restrictions, decreased absorption, increased losses, hemolysis, and sequestration, to genetic determinants of different types of anemia (some related to sport), the anemia in athletes deserves a careful and multifactorial approach. Dietary factors that reduce iron absorption (e.g., phytate, polyphenols) and that augment iron’s bioavailability (e.g., ascorbic acid) should be considered. Celiac disease, more prevalent in female athletes, may underlie an unexplained iron deficiency anemia. Iron loss during exercise occurs in several ways: sweating, hematuria, gastrointestinal bleeding, inflammation, and intravascular and extravascular hemolysis. From a practical point of view, assessing iron status, especially in the athletes at risk for iron deficiency (females, adolescents, in sports with dietary restrictions, etc.), may improve the iron balance and possibly the performance. Hemoglobin and serum ferritin are measures that are easily employable for the evaluation of patients’ iron status. Cutoff values should probably be further assessed with respect to the sex, age, and type of sport. A healthy gut microbiome influences the iron status. Athletes at risk of iron deficiency should perform non-weight-bearing, low-intensity sports to avoid inducing hemolysis.

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“…Recently, an international team of physiologists and sport nutritionists published a narrative review paper that focused on the association between training overload and relative energy deficiency in sport (RED-S) (Stellingwerff, 2021). First introduced by the International Olympic Committee in 2014 (Mountjoy, 2014), RED-S is a complex syndrome caused by low energy availability that results in impaired physiological function and negative health/performance consequences.…”

Section: Diet Macronutrients and Energy Availabilitymentioning

confidence: 99%

Overtraining Syndrome as a Complex Systems Phenomenon

Armstrong

Bergeron²,

Lee

et al. 2022

Front. Netw. Physiol.

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The phenomenon of reduced athletic performance following sustained, intense training (Overtraining Syndrome, and OTS) was first recognized more than 90 years ago. Although hundreds of scientific publications have focused on OTS, a definitive diagnosis, reliable biomarkers, and effective treatments remain unknown. The present review considers existing models of OTS, acknowledges the individualized and sport-specific nature of signs/symptoms, describes potential interacting predisposing factors, and proposes that OTS will be most effectively characterized and evaluated via the underlying complex biological systems. Complex systems in nature are not aptly characterized or successfully analyzed using the classic scientific method (i.e., simplifying complex problems into single variables in a search for cause-and-effect) because they result from myriad (often non-linear) concomitant interactions of multiple determinants. Thus, this review 1) proposes that OTS be viewed from the perspectives of complex systems and network physiology, 2) advocates for and recommends that techniques such as trans-omic analyses and machine learning be widely employed, and 3) proposes evidence-based areas for future OTS investigations, including concomitant multi-domain analyses incorporating brain neural networks, dysfunction of hypothalamic-pituitary-adrenal responses to training stress, the intestinal microbiota, immune factors, and low energy availability. Such an inclusive and modern approach will measurably help in prevention and management of OTS.

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Overtraining Syndrome (OTS) and Relative Energy Deficiency in Sport (RED-S): Shared Pathways, Symptoms and Complexities

Cited by 76 publications

References 256 publications

Clinical application of monitoring indicators of female dancer health, including application of artificial intelligence in female hormone networks

Clinical application of monitoring indicators of female dancer health, including application of artificial intelligence in female hormone networks

Anemia in Sports: A Narrative Review

Overtraining Syndrome as a Complex Systems Phenomenon

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