Comparison of Bone Quality Among Winter Endurance Athletes with and Without Risk Factors for Relative Energy Deficiency in Sport (REDs): A Cross-Sectional Study

Wyatt, Patrick; Drager, Kelly L; Groves, Erik M.; Stellingwerff, Trent; Billington, Emma O; Boyd, Steven K.; Burt, Lauren A

doi:10.1007/s00223-023-01120-0

Cited by 4 publications

(3 citation statements)

References 45 publications

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“…For more information on the study inclusion and exclusion criteria and study-specific health data for these participants, please see the corresponding studies. [17] 1244 56 [18,93] 472M, 772F 1243R, 1245T Hip fracture [18] 110 72 [57, 97] 25M, 85F 109R, 176T Athletes [19], [20] 80 24 [14,41] 36M, 44F 103R, 111T Aggregated 1434 57 [14,97] 533M, 901F 1455R, 1532T Sex: M -male, F -female. Images: R -radius, T -tibia.…”

Section: Resultsmentioning

confidence: 99%

“…Image data captured in vivo with human participants were aggregated from four separate studies performed in our lab exploring bone microarchitecture by HR-pQCT, which were: a normative study [17], a hip fracture study [18], and two studies with high-performance athletes [19], [20]. All images were obtained using HR-pQCT (XtremeCT II, Scanco Medical AG, Brütisellen, Switzerland) with the standard fixed offset in vivo scan protocol at standard scan sites for the distal radius and tibia.…”

Section: Methodsmentioning

confidence: 99%

“…Turning to bone volume fraction, we first note that this parameter is defined as the ratio of bone volume to total volume within a compartment. We hypothesize that within a unit volume, this ratio will scale as some power of the ratio of the trabecular thickness to the sum of trabecular thickness and separation: Image data captured in vivo with human participants were aggregated from four separate studies performed in our lab exploring bone microarchitecture by HR-pQCT, which were: a normative study [17], a hip fracture study [18], and two studies with high-performance athletes [19], [20]. All images were obtained using HR-pQCT (XtremeCT II, Scanco Medical AG, Brütisellen, Switzerland) with the standard fixed offset in vivo scan protocol at standard scan sites for the distal radius and tibia.…”

Section: Theoretical Relationshipsmentioning

confidence: 99%

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Interdependence of trabecular microarchitectural parameters from micro-computed tomography

Neeteson,

Bugbird,

Burt

et al. 2024

Preprint

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Standard microarchitectural analysis of bone using micro-computed tomography produces a large number of parameters that quantify the structure of the trabecular network. Analyses that perform statistical tests on many parameters are at elevated risk of making Type I errors. However, when multiple testing correction procedures are applied, the risk of Type II errors is elevated if the parameters being tested are strongly correlated. In this article, we argue that four commonly used trabecular microarchitectural parameters (thickness, separation, number, and bone volume fraction) are interdependent and describe only two independent properties of the trabecular network. We first derive theoretical relationships between the parameters based on their geometric definitions. Then, we analyze these relationships with an aggregated in vivo dataset with 2987 images from 1434 participants and a synthetically generated dataset with 144 images using principal component analysis (PCA) and linear regression analysis. With PCA, when trabecular thickness, separation, number, and bone volume fraction are combined, we find that 92% to 97% of the total variance in the data is explained by the first two principal components. With linear regressions, we find high coefficients of determination (0.827 to 0.994) and fitted coefficients within expected ranges. These findings suggest that to maximize statistical power in future studies, only two of trabecular thickness, separation, number and bone volume fraction should be used for statistical testing.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Theoretical Relationshipsmentioning

confidence: 99%

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Interdependence of trabecular microarchitectural parameters from micro-computed tomography

Neeteson,

Bugbird,

Burt

et al. 2024

Preprint

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Does Relative Energy Deficiency in Sport (REDs) Syndrome Exist?

Jeukendrup,

Areta,

Van Genechten

et al. 2024

Sports Med

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Relative energy deficiency in sport (REDs) is a widely adopted model, originally proposed by an International Olympic Committee (IOC) expert panel in 2014 and recently updated in an IOC 2023 consensus statement. The model describes how low energy availability (LEA) causes a wide range of deleterious health and performance outcomes in athletes. With increasing frequency, sports practitioners are diagnosing athletes with “REDs,” or “REDs syndrome,” based largely upon symptom presentation. The purpose of this review is not to “debunk” REDs but to challenge dogmas and encourage rigorous scientific processes. We critically discuss the REDs concept and existing empirical evidence available to support the model. The consensus (IOC 2023) is that energy availability, which is at the core of REDs syndrome, is impossible to measure accurately enough in the field, and therefore, the only way to diagnose an athlete with REDs appears to be by studying symptom presentation and risk factors. However, the symptoms are rather generic, and the causes likely multifactorial. Here we discuss that (1) it is very difficult to isolate the effects of LEA from other potential causes of the same symptoms (in the laboratory but even more so in the field); (2) the model is grounded in the idea that one factor causes symptoms rather than a combination of factors adding up to the etiology. For example, the model does not allow for high allostatic load (psychophysiological “wear and tear”) to explain the symptoms; (3) the REDs diagnosis is by definition biased because one is trying to prove that the correct diagnosis is REDs, by excluding other potential causes (referred to as differential diagnosis, although a differential diagnosis is supposed to find the cause, not demonstrate that it is a pre-determined cause); (4) observational/cross-sectional studies have typically been short duration (< 7 days) and do not address the long term “problematic LEA,” as described in the IOC 2023 consensus statement; and (5) the evidence is not as convincing as it is sometimes believed to be (i.e., many practitioners believe REDs is well established). Very few studies can demonstrate causality between LEA and symptoms, most studies demonstrate associations and there is a worrying number of (narrative) reviews on the topic, relative to original research. Here we suggest that the athlete is best served by an unbiased approach that places health at the center, leaving open all possible explanations for the presented symptoms. Practitioners could use a checklist that addresses eight categories of potential causes and involve the relevant experts if and when needed. The Athlete Health and Readiness Checklist (AHaRC) we introduce here simply consists of tools that have already been developed by various expert/consensus statements to monitor and troubleshoot aspects of athlete health and performance issues. Isolating the purported effects of LEA from the myriad of other potential causes of REDs symptoms is experimentally challenging. This renders the REDs model somewhat immune to falsification and we may never definitively answer the question, “does REDs syndrome exist?” From a practical point of view, it is not necessary to isolate LEA as a cause because all potential areas of health and performance improvement should be identified and tackled.

show abstract

Statistical investigation of interdependence of trabecular microarchitectural parameters from micro-computed tomography

Neeteson,

Bugbird,

Burt

et al. 2024

Bone

View full text Add to dashboard Cite

Comparison of Bone Quality Among Winter Endurance Athletes with and Without Risk Factors for Relative Energy Deficiency in Sport (REDs): A Cross-Sectional Study

Cited by 4 publications

References 45 publications

Interdependence of trabecular microarchitectural parameters from micro-computed tomography

Interdependence of trabecular microarchitectural parameters from micro-computed tomography

Does Relative Energy Deficiency in Sport (REDs) Syndrome Exist?

Statistical investigation of interdependence of trabecular microarchitectural parameters from micro-computed tomography

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