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The influence of acute exercise on bone biomarkers: protocol for a systematic review with meta-analysis. [Protocol]

Dolan, E.; Dumas, A.; Keane, K.M.; Bestetti, G.; Freitas, L.H.M.; Gualano, B.; Kohrt, W.; Kelley, G.A.; Pereira, R.M.R.; Sale, C.; Swinton, P.

Authors

E. Dolan

A. Dumas

K.M. Keane

G. Bestetti

L.H.M. Freitas

B. Gualano

W. Kohrt

G.A. Kelley

R.M.R. Pereira

C. Sale



Abstract

Bone is a plastic tissue that is responsive to its physical environment. As a result, exercise interventions represent a potential means to influence bone. However, little is currently known about how various exercise and participant characteristics interact to influence bone metabolism. Acute, controlled, interventions provide an in-vivo model through which the acute bone response to exercise can be investigated, typically by monitoring circulating bone biomarkers. Currently, substantial heterogeneity in factors such as study design, quality, exercise and participant characteristics render it difficult to synthesize and evaluate the available evidence. Using a systematic review and meta-analytic approach, the aim of this investigation is to quantify the effect of an acute exercise bout on circulating bone biomarkers as well as examine potential factors that may moderate this response e.g., variation in participant, exercise and sampling characteristics. This protocol was designed in accordance with PRISMA-P guidelines. Seven databases (Medline, Embase, Sport Discus, Cochrane CENTRAL, PEDro, LILACS and Ibec) will be systematically searched and supplemented by secondary screening of the reference lists of all included articles. The PICOS (Population, Intervention, Comparator, Outcomes and Study Design) approach was used to guide the determination of eligibility criteria. Participants of any age, sex, training or health status will be considered for inclusion. We will select studies that have measured the bone biomarker response before and after an acute exercise session. All biomarkers considered to represent bone metabolism will be considered for inclusion and sensitivity analyses will be conducted using reference biomarkers for the measurement of bone resorption and formation (namely β-CTX-1 and P1NP). Multi-level, meta-regression models within a Bayesian framework will be used to explore the main effect of acute exercise on bone biomarkers as well as potential moderating factors. Risk of bias for each individual study will be evaluated using a modified version of the Downs and Black checklist while certainty in resultant outcomes will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Discussion: A better understanding of the bone metabolic response to an acute bout of exercise has the potential to advance our understanding of the mechanisms through which this stimulus impacts bone metabolism, including factors that may moderate this response. Additionally, we will identify current gaps in the evidence base and provide recommendations to inform future research. This protocol was prospectively registered in the Open Science Framework Registry (https://osf.io/6f8dz)

Citation

DOLAN, E., DUMAS, A., KEANE, K.M., BESTETTI, G., FREITAS, L.H.M., GUALANO, B., KOHRT, W., KELLEY, G.A., PEREIRA, R.M.R., SALE, C. and SWINTON, P. 2020. The influence of acute exercise on bone biomarkers: protocol for a systematic review with meta-analysis. [Protocol]. Systematic reviews [online], 9, article ID 291. Available from: https://doi.org/10.1186/s13643-020-01551-y

Other Type Experiment
Acceptance Date Nov 30, 2020
Online Publication Date Dec 12, 2020
Publication Date Dec 31, 2020
Deposit Date Dec 7, 2020
Publicly Available Date Mar 29, 2024
Publisher Springer
DOI https://doi.org/10.1186/s13643-020-01551-y
Keywords Exercise; Bone; Meta-analysis; Systematic review
Public URL https://rgu-repository.worktribe.com/output/1003590
Related Public URLs https://rgu-repository.worktribe.com/output/1681889
https://rgu-repository.worktribe.com/output/1724559
Additional Information This protocol was prospectively registered in the Open Science Framework Registry, available from: https://osf.io/6f8dz