Sarcopenia and Risk of Fall in Osteoporotic Postmenopausal Women
Sarcopenia
1 other identifier
interventional
40
1 country
1
Brief Summary
The main scope of the present pilot study is to evaluate the possible association between the status of sarcopenia and the risk of fall in osteoporotic postmenopausal women. Forty osteoporotic postmenopausal women, previously (pre-recruitment) classified by DXA in 20 sarcopenic and 20 non-sarcopenic subjects, will be recruited. The investigators will collect data on: 1) bone (vitamin D) and muscle (myokines) metabolisms through blood sampling; 2) Risk of fall by the OAK device produced by Khymeia; 3) thigh muscle quality through MR.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for not_applicable
Started Mar 2017
Typical duration for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
March 29, 2017
CompletedFirst Submitted
Initial submission to the registry
December 4, 2017
CompletedFirst Posted
Study publicly available on registry
December 22, 2017
CompletedPrimary Completion
Last participant's last visit for primary outcome
May 31, 2019
CompletedStudy Completion
Last participant's last visit for all outcomes
May 31, 2019
CompletedJuly 17, 2018
July 1, 2018
2.2 years
December 4, 2017
July 16, 2018
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Association between sarcopenia, meant as the percentage of fat fraction of the thigh muscle evaluated by RM, and risk of fall evaluated through the OAK device.
The fat fraction of the thigh muscle is obtained by RM and expressed in percentage (%) of fat on muscle. The risk of fall will be derived by the final score of the OAK device system. The score range is 0-24. Higher scores represent lower risk of falls.
2 days.
Association between sarcopenia, meant as the Appensicular Skeletal Muscle Mass Index (ASMMI) obtained by DXA, and risk of fall evaluated through the OAK device.
ASMMI is obtained by DXA and calculated with the following formula: (total grams of lean muscle mass of left and right lower and upper limbs)/height\*height, expressed in meters. The risk of fall will be derived by the final score of the OAK device system. The score range is 0-24. Higher scores represent lower risk of falls.
2 days.
Secondary Outcomes (2)
Comparison of the fat fraction of the thigh muscle, obtained by RM, between sarcopenic and non-sarcopenic subjects.
2 days.
Comparison of risk of fall, evaluated with the use of the OAK device, between sarcopenic and non-sarcopenic subjects.
2 days.
Study Arms (2)
Sarcopenic Group
OTHERThis group is composed by 20 osteoporotic postmenopausal women, previously (pre-recruitment) classified as "sarcopenic" by the DXA. This group will undergo the same evaluations/intervention of the second group.
Non-sarcopenic Group
OTHERThis group is composed by 20 osteoporotic postmenopausal women, previously (pre-recruitment) classified as "non-sarcopenic" by the DXA. This group will undergo the same evaluations/intervention of the first group.
Interventions
Data will be collected on 1) bone/muscle metabolism through blood sampling, 2) risk of fall through OAK device; 3) muscle quality through MR acquisition.
Eligibility Criteria
You may qualify if:
- Female.
- Aged over 60 yo.
- Classified as osteoporotic with t-score = or \< -2,5 evaluated by DXA.
- Autonomous walking.
- Signed informed consent.
You may not qualify if:
- Male.
- Aged under 60 yo.
- Psychiatric disorders.
- Neurological pathologies.
- Endocrine disorders.
- Active cigarettes smoke.
- Recent bone fractures (6 months)
- Surgical treatments for orthopedic pathologies (6 months).
- Pacemaker carrier.
- Use of drugs influencing bone metabolism or limiting physical function.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
IRCCS Istituto Ortopedico Galeazzi
Milan, 20161, Italy
Related Publications (10)
Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, Martin FC, Michel JP, Rolland Y, Schneider SM, Topinkova E, Vandewoude M, Zamboni M; European Working Group on Sarcopenia in Older People. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010 Jul;39(4):412-23. doi: 10.1093/ageing/afq034. Epub 2010 Apr 13.
PMID: 20392703BACKGROUNDLourenco RA, Perez-Zepeda M, Gutierrez-Robledo L, Garcia-Garcia FJ, Rodriguez Manas L. Performance of the European Working Group on Sarcopenia in Older People algorithm in screening older adults for muscle mass assessment. Age Ageing. 2015 Mar;44(2):334-8. doi: 10.1093/ageing/afu192. Epub 2014 Dec 23.
PMID: 25539836BACKGROUNDSergi G, Trevisan C, Veronese N, Lucato P, Manzato E. Imaging of sarcopenia. Eur J Radiol. 2016 Aug;85(8):1519-24. doi: 10.1016/j.ejrad.2016.04.009. Epub 2016 Apr 14.
PMID: 27117135BACKGROUNDTosato M, Marzetti E, Cesari M, Savera G, Miller RR, Bernabei R, Landi F, Calvani R. Measurement of muscle mass in sarcopenia: from imaging to biochemical markers. Aging Clin Exp Res. 2017 Feb;29(1):19-27. doi: 10.1007/s40520-016-0717-0. Epub 2017 Feb 7.
PMID: 28176249BACKGROUNDRubbieri G, Mossello E, Di Bari M. Techniques for the diagnosis of sarcopenia. Clin Cases Miner Bone Metab. 2014 Sep;11(3):181-4.
PMID: 25568650BACKGROUNDBaumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, Garry PJ, Lindeman RD. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol. 1998 Apr 15;147(8):755-63. doi: 10.1093/oxfordjournals.aje.a009520.
PMID: 9554417BACKGROUNDRoubenoff R, Hughes VA. Sarcopenia: current concepts. J Gerontol A Biol Sci Med Sci. 2000 Dec;55(12):M716-24. doi: 10.1093/gerona/55.12.m716.
PMID: 11129393BACKGROUNDCummings-Vaughn LA, Gammack JK. Falls, osteoporosis, and hip fractures. Med Clin North Am. 2011 May;95(3):495-506, x. doi: 10.1016/j.mcna.2011.03.003.
PMID: 21549874BACKGROUNDTyson SF, Connell LA. How to measure balance in clinical practice. A systematic review of the psychometrics and clinical utility of measures of balance activity for neurological conditions. Clin Rehabil. 2009 Sep;23(9):824-40. doi: 10.1177/0269215509335018. Epub 2009 Aug 5.
PMID: 19656816BACKGROUNDDixon WT. Simple proton spectroscopic imaging. Radiology. 1984 Oct;153(1):189-94. doi: 10.1148/radiology.153.1.6089263.
PMID: 6089263BACKGROUND
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NON RANDOMIZED
- Masking
- NONE
- Purpose
- PREVENTION
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
December 4, 2017
First Posted
December 22, 2017
Study Start
March 29, 2017
Primary Completion
May 31, 2019
Study Completion
May 31, 2019
Last Updated
July 17, 2018
Record last verified: 2018-07