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Ursula G. Kyle
Researcher at Baylor College of Medicine
Publications - 96
Citations - 12551
Ursula G. Kyle is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Bioelectrical impedance analysis & Lean body mass. The author has an hindex of 45, co-authored 96 publications receiving 11210 citations. Previous affiliations of Ursula G. Kyle include Boston Children's Hospital & Geneva College.
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Journal ArticleDOI
Bioelectrical impedance analysis--part I: review of principles and methods.
Ursula G. Kyle,Ingvar Bosaeus,Antonio D. De Lorenzo,Paul Deurenberg,Marinos Elia,José Manuel Gómez,Berit L. Heitmann,Luisa Kent-Smith,Jean-Claude Melchior,Matthias Pirlich,Hermann Scharfetter,Annemie M. W. J. Schols,Claude Pichard +12 more
TL;DR: The use of bioelectrical impedance analysis (BIA) is widespread both in healthy subjects and patients, but suffers from a lack of standardized method and quality control procedures.
Journal ArticleDOI
Bioelectrical impedance analysis-part II: utilization in clinical practice.
Ursula G. Kyle,Ingvar Bosaeus,Antonio D. De Lorenzo,Paul Deurenberg,Marinos Elia,José Manuel Gómez,Berit L. Heitmann,Luisa Kent-Smith,Jean-Claude Melchior,Matthias Pirlich,Hermann Scharfetter,Annemie M. W. J. Schols,Claude Pichard +12 more
TL;DR: Clinical use of BIA in subjects at extremes of BMI ranges or with abnormal hydration cannot be recommended for routine assessment of patients until further validation has proven for BIA algorithm to be accurate in such conditions.
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Fat-free mass index and fat mass index percentiles in Caucasians aged 18-98 y.
TL;DR: Reference intervals for FFMI and FMI could be of practical value for the clinical evaluation of a deficit in fat-free mass with or without excess fat mass (sarcopenic obesity) for a given age category, complementing the classical concept of body mass index (BMI) in a more qualitative manner.
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Single prediction equation for bioelectrical impedance analysis in adults aged 20–94 years
TL;DR: Inclusion of reactance in the single prediction equation appeared to be essential for use of BIA equations in populations with large variations in age or body mass.
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Fat-free and fat mass percentiles in 5225 healthy subjects aged 15 to 98 years.
TL;DR: The results suggested that the greater weight noted in older subjects is due to larger FM, and the percentile data presented serve as reference to evaluate deviations from normal values of FFM and FM in healthy adult men and women at a given age.