scholarly journals Anthropometric Prediction of DXA-Measured Percentage of Fat Mass in Athletes With Unilateral Lower Limb Amputation

2020 ◽  
Vol 11 ◽  
Author(s):  
Valentina Cavedon ◽  
Marco Sandri ◽  
Massimo Venturelli ◽  
Carlo Zancanaro ◽  
Chiara Milanese
Keyword(s):  
Regression Analysis ◽  
Fat Mass ◽  
Lower Limb ◽  
Cross Validation ◽  
Linear Regression Analysis ◽  
White Male ◽  
Lower Limb Amputation ◽  
Limb Amputation ◽  
Skinfold Measurements ◽  
Fold Cross Validation

To date there is no anthropometric equation specific to athletes with unilateral lower limb amputation to estimate the percentage of fat mass (%FM). This study investigated the accuracy of a set of anthropometric equations validated on able-bodied populations to predict the %FM assessed by-means of dual-energy x-ray absorptiometry (DXA) in athletes with unilateral lower limb amputation. Furthermore, a predictive anthropometric equation specific to athletes with unilateral lower limb amputation was developed from skinfold thickness measurements using DXA as the reference method for the estimation of the %FM. Twenty-nine white male athletes with unilateral lower limb amputation underwent a DXA scan and an anthropometric assessment on the same day. The %FM, calculated through several existing anthropometric equations validated upon able-bodied populations, was compared with the DXA-measured %FM (%FM_DXA). Accuracy and agreement between the two methods was computed with two-tailed paired-sample t-test, concordance correlation coefficient, reduced major axis regression and Bland-Altman analysis. A stepwise multiple regression analysis with the %FM_DXA as the dependent variable and age and nine skinfold thicknesses as potential predictors was carried out and validated using a repeated 10-fold cross-validation. A linear regression analysis with the sum of nine skinfolds as the independent variable was also carried out and validated using a repeated 10-fold cross-validation. The results showed that the anthropometric equations validated on able-bodied populations are inaccurate in the estimation of %FM_DXA with an average bias ranging from 0.51 to −13.70%. Proportional bias was also found revealing that most of the anthropometric equations considered, tended to underestimate/overestimate the %FM_DXA as body fat increased. Regression analysis produced two statistically significant models (P < 0.001 for both) which were able to predict more than 93% of total variance of %FM_DXA from the values of four skinfold measurements (i.e., thigh, abdominal, subscapular and axillary skinfold measurements) or from the sum of 9 skinfolds. Repeated cross-validation analysis highlighted a good predictive performance of the proposed equations. The predictive equations proposed in this study represent a useful tool for clinicians, nutritionists, and physical conditioners to evaluate the physical and nutritional status of athletes with unilateral lower limb amputation directly in the field.

scholarly journals Predictors of quality of life among individuals who have a lower limb amputation

2008 ◽  
Vol 32 (2) ◽  
pp. 231-243 ◽  
Author(s):  
Miho Asano ◽  
Paula Rushton ◽  
William C. Miller ◽  
Barry A. Deathe
Keyword(s):  
Quality Of Life ◽  
Lower Limb ◽  
Linear Regression Analysis ◽  
Social Activity ◽  
Depression Scale ◽  
Lower Limb Amputation ◽  
Limb Amputation ◽  
Subjective Quality Of Life ◽  
Cross Sectional

Objective: The purpose of this study was to identify factors that predict an individual's subjective quality of life (QoL) after having a lower limb amputation.Design: Cross-sectional descriptive study design.Subjects: A total of 415 unilateral, above knee (27.0%) and below knee (73.0%) amputees with an average age of 61.9 years (SD = 15.7) who had lost their limb related to vascular (53.0%) or non-vascular (47.0%) etiology.Methods: Medical chart review, questionnaires (Frenchay Activities Index, Interpersonal Support Evaluation List, the Center for Epidemiology Studies – Depression scale, Prosthetic Evaluation Questionnaire mobility subscale, and the Activities-specific Balance Confidence Scale) and a QoL Visual Analogue Scale were assessed using multiple linear regression analysis.Results: The analysis revealed seven significant factors (depression, perceived prosthetic mobility, social support, comorbidity, prosthesis problems, age and social activity participation) as predictors of subjects' perceived QoL. Depression explained 30% of the variation, while the full model explained 42% of the variation.Conclusion: Several modifiable characteristics influence QoL after lower limb amputation including depression and participation in daily living. This finding suggests the importance of addressing individuals' affective status to regain or maintain QoL.

Analysis of the Relationships between Balance Ability and Walking in Terms of Muscle Activities and Lower Limb Kinematics and Kinetics

Biomechanics ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 190-201
Author(s):  
Pathmanathan Cinthuja ◽  
Graham Arnold ◽  
Rami J. Abboud ◽  
Weijie Wang
Keyword(s):  
Regression Analysis ◽  
Lower Limb ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression Analysis ◽  
Vastus Medialis ◽  
Balance Test ◽  
Balance Ability ◽  
Limb Kinematics ◽  
Lower Limb Kinematics ◽  
Kinematics And Kinetics

There is a lack of evidence about the ways in which balance ability influences the kinematic and kinetic parameters and muscle activities during gait among healthy individuals. The hypothesis is that balance ability would be associated with the lower limb kinematics, kinetics and muscle activities during gait. Twenty-nine healthy volunteers (Age 32.8 ± 9.1; 18 males and 11 females) performed a Star Excursion Balance test to measure their dynamic balance and walked for at least three trials in order to obtain a good quality of data. A Vicon® 3D motion capture system and AMTI® force plates were used for the collection of the movement data. The selected muscle activities were recorded using Delsys® Electromyography (EMG). The EMG activities were compared using the maximum values and root mean squared (RMS) values within the participants. The joint angle, moment, force and power were calculated using a Vicon Plug-in-Gait model. Descriptive analysis, correlation analysis and multivariate linear regression analysis were performed using SPSS version 23. In the muscle activities, positive linear correlations were found between the walking and balance test in all muscles, e.g., in the multifidus (RMS) (r = 0.800 p < 0.0001), vastus lateralis (RMS) (r = 0.639, p < 0.0001) and tibialis anterior (RMS) (r = 0.539, p < 0.0001). The regression analysis models showed that there was a strong association between balance ability (i.e., reaching distance) and the lower limb muscle activities (i.e., vastus medialis–RMS) (R = 0.885, p < 0.0001), and also between balance ability (i.e., reaching distance) and the lower limb kinematics and kinetics during gait (R = 0.906, p < 0.0001). In conclusion, the results showed that vastus medialis (RMS) muscle activity mainly contributes to balance ability, and that balance ability influences the lower limb kinetics and kinematics during gait.

scholarly journals P90 PERCEIVE: PrEdiction of Risk and Communication of outcome following major lower limb amputation - a collaboratIVE study

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
B Gwilym ◽  
C Waldron ◽  
E Thomas-Jones ◽  
P Pallmann ◽  
R Preece ◽  
...  
Keyword(s):  
Risk Prediction ◽  
Lower Limb ◽  
Health Care Professionals ◽  
Healthcare Professionals ◽  
Demographic Data ◽  
Collaborative Study ◽  
Lower Limb Amputation ◽  
Research Network ◽  
Limb Amputation ◽  
Prediction Tools

Abstract Introduction Major Lower Limb Amputation (MLLA) is a life changing event with significant morbidity and mortality. Inaccurate risk prediction can lead to poor decision making, resulting in delay to definitive surgery, or undertaking amputation when not in the patient’s best interest. We aim to answer: In adult patients undergoing MLLA for chronic limb threatening ischaemia or diabetes, how accurately do health care professionals prospectively predict outcomes after MLLA, and how does this compare to existing prediction tools? Methods A multicentre prospective observational cohort study is being delivered through the Vascular and Endovascular Research Network. Dissemination was via an existing network of contacts and social media. Consecutive data will be collected for seven months from site launch date, including demographic data and pre-operative outcome predictions from surgeons, anaesthetists, and allied healthcare professionals. Follow-up data will comprise 30-day (mortality, morbidity, MLLA revision, surgical site infection, and blood transfusion) and 1-year (mortality, MLLA revision and ambulation). The accuracy of surgeons’ predictions will be evaluated and compared to pre-existing risk prediction scoring tools. Results PERCEIVE launched on 01/10/2020 with 23 centres (16 UK, 7 international) registered to collect data. 50 other centres (27 UK, 23 international) have expressed interest/are pursuing local audit/ethical approval. We aim to collect data on clinicians estimate of outcomes for over 500 patients. Discussion This study will utilise a trainee research network to provide data on the accuracy of healthcare professionals’ predictions of outcomes following MLLA and compare this to the utility of existing prediction tools in this patient cohort.

The impact of legs fat mass and legs lean fat mass on thigh circumference according cardiovascular risk: a population-based study

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
M Chlabicz ◽  
M Paniczko ◽  
J Jamolkowski ◽  
P Sowa ◽  
M Lapinska ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Regression Analysis ◽  
Linear Regression ◽  
Muscle Tissue ◽  
Fat Mass ◽  
Linear Regression Analysis ◽  
Population Based ◽  
Thigh Circumference ◽  
Tissue Model ◽  
The Mean

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Medical University of Bialystok, Poland Introduction A low thigh circumference is associated with an increased risk of high blood pressure, diabetes, cardiovascular diseases, and total mortality. Objectives The aim of the study was to investigate the relationship between the thigh circumference and cardiovascular (CV) risk classes, and to assess what type of tissue, adipose tissue or muscle tissue affects the thigh circumference. Methods The longitudinal, population-based, Polish study was conducted in 2017-2020. A total of 931 individuals aged 20-79 were analyzed. Pol-SCORE system was used to assess the 10-year risk of fatal CV based on the following risk factors: age, gender, smoking, systolic blood pressure, and total cholesterol for individuals aged 40-70.  Then, CV risk classes were assessed using the 2019 ESC/EAS guidelines. The measurement of thigh circumference were performed directly below the gluteal fold of the thigh. Both thighs were measured and the mean value was calculated as the final thigh circumference. Body composition was assessed using Dual Energy X-ray Absorptiometry (DEXA). Results The mean age was 49.1 ± 15.5 years and 43.2% male. The mean thigh circumference was 58.2 ± 5.9 cm, the mean legs fat mass was 7.7 ± 2.8kg, and the mean legs lean mass was 16.9 ± 4.0kg. Lower thigh circumference was associated with higher CV risk classes in univariate linear regression analysis (β -0.516, p = 0.002), as well adjusted by age and sex (β -0.839, p = 0.008), adjusted by age, sex, BMI (β -0.886, p &lt;0.001), and age, sex, WHR (β -0.988, p &lt;0.001). In linear regression analysis legs adipose tissue and muscle tissue were related to the thigh circumference independently of CV risk classes (Model 1) and Pol-SCORE value (Model 2). However, fatty tissue (Model 1: β 0.746, p &lt; 0.001; Model 2: β 0.749, p &lt; 0.001) affects the thigh circumference more than the muscle tissue (Model 1: β 0.479, p &lt; 0.001; Model 2: β 0.442, p &lt; 0.001) (Fig. 1). Conclusion Smaller thigh circumference was associated with higher CV risk classes. Thigh circumference was more influenced by adipose tissue than by muscle tissue, regardless of the Pol-SCORE  or CV risk classes. Table 1. Variable Model 1 Model 2 Beta p R2 Beta p R2 Legs fat mass 0.746 &lt;0.001 0.785 0.749 &lt;0.001 0.760 Legs lean mass 0.479 &lt;0.001 0.785 0.442 &lt;0.001 0.760 Model 1: adjusted for Cardiovascular risk classesModel 2: adjusted for Pol-SCOREResults of the linear regression analysis thigh circumference in the general population Abstract Figure 1.

scholarly journals Socio-economic outcome of paraplegia compared to lower limb amputation

Spinal Cord ◽  
2002 ◽  
Vol 40 (4) ◽  
pp. 174-177 ◽  
Author(s):  
A Cavigelli ◽  
R Fischer ◽  
V Dietz
Keyword(s):  
Lower Limb ◽  
Lower Limb Amputation ◽  
Economic Outcome ◽  
Limb Amputation

scholarly journals Geographic Variation of the Incidence Rate of Lower Limb Amputation in Australia from 2007-12

PLoS ONE ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. e0170705 ◽  
Author(s):  
Michael P. Dillon ◽  
Lauren V. Fortington ◽  
Muhammad Akram ◽  
Bircan Erbas ◽  
Friedbert Kohler
Keyword(s):  
Incidence Rate ◽  
Geographic Variation ◽  
Lower Limb ◽  
Lower Limb Amputation ◽  
Limb Amputation
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