Ignite Creation Date:
2024-10-26 @ 3:37 PM
Last Modification Date:
2024-10-26 @ 3:37 PM
Study NCT ID:
NCT06545435
Status:
RECRUITING
Last Update Posted:
None
First Post:
2024-08-05
Brief Title:
Predicting Appendicular Lean and Fat Mass With Bioelectrical Impedance Analysis Among Adult Patients With Obesity
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Predicting Appendicular Lean and Fat Mass With Bioelectrical Impedance Analysis Among Adult Patients With Obesity
Status:
RECRUITING
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
This study aims to develop and cross-validate novel bioelectrical impedance analysis BIA equations for predicting appendicular soft tissue masses specifically fat mass FM and appendicular lean mass ALM in a sample of Caucasian adult subjects affected by obesity The research will compare these new BIA equations with three established BIA-derived prediction models and validate them using dual-energy X-ray absorptiometry DXA and magnetic resonance imaging MRI data This study utilizes existing datasets to enhance the accuracy and applicability of BIA in assessing body composition and supports the development of standardized algorithms for converting raw BIA data across different devices and populations
Detailed Description:
Assessing body composition in persons with obesity and in particular the excess of fat mass and the possible reduction of muscle mass is important to define the phenotypic manifestation of obesity estimating the risk of dysmetabolic cardiovascular and functional complications and to determine a better treatment approach Dual X-ray absorptiometry DXA is a mature technology for assessing body composition with major advances in the technology over the past three decades DXA is a validated tool to investigate body composition phenotypes as it reliably assesses whole-body and regional bone mineral content fat mass and lean mass Unfortunately it is not always available in all settings where instead Bio-Impedance Analysis BIA which has lower costs and greater convenience of use is commonly used to estimate body composition starting from electrical resistance and reactance data
Regrettably the two methods often give non-superimposable results and studies have been carried out to predict from BIA values commonly obtainable only with DXA In particular different studies estimated the appendicular lean mass from BIA which represents an important parameter for the evaluation of sarcopenia and is correlated with its functional limitations For example a post hoc analysis of the PROVIDE study was aimed in particular at assessing the level of agreement between BIA- and DXA-derived soft tissue ratios as indicators of limb tissue quality and at developing and cross-validating new BIA equations for predicting appendicular soft tissue fat mass FM and appendicular lean mass ALM in older Caucasian adults with physical function decline using both the Hologic Horizon and GE Lunar DXA systems as reference methods
METHODS
This study is based on baseline data anthropometric BIA and DXA collected in pre-existing datasets In particular
the Sapienza dataset which derived from a study aimed at investigating the association between markers of insulin sensitivity and SO defined by three novel body composition models will be used to develop BIA equations predicting appendicular soft tissue masses
datasets from different studies and in particular from the BIA International Dataset Project will be used to validate the BIA equations assessing the agreement between BIA- and DXA-derived soft tissue estimation
STUDY PARAMETERS
-Anthropometry anthropometric parameters should have been measured in accordance with validated and standardized methodologies
The anthropometric parameters of interest are body mass stature waist circumference calf circumference arm circumference and triceps skinfold thickness limb length
-Dual energy X-ray absorptiometry all participants should have been scanned using a fan beam whole body DXA device Hologic Bedford Massachusetts USA Lunar Prodigy GE Healthcare Daily calibration of the densitometers should have been performed following the instructions provided by the manufacturer
Since measurements vary among instruments from different manufacturers calibration equations will be used to address these issues and improve the agreement between devices
The body components of interest are total fat mass FM total lean mass LM ALM sum of the lean mass in the limbs FM sum of the fat mass in the limbs and the ratio of ALM to FM
-Bioelectrical impedance analysis After overnight fasting and bladder voiding bioelectrical impedance analysis should have been performed with participants lying supine with their limbs slightly away from their body active electrodes should have been placed on the right side on conventional metacarpal and metatarsal lines recording electrodes in standard positions at the right wrist and ankle or in vertical position barefoot stepping onto the electrodes embedded into the scale and grasping the electrode-embedded handles At each location a whole-body tetrapolar BIA device operating at a weak alternating electrical current of 500 µA to 1 mA and a single frequency of 50 kHz should have been used to measure the voltage drop across body tissues
The electric parameters of interest are resistance R restriction of current flow reactance Xc capacitance of cell membranes and tissue interfaces and phase angle PhA
The information about BIA devices will be recorded since raw R and Xc values may not be not comparable
Due to the significant differences found in different studies when comparing vertical to supine position the results obtained with the two methodologies will be analysed separately
With reference to the limitation reported by the PROVIDE study authors ie the absence of a direct measurement of extracellular water the raw data detected through multifrequency bioimpedance devices will also be used where available Specifically the values of impedance and resistance measured at a frequency of 5 kHz will be included furthermore where available it would be optimal to analyze data measured at the following frequencies 1 2 5 10 50 100 200 250 and 500 kHz
STATISTICS
Data will be analyzed by using IBM SPSS Statistics version 25 The data will be presented as frequency percent and mean SD for qualitative and quantitative variables respectively The Shapiro-Wilk test will be used to evaluate if the data are normally distributed Comparison of continuous variables will be performed using parametric or non-parametric tests depending on whether the distribution is normal or not The chi-square test will be used to check whether the frequencies occurring in the sample differ significantly from the expected frequencies The cut-off for statistical significance will be set at p005
Preliminary equations using DXA-derived appendicular lean and fat mass as the dependent variables and age gender BMI weight impedance index and reactance as independent variables will be developed using a stepwise multiple linear regression approach Only significant regressors of appendicular soft tissue masses will be considered in the equations
Model performance fit will be assessed using multiple correlations R2 and standard errors of the estimate SEE For each of the appendicular soft tissue components the model with the lowest standard error of the estimate will be used in the cross-validation analysis
The individual and body composition data from the cross-validation samples will be imputed into the developed equations to assess their accuracy The statistics for cross-validation includes mean difference limits of agreement and root mean squared error
Additionally the agreement between ALM_BIA estimated in our sample ALM_SERGI ALM_Provide and ALM_KYLE will be assessed using regression analysis
Finally the agreement between the ALMFM-ratios estimated by DXA and by BIA will be evaluated using Bland and Altman analysis
Regrettably the two methods often give non-superimposable results and studies have been carried out to predict from BIA values commonly obtainable only with DXA In particular different studies estimated the appendicular lean mass from BIA which represents an important parameter for the evaluation of sarcopenia and is correlated with its functional limitations For example a post hoc analysis of the PROVIDE study was aimed in particular at assessing the level of agreement between BIA- and DXA-derived soft tissue ratios as indicators of limb tissue quality and at developing and cross-validating new BIA equations for predicting appendicular soft tissue fat mass FM and appendicular lean mass ALM in older Caucasian adults with physical function decline using both the Hologic Horizon and GE Lunar DXA systems as reference methods
METHODS
This study is based on baseline data anthropometric BIA and DXA collected in pre-existing datasets In particular
the Sapienza dataset which derived from a study aimed at investigating the association between markers of insulin sensitivity and SO defined by three novel body composition models will be used to develop BIA equations predicting appendicular soft tissue masses
datasets from different studies and in particular from the BIA International Dataset Project will be used to validate the BIA equations assessing the agreement between BIA- and DXA-derived soft tissue estimation
STUDY PARAMETERS
-Anthropometry anthropometric parameters should have been measured in accordance with validated and standardized methodologies
The anthropometric parameters of interest are body mass stature waist circumference calf circumference arm circumference and triceps skinfold thickness limb length
-Dual energy X-ray absorptiometry all participants should have been scanned using a fan beam whole body DXA device Hologic Bedford Massachusetts USA Lunar Prodigy GE Healthcare Daily calibration of the densitometers should have been performed following the instructions provided by the manufacturer
Since measurements vary among instruments from different manufacturers calibration equations will be used to address these issues and improve the agreement between devices
The body components of interest are total fat mass FM total lean mass LM ALM sum of the lean mass in the limbs FM sum of the fat mass in the limbs and the ratio of ALM to FM
-Bioelectrical impedance analysis After overnight fasting and bladder voiding bioelectrical impedance analysis should have been performed with participants lying supine with their limbs slightly away from their body active electrodes should have been placed on the right side on conventional metacarpal and metatarsal lines recording electrodes in standard positions at the right wrist and ankle or in vertical position barefoot stepping onto the electrodes embedded into the scale and grasping the electrode-embedded handles At each location a whole-body tetrapolar BIA device operating at a weak alternating electrical current of 500 µA to 1 mA and a single frequency of 50 kHz should have been used to measure the voltage drop across body tissues
The electric parameters of interest are resistance R restriction of current flow reactance Xc capacitance of cell membranes and tissue interfaces and phase angle PhA
The information about BIA devices will be recorded since raw R and Xc values may not be not comparable
Due to the significant differences found in different studies when comparing vertical to supine position the results obtained with the two methodologies will be analysed separately
With reference to the limitation reported by the PROVIDE study authors ie the absence of a direct measurement of extracellular water the raw data detected through multifrequency bioimpedance devices will also be used where available Specifically the values of impedance and resistance measured at a frequency of 5 kHz will be included furthermore where available it would be optimal to analyze data measured at the following frequencies 1 2 5 10 50 100 200 250 and 500 kHz
STATISTICS
Data will be analyzed by using IBM SPSS Statistics version 25 The data will be presented as frequency percent and mean SD for qualitative and quantitative variables respectively The Shapiro-Wilk test will be used to evaluate if the data are normally distributed Comparison of continuous variables will be performed using parametric or non-parametric tests depending on whether the distribution is normal or not The chi-square test will be used to check whether the frequencies occurring in the sample differ significantly from the expected frequencies The cut-off for statistical significance will be set at p005
Preliminary equations using DXA-derived appendicular lean and fat mass as the dependent variables and age gender BMI weight impedance index and reactance as independent variables will be developed using a stepwise multiple linear regression approach Only significant regressors of appendicular soft tissue masses will be considered in the equations
Model performance fit will be assessed using multiple correlations R2 and standard errors of the estimate SEE For each of the appendicular soft tissue components the model with the lowest standard error of the estimate will be used in the cross-validation analysis
The individual and body composition data from the cross-validation samples will be imputed into the developed equations to assess their accuracy The statistics for cross-validation includes mean difference limits of agreement and root mean squared error
Additionally the agreement between ALM_BIA estimated in our sample ALM_SERGI ALM_Provide and ALM_KYLE will be assessed using regression analysis
Finally the agreement between the ALMFM-ratios estimated by DXA and by BIA will be evaluated using Bland and Altman analysis
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None