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Validation of Bedside Ultrasound to Predict Body Composition in Non- and Critically Ill Patients (USVALID)

Primary Purpose

Ultrasound, Body Composition

Status
Unknown status
Phase
Not Applicable
Locations
Austria
Study Type
Interventional
Intervention
Body Composition Measurements
Sponsored by
Medical University of Vienna
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Ultrasound focused on measuring reliability, bioelectrical impedance analysis, computed tomography, strength, mobility

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria:

  • cross-sectional abdominal CT scan including the level of L3 vertebra for any clinical reason
  • study-related ultrasound examination must take place within 48 hours of CT

Exclusion Criteria:

  • patients younger than 18 years

Sites / Locations

  • Medical University of Vienna

Arms of the Study

Arm 1

Arm Type

Other

Arm Label

Body Composition Measurements

Arm Description

Body composition measurements comprise the ultrasound measurement of fat and muscle thickness of both upper arms and thighs, the bioelectrical impedance analysis (BIA), measurement of weight, handgrip strength, overall muscle strength (Medical Research Council scale) and questionnaires about physical activity, nutrition and fluid status.

Outcomes

Primary Outcome Measures

prediction (r2) of CT-based whole body muscle volume from ultrasound-based muscle thickness
In a linear regression model, the dependent variable is CT-based whole body muscle volume. The independent variable is ultrasound-based muscle thickness. The prediction (r2) of CT-based muscle volume in the multiple linear regression model is the outcome.
prediction (r2) of CT-based whole body fat volume from ultrasound-based fat thickness
In a linear regression model, the dependent variable is CT-based whole body fat volume. The independent variable is ultrasound-based fat thickness. The prediction (r2) of CT-based fat volume in the multiple linear regression model is the outcome.

Secondary Outcome Measures

prediction (r2) of BIA-based whole body muscle volume from ultrasound-based muscle thickness
In a linear regression model, the dependent variable is BIA-based whole body muscle volume. The independent variable is ultrasound-based muscle thickness. The prediction (r2) of BIA-based muscle volume in the multiple linear regression model is the outcome.
prediction (r2) of BIA-based whole body fat volume from ultrasound-based fat thickness
In a linear regression model, the dependent variable is BIA-based whole body fat volume. The independent variable is ultrasound-based fat thickness. The prediction (r2) of BIA-based fat volume in the multiple linear regression model is the outcome.
intrarater reliability (bias in Bland Altman analysis) of ultrasound muscle/fat thickness
For intrarater reliability each of the 5 examiners repeats the ultrasound measurement in 12 patients. In a Bland Altman analysis, the mean difference (=bias) in muscle/fat thickness between repeated measurements of the same examiner is the outcome.
interrater reliability (bias in Bland Altman analysis) of ultrasound muscle/fat thickness
For interrater reliability each of the 10 different pairs of examiners analyzes 6 patients. For each pair both examiners perform the ultrasound examination. In a Bland Altman analysis, the mean difference (=bias) in ultrasound muscle/fat thickness between examiners is the outcome.
muscle strength in patients with different CT-based body compositions (sarcopenia, malnutrition, obesity, sarcopenic obesity)
Muscle strength is measured with MRC scale and hand dynamometry. The outcome is muscle strength evaluated in different patient's group according to their CT-based body composition. Sarcopenia is defined as lowered L3 skeletal muscle index. Malnutrition is defined at a BMI beneath18,5 kg/m². Obesity is defined as a BMI above or equal to 30 kg/m². Sarcopenia obesity is defined as lowered L3 skeletal muscle indices and a BMI above or equal to 30 kg/m2.

Full Information

First Posted
December 30, 2016
Last Updated
August 28, 2019
Sponsor
Medical University of Vienna
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1. Study Identification

Unique Protocol Identification Number
NCT03160222
Brief Title
Validation of Bedside Ultrasound to Predict Body Composition in Non- and Critically Ill Patients
Acronym
USVALID
Official Title
Validation of Bedside Ultrasound to Predict Body Composition in Non- and Critically Ill Patients: The USVALID Prospective Study
Study Type
Interventional

2. Study Status

Record Verification Date
August 2019
Overall Recruitment Status
Unknown status
Study Start Date
January 2017 (undefined)
Primary Completion Date
March 22, 2019 (Actual)
Study Completion Date
September 2019 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Medical University of Vienna

4. Oversight

Data Monitoring Committee
No

5. Study Description

Brief Summary
The prospective study will include 200 patients and 50 critically ill patients, who had an abdominal computed tomography (CT) scan including the L3 level for any clinical reason. Ultrasound scans of the anterior thighs and forearms will be taken after the CT scan within 48 hours. Bioelectrical impedance analysis (BIA) will also be performed. In addition muscle strength, mobility, physical function and nutrition will be assessed. Primary outcome is the prediction of CT-based whole body muscle and fat volume and BIA-based fat and lean body mass from ultrasound-based muscle and fat thickness. Other secondary outcomes include the intra- and interrater reliability of the CT evaluation and ultrasound examination of muscle and fat mass. The relationship between clinical aspects (strength, mobility, physical function, nutrition) and whole body composition is another secondary outcome.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Ultrasound, Body Composition
Keywords
reliability, bioelectrical impedance analysis, computed tomography, strength, mobility

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
250 (Actual)

8. Arms, Groups, and Interventions

Arm Title
Body Composition Measurements
Arm Type
Other
Arm Description
Body composition measurements comprise the ultrasound measurement of fat and muscle thickness of both upper arms and thighs, the bioelectrical impedance analysis (BIA), measurement of weight, handgrip strength, overall muscle strength (Medical Research Council scale) and questionnaires about physical activity, nutrition and fluid status.
Intervention Type
Other
Intervention Name(s)
Body Composition Measurements
Intervention Description
Body composition measurements comprise the ultrasound measurement of fat and muscle thickness of both upper arms and thighs, the bioelectrical impedance analysis (BIA), measurement of weight, handgrip strength, overall muscle strength (Medical Research Council scale) and questionnaires about physical activity, nutrition and fluid status.
Primary Outcome Measure Information:
Title
prediction (r2) of CT-based whole body muscle volume from ultrasound-based muscle thickness
Description
In a linear regression model, the dependent variable is CT-based whole body muscle volume. The independent variable is ultrasound-based muscle thickness. The prediction (r2) of CT-based muscle volume in the multiple linear regression model is the outcome.
Time Frame
Ultrasound measurement once-only within 48 hours after the CT scan
Title
prediction (r2) of CT-based whole body fat volume from ultrasound-based fat thickness
Description
In a linear regression model, the dependent variable is CT-based whole body fat volume. The independent variable is ultrasound-based fat thickness. The prediction (r2) of CT-based fat volume in the multiple linear regression model is the outcome.
Time Frame
Ultrasound measurement once-only within 48 hours after the CT scan
Secondary Outcome Measure Information:
Title
prediction (r2) of BIA-based whole body muscle volume from ultrasound-based muscle thickness
Description
In a linear regression model, the dependent variable is BIA-based whole body muscle volume. The independent variable is ultrasound-based muscle thickness. The prediction (r2) of BIA-based muscle volume in the multiple linear regression model is the outcome.
Time Frame
BIA measurement once-only within 48 hours after the CT scan
Title
prediction (r2) of BIA-based whole body fat volume from ultrasound-based fat thickness
Description
In a linear regression model, the dependent variable is BIA-based whole body fat volume. The independent variable is ultrasound-based fat thickness. The prediction (r2) of BIA-based fat volume in the multiple linear regression model is the outcome.
Time Frame
BIA measurement once-only within 48 hours after the CT scan
Title
intrarater reliability (bias in Bland Altman analysis) of ultrasound muscle/fat thickness
Description
For intrarater reliability each of the 5 examiners repeats the ultrasound measurement in 12 patients. In a Bland Altman analysis, the mean difference (=bias) in muscle/fat thickness between repeated measurements of the same examiner is the outcome.
Time Frame
repeated US measurement in 60 patients once-only within 48 hours after the CT scan
Title
interrater reliability (bias in Bland Altman analysis) of ultrasound muscle/fat thickness
Description
For interrater reliability each of the 10 different pairs of examiners analyzes 6 patients. For each pair both examiners perform the ultrasound examination. In a Bland Altman analysis, the mean difference (=bias) in ultrasound muscle/fat thickness between examiners is the outcome.
Time Frame
repeated US measurement in 60 patients once-only within 48 hours after the CT scan
Title
muscle strength in patients with different CT-based body compositions (sarcopenia, malnutrition, obesity, sarcopenic obesity)
Description
Muscle strength is measured with MRC scale and hand dynamometry. The outcome is muscle strength evaluated in different patient's group according to their CT-based body composition. Sarcopenia is defined as lowered L3 skeletal muscle index. Malnutrition is defined at a BMI beneath18,5 kg/m². Obesity is defined as a BMI above or equal to 30 kg/m². Sarcopenia obesity is defined as lowered L3 skeletal muscle indices and a BMI above or equal to 30 kg/m2.
Time Frame
muscle strength measurement once-only within 48 hours after the CT scan

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria: cross-sectional abdominal CT scan including the level of L3 vertebra for any clinical reason study-related ultrasound examination must take place within 48 hours of CT Exclusion Criteria: patients younger than 18 years
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Arabella Fischer, Dr.
Organizational Affiliation
Medical University of Vienna
Official's Role
Principal Investigator
First Name & Middle Initial & Last Name & Degree
Michael Hiesmayr, Prof. Dr.
Organizational Affiliation
Medical University of Vienna
Official's Role
Study Director
Facility Information:
Facility Name
Medical University of Vienna
City
Vienna
ZIP/Postal Code
1180
Country
Austria

12. IPD Sharing Statement

Plan to Share IPD
No
Citations:
PubMed Identifier
15277145
Citation
Shen W, Punyanitya M, Wang Z, Gallagher D, St-Onge MP, Albu J, Heymsfield SB, Heshka S. Visceral adipose tissue: relations between single-slice areas and total volume. Am J Clin Nutr. 2004 Aug;80(2):271-8. doi: 10.1093/ajcn/80.2.271.
Results Reference
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PubMed Identifier
16235068
Citation
Sanada K, Kearns CF, Midorikawa T, Abe T. Prediction and validation of total and regional skeletal muscle mass by ultrasound in Japanese adults. Eur J Appl Physiol. 2006 Jan;96(1):24-31. doi: 10.1007/s00421-005-0061-0. Epub 2005 Oct 19.
Results Reference
background
PubMed Identifier
24410863
Citation
Weijs PJ, Looijaard WG, Dekker IM, Stapel SN, Girbes AR, Oudemans-van Straaten HM, Beishuizen A. Low skeletal muscle area is a risk factor for mortality in mechanically ventilated critically ill patients. Crit Care. 2014 Jan 13;18(2):R12. doi: 10.1186/cc13189.
Results Reference
background
PubMed Identifier
26962061
Citation
Paris MT, Mourtzakis M, Day A, Leung R, Watharkar S, Kozar R, Earthman C, Kuchnia A, Dhaliwal R, Moisey L, Compher C, Martin N, Nicolo M, White T, Roosevelt H, Peterson S, Heyland DK. Validation of Bedside Ultrasound of Muscle Layer Thickness of the Quadriceps in the Critically Ill Patient (VALIDUM Study). JPEN J Parenter Enteral Nutr. 2017 Feb;41(2):171-180. doi: 10.1177/0148607116637852. Epub 2016 Jul 11.
Results Reference
background
PubMed Identifier
25239112
Citation
Prado CM, Heymsfield SB. Lean tissue imaging: a new era for nutritional assessment and intervention. JPEN J Parenter Enteral Nutr. 2014 Nov;38(8):940-53. doi: 10.1177/0148607114550189. Epub 2014 Sep 19. Erratum In: JPEN J Parenter Enteral Nutr. 2016 Jul;40(5):742.
Results Reference
background
PubMed Identifier
24950147
Citation
Takai Y, Ohta M, Akagi R, Kato E, Wakahara T, Kawakami Y, Fukunaga T, Kanehisa H. Applicability of ultrasound muscle thickness measurements for predicting fat-free mass in elderly population. J Nutr Health Aging. 2014;18(6):579-85. doi: 10.1007/s12603-013-0419-7.
Results Reference
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Validation of Bedside Ultrasound to Predict Body Composition in Non- and Critically Ill Patients

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