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Predicting Resting Energy Expenditure in Critically Ill Patients by Measuring Lean Body Mass by US

The Novel Use of Point of Care Ultrasound to Predict Resting Energy Expenditure in Critically Ill Patients by Measuring Lean Body Mass Using Musculo-skeletal Ultrasound

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03193632
Enrollment
40
Registered
2017-06-21
Start date
2017-07-01
Completion date
2018-08-01
Last updated
2018-10-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Resting Energy Expenditure

Keywords

lean body mass, resting energy expenditure, oxygen consumption, Indirect calorimetry, carbon dioxide excretion, respiratory quotient

Brief summary

The study aims to correlate Lean Body Mass (LBM) Evaluated by Musculoskeletal Ultrasound with Resting Energy Expenditure (REE) measured by Indirect Calorimetry and to generate a predictive equation of REE based on LBM, in addition to identifying other factors that may affect REE such as age, gender, and severity scores.

Detailed description

Caloric needs in critically-ill patients fluctuate significantly over the course of the disease which might expose patients to either malnutrition or overfeeding.Malnutrition is associated with deterioration of lean body mass (LBM), poor wound healing, increased risk of nosocomial infection, and weakened respiratory muscles. On the other hand overfeeding in medically compromised patients can promote lipogenesis, hyperglycemia, and exacerbation of respiratory failure. Many factors may affect the resting energy expenditure (REE) through manipulation of oxygen consumption (VO2). One of the strongest determinants of REE is the LBM. A measurement of muscle mass and changes in muscle mass could thus provide an index of LBM in critically ill patients. At present, computerized tomography, magnetic resonance imaging and dual-energy X-ray absorptiometry (DXA) are widely used as reference methods for evaluating LBM in vivo. However, these methods are impractical in critically ill patients. More practically, ultrasound scanning is a simple, portable, safe, and a low-patient burden technique. Several studies found that the use of ultrasound can be a good estimate to LBM. Indirect calorimetry remains the accepted standard for determining the REE in the critically ill. Indirect calorimetry measures oxygen consumption(VO2) and carbon dioxide excretion (VCO2 ) (both in mL/min), which are used to calculate the respiratory quotient and the resting energy expenditure. Although, the measured LBM has been shown as an important determinant of REE, there was no previous study tested the relationship between estimated LBM by ultrasound-based muscle thickness measurement and REE.

Interventions

DIAGNOSTIC_TESTUS Muscle layer thickness (MLT) estimation

Three measurements will be made at each of three sites; mid-upper arm, forearm and thigh anteriorly and the mean value will be calculated. Measurement sites will be marked with indelible ink to ensure day-to-day consistency. 1. Thigh: MLT of the quadriceps femoris muscle (M. Vastus intermedius and M. rectus femoris) will be assessed bilaterally 2. Mid-upper arm: Muscle layer thickness will be measured over the biceps,midway between the tip of the acromion and the tip of the olecranon 3. Forearm: A point midway between the antecubital skin crease and the ulnar styloid was marked and muscle thickness down to the interosseus membrane

DIAGNOSTIC_TESTREE estimation by indirect calorimetry

REE will be calculated using indirect calorimetry via metabolic module on General Electric ventilator (Engstrom Carestation and Carescape R860, GE Health care, USA) All indirect calorimetric measurements will be done using standardized technique. Gas calibration will be performed before each measurement, and the measurements will last for at least 30 minutes. Measurements will be taken with the patient lying supine and ventilator settings left unchanged for at least 60 minutes ahead of indirect calorimetry. The REE will be calculated during the first 24 hours of admission to ICU.

Sponsors

Eslam Ayman Mohamed Shawki
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

\- Patient requiring ventilatory support \> 24 hours

Exclusion criteria

* Patient who will require FIO2 more than 0.6. * Air leak from the chest tube. * Patient with body temperature \> 39oC. * Patients with known endocrine dysfunction. * Patients on parenteral nutrition

Design outcomes

Primary

MeasureTime frameDescription
correlation between LBM derived from ultrasound MLT and REE by indirect calorimetry24 hours of ICU admissionThe correlation of the LBM derived from ultrasound MLT to the REE measured within 24 hours of ICU admission with indirect calorimetry

Secondary

MeasureTime frameDescription
Predictive equation for REE based on US measurement of MLT24 hours of ICU admissiongeneration of predictive equation of REE based on ultrasound measurement of MLT
Estimation of the effect of severity scores on the REE24 hours of ICU admissionEstimation of the effect of severity scores on the REE

Countries

Egypt

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026