ClinicalTrials.Veeva

Menu

Metabolic Determinants Of Resting Energy Expenditure Among Mechanically Ventilated Critically Ill Patients

U

University of Malaya

Status

Unknown

Conditions

Critical Illness

Treatments

Device: Indirect Calorimetry

Study type

Observational

Funder types

Other

Identifiers

NCT03319329
20161024-4407

Details and patient eligibility

About

Currently there are no study related to Indirect Calorimetry (IC) has been done among hospitalised Malaysian ICU adult patients with its racial mix. The aim of this study is to perform a cross-sectional study in Malaysian critically ill patients to determine metabolic determinants that might influence resting energy expenditure (REE) and to develop predictive equation for the estimation of energy requirement using the regression based approach to increase the accuracy in calorie prescriptions. In addition, expected outcome of this study is to determine which equations have clinical usefulness among Malaysian adult critically ill patients and hope to introduce into routine clinical practice in the future if IC is not available.

Full description

Nutrition provision in the clinical setting relies heavily on the accurate estimation of energy and protein requirements. This can be done in a quick and inexpensive manner via the use of predictive equations. Some of the most popularly used predictive equations such as the Harris-Benedict equation and the Mifflin-St. Jeor equation have been widely applied within the clinical setting to estimate energy requirements among mechanically ventilated critically ill patients. However, these existing equations were not specially developed for a population with disease, as the equations were derived from a pool of healthy Caucasian adults. In addition, most of the equations for critically ill patients such as the Penn State equation, Faisy equation and Raurich Equation developed and validated among Caucasian in western country and not among Asian population. Therefore, their accuracy in predicting energy requirement is questionable when applied within Malaysian mechanically ventilated critically ill patients with its racial mix.

Enrollment

314 estimated patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  1. Adult patients aged over 18 years old
  2. Critically ill patients with mechanically ventilated
  3. Expected to have an ICU stay of more than 5 days
  4. Patients had implemented for continuous enteral or parenteral nutrition support.

Exclusion criteria

  1. Requirement for inspired oxygen content (FiO2) greater than 0.6
  2. Patients on high frequency ventilation
  3. Patients with chest tubes that leak air
  4. Patients with incompetent tracheal cuff
  5. Patients inhaled nitric oxide therapy
  6. Patients receiving intermittent hemodialysis and continuous renal replacement therapy (CRRT) during IC measurement
  7. Patients with pregnancy
  8. Patients with burn injury
  9. Patients infected with human immunodeficiency virus (HIV)
  10. Patients with severe liver disease (Child-Pugh score C)
  11. Patients with post open heart surgery
  12. Patients with paraplegia and quadriplegia

Trial design

314 participants in 1 patient group

critically ill adult patients
Description:
Part I: A cross-sectional study to compare validity of several predictive equations used to predict REE in critically ill adult patients for staying ≤ 5 days, 6 - 10 days and \> 10 days by using indirect calorimetry (IC) as the reference standard. Part II: To develop predictive equation for the estimation of energy requirement by identifying variables that might influence REE of mechanically ventilated critically ill patients. Part III: To validate the newly developed predictive equation for the estimation of energy requirement by using Ten fold cross-validation approach
Treatment:
Device: Indirect Calorimetry

Trial contacts and locations

1

Loading...

Central trial contact

Pei Chien Tah; Pei Chien Tah

Data sourced from clinicaltrials.gov

Clinical trials

Find clinical trialsTrials by location
© Copyright 2026 Veeva Systems