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

Metabolic Determinants Of Resting Energy Expenditure Among Mechanically Ventilated Critically Ill Patients In Malaysian Tertiary Hospital

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.

Study Overview

• Status: Unknown
• Conditions: Critical Illness
• Intervention / Treatment: Device: Indirect Calorimetry

Detailed 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.

• Study Type: Observational
• Enrollment (Anticipated): 314

Contacts and Locations

Study Locations

• Malaysia
  • Wilayah Persekutuan
    • Kuala Lumpur, Wilayah Persekutuan, Malaysia, 59100
      • Recruiting
      • University of Malaya Medical Centre
      • Contact: Pei Chien Tah; Phone Number: 0163091880; Email: pctah@ummc.edu.my
      • Sub-Investigator: Mohd Shahnaz Bin Hasan
      • Sub-Investigator: Vineya Rai Hakumat Rai
      • Sub-Investigator: Bee Koon Poh
      • Sub-Investigator: Mohd Basri Bin Mat Nor
      • Sub-Investigator: Hazreen Bin Abdul Majid
      • Sub-Investigator: Chee Cheong Kee
      • Sub-Investigator: Mazuin Kamarul Zaman

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Critically ill patients with mechanically ventilated

Description

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

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

critically ill adult patients; 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

Device: Indirect Calorimetry; REE measurements were using IC (Cosmed, Quark RMR 2.0, Indirect Calorimetry Lab, Italy). A standard protocol for conducting the measurement was followed (Schlein & Coulter, 2014);(P. Singer & Singer, 2016); (Taku Oshima et al., 2016). Before each measurement, the metabolic monitor was allowed to warm up for 30 min, and then gas and flowmeter calibrations were performed by an experienced dietitian or healthcare professional. The REE was recorded after a 30 min non-fasting steady state according to RMR protocol and manufacturer instructions.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of participants measured resting energy expenditure for the development of predictive equations	predictive equations for the estimation of energy requirement among mechanically ventilated critically ill patients among Malaysian population.	24 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The validity of several predictive equations by using Intraclass Correlation Coefficient (ICC) test	predictive equations used to predict REE in critically ill adult patients among Malaysian population by using indirect calorimetry (IC) as the reference standard.	24 months
Determine metabolic determinants	metabolic determinants that might influence resting energy expenditure among mechanically ventilated critically ill patients.	24 months
The best regression equation model	Regression equation model for predicting energy requirement of mechanically ventilated critically ill patients.	24 months
Determine and compare REE measured by IC among mechanically ventilated critically ill patients	during early phase (staying ≤ 5 days), late phase (staying 6-10 days) and chronic phase (staying > 10 days) in ICU.	24 months
The association of REE in critically ill patients with clinical outcome	Clinical outcome are hospital mortality and ICU mortality in 28 days and 60 days, length of mechanical ventilation in hours, duration of ICU stay in days and infectious complications such as Hospital acquired infection.	24 months
The association of REE in critically ill patients with quality of life	Questionnaire SF-36v2 Health Survey to measure quality of life for critically ill patients.	24 months
The association of REE in critically ill patients with nutrition risk	NUTRIC score to quantify the nutrition risk of critically ill patients developing adverse events	24 months
The energy and protein adequacy in relation to patient outcome.	Energy and protein adequacy in terms of Energy/Nitrogen ratio in relation to patient outcome.	24 months

Collaborators and Investigators

• Sponsor: University of Malaya
• Investigators: Principal Investigator: Pei Chien Tah, University of Malaya Medical Centre

Publications and helpful links

General Publications

• Tah PC, Poh BK, Kee CC, Lee ZY, Hakumat-Rai VR, Mat Nor MB, Kamarul Zaman M, Majid HA, Hasan MS. Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements. Eur J Clin Nutr. 2022 Apr;76(4):527-534. doi: 10.1038/s41430-021-00999-y. Epub 2021 Aug 30. Erratum In: Eur J Clin Nutr. 2021 Oct 25;:

Study record dates

Study Major Dates

• Study Start (ACTUAL): February 13, 2017
• Primary Completion (ANTICIPATED): December 31, 2020
• Study Completion (ANTICIPATED): December 31, 2022

Study Registration Dates

• First Submitted: September 23, 2017
• First Submitted That Met QC Criteria: October 22, 2017
• First Posted (ACTUAL): October 24, 2017

Study Record Updates

• Last Update Posted (ACTUAL): October 24, 2017
• Last Update Submitted That Met QC Criteria: October 22, 2017
• Last Verified: October 1, 2017

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Disease Attributes; Critical Illness
• Other Study ID Numbers: 20161024-4407

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No