An observational study in Critical Illness, sponsored by University of Malaya. Status unknown at 1 site in Malaysia. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2017-10-24.
Sponsored by University of Malaya · Observational
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.
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.
1,780 studies on the registry are indexed under Critical Illness; 442 are open to participants now.
This study's planned enrollment of 314 is above the median of 140 across 814 observational studies indexed under Critical Illness.
Browse Critical Illness studies →University of Malaya is the lead sponsor of 284 studies on the registry; 58 are open to participants now.
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Critically ill patients with mechanically ventilated
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Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
The human immunodeficiency virus, which weakens the immune system.
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A score of how well the liver works in people with liver disease such as cirrhosis: class A is mild, B moderate and C severe.
HIV
The human immunodeficiency virus, which weakens the immune system.
Many studies now accept people whose HIV is controlled on treatment, judged by the viral load and the CD4 count. Check the limits this study sets.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Child-Pugh class
A score of how well the liver works in people with liver disease such as cirrhosis: class A is mild, B moderate and C severe.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
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.
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.
Time frame: 24 months
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.
Time frame: 24 months
Determine metabolic determinants
metabolic determinants that might influence resting energy expenditure among mechanically ventilated critically ill patients.
Time frame: 24 months
The best regression equation model
Regression equation model for predicting energy requirement of mechanically ventilated critically ill patients.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 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
Time frame: 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.
Time frame: 24 months
Started Feb 2017 (actual). Primary completion is estimated for Dec 2020, 46 months after the start.
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