Using Indirect Calorimetry for Liver Transplants Patients

NCT03622268 | Completed

• 1 other identifier: AsanMC-LTindirectKcal
• Study Type: observational
• Target: 50
• Locations: 1 country
• Sites: 1

Brief Summary

Although predicted REE calculated using the Penn state 1988 method agreed (ICC 0.61, p=0.00014) with the measured REE, all three predictive equations had a fixed bias and appeared to be inaccurate for predicting REE for liver transplant recipients. Therefore, precise measurements using indirect calorimetry may be helpful when treating critically ill patients to avoid underestimating or overestimating their metabolic needs.

Conditions

Indirect Calorimetry

Keywords

indirect calorimetry; energy expenditure assessment; intensive care unit

Outcome Measures

Primary Outcomes (1)

• Comparing REE with the measurement for each predictive equation and indirect calorimetry

  The REEs derived from each predictive equation were compared with the measured REE using an intraclass correlation coefficient (ICC) and a Bland-Altman plot.

  1 year

Study Arms (1)

Indirect calorimetry measurement

Using indirect calorimetry for measure resting energy expenditure

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients who had received liver transplants

You may qualify if:

• mechanically ventilated patients who had received liver transplants and were expected to stay in the ICU more than 2 days were studied.

You may not qualify if:

• Refusal
• patients who were extubated before 36 hrs

Sponsors & Collaborators

• Asan Medical Center: lead

Study Sites (1)

Hakjae Lee

Seoul, South Korea

Location

Related Publications (4)

• McClave SA, Martindale RG, Kiraly L. The use of indirect calorimetry in the intensive care unit. Curr Opin Clin Nutr Metab Care. 2013 Mar;16(2):202-8. doi: 10.1097/MCO.0b013e32835dbc54.

  PMID: 23340008 RESULT

• Sundstrom M, Tjader I, Rooyackers O, Wernerman J. Indirect calorimetry in mechanically ventilated patients. A systematic comparison of three instruments. Clin Nutr. 2013 Feb;32(1):118-21. doi: 10.1016/j.clnu.2012.06.004. Epub 2012 Jul 3.

  PMID: 22763268 RESULT

• Kross EK, Sena M, Schmidt K, Stapleton RD. A comparison of predictive equations of energy expenditure and measured energy expenditure in critically ill patients. J Crit Care. 2012 Jun;27(3):321.e5-12. doi: 10.1016/j.jcrc.2011.07.084. Epub 2012 Mar 14.

  PMID: 22425340 RESULT

• Xiao GZ, Su L, Duan PK, Wang QX, Huang Y. [Comparison of measuring energy expenditure with indirect calorimetry and traditional estimation of energy expenditure in patients in intensive care unit]. Zhongguo Wei Zhong Bing Ji Jiu Yi Xue. 2011 Jul;23(7):392-5. Chinese.

  PMID: 21787465 RESULT

Study Officials

• Suk-kyung Hong, Ph.D.

  Asan Medical Center

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate professor

Study Record Dates

• First Submitted: August 3, 2018
• First Posted: August 9, 2018
• Study Start: December 1, 2017
• Primary Completion: May 1, 2018
• Study Completion: August 1, 2018
• Last Updated: August 9, 2018

Record last verified: 2018-08

Data Sharing

• IPD Sharing: Will not share

Locations

KR (1)