Publication:
Determining the best predictive equation for resting energy expenditure among mechanically ventilated critically ill patients in a Malaysian tertiary hospital

dc.contributor.affiliation#PLACEHOLDER_PARENT_METADATA_VALUE#en_US
dc.contributor.authorKhairul Anam Mansoren_US
dc.contributor.supervisorMohd Basri Mat Nor, Ph.Den_US
dc.contributor.supervisorAzrina MD Ralib, Ph.Den_US
dc.contributor.supervisorMohd Nizamuddin Ismail, Ph.Den_US
dc.date.accessioned2024-10-09T04:37:41Z
dc.date.available2024-10-09T04:37:41Z
dc.date.issued2020
dc.description.abstractIntroduction: Measurement of resting energy expenditure using indirect calorimetry in intensive care unit patient is the gold standard as recommended by guidelines. Unfortunately, technical difficulties and high cost prevent its widespread adoption by medical facilities. Predictive equations are largely used instead. We aim to validate commonly used predictive equation at different period of acute phase of critical illness. Methods: Patients hospitalized from November 2019-August 2020 in a general ICU of Sultan Ahmad Shah Medical Center, a university affiliated, tertiary care hospital who had been ventilated with GE Carescape R860 to assess caloric targets were included. Measurement was done up to 3 times per day from day 1 of ICU admission to day 7 of ICU admission. Equation performance was assessed by comparing means, standard deviations, correlation, concordance and agreement, which was defined as a measurement within 90-110% of measured REE by indirect calorimetry. A total of 18 equations was evaluated. Results: A total of 49 patients were recruited. Mean patient age was 63 years, 63.6% were male and 90.9% were Malay ethnic. Medical admission comprises of 69.7% of patients category. The mean of REE as measured by IC was 1176±332 kcal during early acute phase and 1222±321 kcal during late acute phase. There was no significant difference of REE during the two acute phases of critical illness. During acute phase, the Mifflin-St. Jeor have the highest accuracy (33.33%) but no agreement. In the late acute phase, WHO predictive equation shows the highest accuracy but poor agreement with IC. The Mifflin-St. Jeor equation demonstrates the second highest accuracy and moderate agreement with IC. None of the predictive equations have level of accuracy of more than 50% across both phases. Lack of sample size due to COVID-19 pandemic and technical issues affect the overall result of this study. Conclusions: From this study, no predictive equation can be recommended during the early acute phase of critical illness. The Mifflin-St. Jeor can be recommended to be used in late acute phase of critically ill patients. This predictive equation include static variables of height, weight and age. Incorporation of dynamic variables such as maximum temperature, minute ventilation does not increase the accuracy of predictive equation such as Faisy and Ireton-Jones. Recommendations cannot be concluded due to lack of sample size.en_US
dc.description.callnumbert RC 86.7 K45D 2020
dc.description.identifierThesis : Determining the best predictive equation for resting energy expenditure among mechanically ventilated critically ill patients in a Malaysian tertiary hospitalen_US
dc.description.identityt11100436576KhairulAnamBinMansoren_US
dc.description.kulliyahKulliyyah of Medicineen_US
dc.description.nationalityMalaysianen_US
dc.description.notesThesis (MMA)--International Islamic University Malaysia, 2020.en_US
dc.description.physicaldescriptionxi, 60 leaves : illustrations ; 30cm.en_US
dc.description.programmeMaster of Medicine (Anaesthesiologyen_US
dc.identifier.urihttps://studentrepo.iium.edu.my/handle/123456789/10890
dc.language.isoenen_US
dc.publisherKuantan, Pahang : Kulliyyah of Medicine, International Islamic University Malaysia, 2020en_US
dc.subject.lcshCritical Care
dc.subject.lcshIndirect Calorimetry
dc.titleDetermining the best predictive equation for resting energy expenditure among mechanically ventilated critically ill patients in a Malaysian tertiary hospitalen_US
dc.typeMaster Thesisen_US
dspace.entity.typePublication

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