Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements
Background Predictive equations (PEs) for estimating resting energy expenditure (REE) that have been developed from acute phase data may not be applicable in the late phase and vice versa. This study aimed to assess whether separate PEs are needed for acute and late phases of critical illness and to...
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my.um.eprints.424322024-11-09T03:42:30Z http://eprints.um.edu.my/42432/ Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements Tah, Pei Chien Poh, Bee Koon Kee, Chee Cheong Lee, Zheng-Yii Hakumat-Rai, Vineya-Rai Nor, Mohd Basri Mat Zaman, Mazuin Kamarul Majid, Hazreen Abdu Hasan, M. Shahnaz R Medicine RA Public aspects of medicine Background Predictive equations (PEs) for estimating resting energy expenditure (REE) that have been developed from acute phase data may not be applicable in the late phase and vice versa. This study aimed to assess whether separate PEs are needed for acute and late phases of critical illness and to develop and validate PE(s) based on the results of this assessment. Methods Using indirect calorimetry, REE was measured at acute (<= 5 days; n = 294) and late (>= 6 days; n = 180) phases of intensive care unit admission. PEs were developed by multiple linear regression. A multi-fold cross-validation approach was used to validate the PEs. The best PEs were selected based on the highest coefficient of determination (R-2), the lowest root mean square error (RMSE) and the lowest standard error of estimate (SEE). Two PEs developed from paired 168-patient data were compared with measured REE using mean absolute percentage difference. Results Mean absolute percentage difference between predicted and measured REE was <20%, which is not clinically significant. Thus, a single PE was developed and validated from data of the larger sample size measured in the acute phase. The best PE for REE (kcal/day) was 891.6(Height) + 9.0(Weight) + 39.7(Minute Ventilation)-5.6(Age) - 354, with R-2 = 0.442, RMSE = 348.3, SEE = 325.6 and mean absolute percentage difference with measured REE was: 15.1 +/- 14.2% acute], 15.0 +/- 13.1% late]. Conclusions Separate PEs for acute and late phases may not be necessary. Thus, we have developed and validated a PE from acute phase data and demonstrated that it can provide optimal estimates of REE for patients in both acute and late phases. Springernature 2022-04 Article PeerReviewed Tah, Pei Chien and Poh, Bee Koon and Kee, Chee Cheong and Lee, Zheng-Yii and Hakumat-Rai, Vineya-Rai and Nor, Mohd Basri Mat and Zaman, Mazuin Kamarul and Majid, Hazreen Abdu and Hasan, M. Shahnaz (2022) Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements. European Journal Of Clinical Nutrition, 76 (4). pp. 527-534. ISSN 0954-3007, DOI https://doi.org/10.1038/s41430-021-00999-y <https://doi.org/10.1038/s41430-021-00999-y>. 10.1038/s41430-021-00999-y |
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R Medicine RA Public aspects of medicine Tah, Pei Chien Poh, Bee Koon Kee, Chee Cheong Lee, Zheng-Yii Hakumat-Rai, Vineya-Rai Nor, Mohd Basri Mat Zaman, Mazuin Kamarul Majid, Hazreen Abdu Hasan, M. Shahnaz Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements |
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Background Predictive equations (PEs) for estimating resting energy expenditure (REE) that have been developed from acute phase data may not be applicable in the late phase and vice versa. This study aimed to assess whether separate PEs are needed for acute and late phases of critical illness and to develop and validate PE(s) based on the results of this assessment. Methods Using indirect calorimetry, REE was measured at acute (<= 5 days; n = 294) and late (>= 6 days; n = 180) phases of intensive care unit admission. PEs were developed by multiple linear regression. A multi-fold cross-validation approach was used to validate the PEs. The best PEs were selected based on the highest coefficient of determination (R-2), the lowest root mean square error (RMSE) and the lowest standard error of estimate (SEE). Two PEs developed from paired 168-patient data were compared with measured REE using mean absolute percentage difference. Results Mean absolute percentage difference between predicted and measured REE was <20%, which is not clinically significant. Thus, a single PE was developed and validated from data of the larger sample size measured in the acute phase. The best PE for REE (kcal/day) was 891.6(Height) + 9.0(Weight) + 39.7(Minute Ventilation)-5.6(Age) - 354, with R-2 = 0.442, RMSE = 348.3, SEE = 325.6 and mean absolute percentage difference with measured REE was: 15.1 +/- 14.2% acute], 15.0 +/- 13.1% late]. Conclusions Separate PEs for acute and late phases may not be necessary. Thus, we have developed and validated a PE from acute phase data and demonstrated that it can provide optimal estimates of REE for patients in both acute and late phases. |
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Tah, Pei Chien Poh, Bee Koon Kee, Chee Cheong Lee, Zheng-Yii Hakumat-Rai, Vineya-Rai Nor, Mohd Basri Mat Zaman, Mazuin Kamarul Majid, Hazreen Abdu Hasan, M. Shahnaz |
author_facet |
Tah, Pei Chien Poh, Bee Koon Kee, Chee Cheong Lee, Zheng-Yii Hakumat-Rai, Vineya-Rai Nor, Mohd Basri Mat Zaman, Mazuin Kamarul Majid, Hazreen Abdu Hasan, M. Shahnaz |
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Tah, Pei Chien |
title |
Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements |
title_short |
Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements |
title_full |
Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements |
title_fullStr |
Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements |
title_full_unstemmed |
Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements |
title_sort |
do we need different predictive equations for the acute and late phases of critical illness? a prospective observational study with repeated indirect calorimetry measurements |
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Springernature |
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2022 |
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http://eprints.um.edu.my/42432/ |
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1816130412175425536 |
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13.214268 |