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2 "Hak-Jae Lee"
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Original Articles
Determining the appropriate resting energy expenditure requirement for severe trauma patients using indirect calorimetry in Korea: a retrospective observational study
Hak-Jae Lee, Sung-Bak Ahn, Jung Hyun Lee, Ji-Yeon Kim, Sungyeon Yoo, Suk-Kyung Hong
J Trauma Inj. 2023;36(4):337-342.   Published online November 3, 2023
DOI: https://doi.org/10.20408/jti.2023.0051
  • 1,558 View
  • 71 Download
AbstractAbstract PDF
Purpose
This study aimed to compare the resting energy expenditure (REE) measured using indirect calorimetry with that estimated using predictive equations in severe trauma patients to determine the appropriate caloric requirements.
Methods
Patients admitted to the surgical intensive care unit between January 2020 and March 2023 were included in this study. Indirect calorimetry was used to measure the patients’ REE values. These values were subsequently compared with those estimated using predictive equations: the weight-based equation (rule of thumb, 25 kcal/kg/day), Harris-Benedict, Ireton-Jones, and the 2003 Penn State equations.
Results
A total of 27 severe trauma patients were included in this study, and 47 indirect calorimetric measurements were conducted. The weight-based equation (mean difference [MD], –28.96±303.58 kcal) and the 2003 Penn State equation (MD, –3.56±270.39 kcal) showed the closest results to REE measured by indirect calorimetry. However, the REE values estimated using the Harris-Benedict equation (MD, 156.64±276.54 kcal) and Ireton-Jones equation (MD, 250.87±332.54 kcal) displayed significant differences from those measured using indirect calorimetry. The concordance rate, which the predictive REE differs from the measured REE value within 10%, was up to 36.2%.
Conclusions
The REE values estimated using predictive equations exhibited substantial differences from those measured via indirect calorimetry. Therefore, it is necessary to measure the REE value through indirect calorimetry in severe trauma patients.
Summary
Clinical Outcomes of Diffuse Axonal Injury According to Radiological Grade
Hak-Jae Lee, Hyun-Woo Sun, Jae-Seok Lee, Nak-Joon Choi, Yoon-Joong Jung, Suk-Kyung Hong
J Trauma Inj. 2018;31(2):51-57.   Published online August 31, 2018
DOI: https://doi.org/10.20408/jti.2018.31.2.51
  • 20,457 View
  • 345 Download
  • 5 Citations
AbstractAbstract PDF
Purpose

Patients with diffuse axonal injury experience various disabilities and have a high cost of treatment. Recent researches have revealed the underlying mechanism and pathogenesis of diffuse axonal injury. This study aimed to investigate the correlation between the radiological grading of diffuse axonal injury and the clinical outcomes of patients.

Methods

From January 2011 to December 2016, among 294 patients with traumatic brain injury, 44 patients underwent magnetic resonance imaging (MRI). A total of 18 patients were enrolled in this study except for other cerebral injuries, such as cerebral hemorrhage or hypoxic brain damage. Demographic data, clinical data, and radiological findings were retrospectively reviewed. The grading of diffuse axonal injury was analyzed based on patient’s MRI findings.

Results

For the most severe diffuse axonal injury patients, prolonged intensive care unit (ICU) stay (p=0.035), hospital stay (p=0.012), and prolonged mechanical ventilation (p=0.030) were observed. However, there was no significant difference in healthcare-associated infection rates between MRI grading (p=0.123). Massive transfusion, initial hemoglobin and lactate levels, and MRI gradings were found to be highly significant in predicting the duration of unconsciousness.

Conclusions

This study showed that patients with high grade diffuse axonal injury have prolonged ICU stays and significantly longer hospital stays. Deteriorated mental patients with high energy injuries should be evaluated to identify diffuse axonal injuries by using an appropriate imaging tool, such as MRI. It will be important to predict the duration of consciousness recovery using MRI scans.

Summary

Citations

Citations to this article as recorded by  
  • Prediction for the prognosis of diffuse axonal injury using automated pupillometry
    Makoto Murase, Shinichi Yasuda, Makoto Sawano
    Clinical Neurology and Neurosurgery.2024; 240: 108244.     CrossRef
  • Head CT for the intensivist: 10 tips and pearls
    Sajeev A. MAHENDRAN, Oliver FLOWER, J. Claude HEMPHILL III rd
    Minerva Anestesiologica.2022;[Epub]     CrossRef
  • Evaluation of Laboratory Variables Related to Diffuse Axonal Injury: A Cross-sectional Study
    Masoud Hatefi, Khalil Komlakh
    Archives of Neuroscience.2022;[Epub]     CrossRef
  • Clinical outcomes of diffuse axonal injury after traumatic brain injury according to magnetic resonance grading
    Insu Lee, Kawngwoo Park, Tae Seok Jeong, Woo-Seok Kim, Woo Kyung Kim, Do Yeon Rhee, Cheol Wan Park
    Journal of Korean Society of Geriatric Neurosurger.2021; 16(2): 71.     CrossRef
  • Use of Magnetic Resonance Imaging in Acute Traumatic Brain Injury Patients is Associated with Lower Inpatient Mortality
    Hwan Lee, Yifeng Yang, Jiehui Xu, Jeffrey B. Ware, Baogiong Liu
    Journal of Clinical Imaging Science.2021; 11: 53.     CrossRef

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