PP011-MON RESTING ENERGY EXPENDITURE IN CHRONICALLY VENTILATED GERIATRIC PATIENTS UNDERGOING WEANING FROM MECHANICAL VENTILATION; AN OBSERVATIONAL STUDY

Objective: Several predictive equations have been used to estimate patients’ energy expenditure. The study aimed to describe the characteristics of resting energy expenditure (REE) in patients undergoing mechanical ventilation during early postoperative stage after cardiac surgery and evaluate the validity of 9 REE predictive equations. Methods: This was a prospective observational study. Patients aged 18–80 years old, undergone open-heart surgery, were enrolled between January 2017 and 2018. The measured REE (mREE) was evaluated via indirect calorimetry (IC). The predictive resting energy expenditure (pREE) was suggested by 9 predictive equations, including Harris-Benedict (HB), HB coefficient method, Ireton-Jones, Owen, Mifflin, Liu, 25 × body weight (BW), 30 × BW, and 35 × BW. The association between mREE and pREE was assessed by Pearson’s correlation, paired t test, Bland-Altman method, and the limits of agreement (LOA). Results: mREE was related to gender, BMI, age, and body temperature. mREE was significantly correlated with pREE, as calculated by 9 equations (all p < 0.05). There was no significant difference between pREE and mREE, as calculated by 30 × BW kcal/kg/day (t = 0.782, p = 0.435), while significant differences were noted between mREE and pREE calculated by other equations (all p < 0.05). Taking the 30 × BW equation as a suitable candidate, most of the data points were within LOA, and the percentage was 95.6% (129/135). Considering the rationality of clinical use, accurate predictions (%) were calculated, and only 40.74% was acceptable. Conclusions: The 30 × BW equation is relatively acceptable for estimating REE in 9 predictive equations in the early stage after heart surgery. However, the IC method should be the first choice if it is feasible.

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Resting energy expenditure in Duchenne patients using home mechanical ventilation

European Respiratory Journal ◽

10.1183/09031936.05.00031304 ◽

2005 ◽

Vol 25 (4) ◽

pp. 682-687 ◽

Cited By ~ 21

Author(s):

J. Gonzalez-Bermejo

Keyword(s):

Mechanical Ventilation ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Home Mechanical Ventilation ◽

Resting Energy

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Effects of the ketogenic diet on nutritional status, resting energy expenditure, and substrate oxidation in patients with medically refractory epilepsy: A 6-month prospective observational study

Clinical Nutrition ◽

10.1016/j.clnu.2011.09.012 ◽

2012 ◽

Vol 31 (2) ◽

pp. 246-249 ◽

Cited By ~ 33

Author(s):

Anna Tagliabue ◽

Simona Bertoli ◽

Claudia Trentani ◽

Paola Borrelli ◽

Pierangelo Veggiotti

Keyword(s):

Energy Expenditure ◽

Observational Study ◽

Nutritional Status ◽

Ketogenic Diet ◽

Prospective Observational Study ◽

Refractory Epilepsy ◽

Resting Energy Expenditure ◽

Substrate Oxidation ◽

Medically Refractory Epilepsy ◽

Resting Energy

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Resting Energy Expenditure During Mechanical Ventilation and Its Relationship With the Type of Lesion

Journal of Parenteral and Enteral Nutrition ◽

10.1177/014860710703100158 ◽

2007 ◽

Vol 31 (1) ◽

pp. 58-62 ◽

Cited By ~ 24

Author(s):

Joan Maria Raurich ◽

Jordi Ibáñez ◽

Pere Marsé ◽

María Riera ◽

Xavier Homar

Keyword(s):

Mechanical Ventilation ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Resting Energy

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ACCURACY OF PREDICTED RESTING ENERGY EXPENDITURE ON PATIENTS WITH INVASIVE MECHANICAL VENTILATION

Journal of Medicine and Pharmacy ◽

10.34071/jmp.2017.2.12 ◽

2017 ◽

pp. 68-73

Author(s):

Ngoc Son Do ◽

Son Tung Vu ◽

Van Chi Nguyen

Keyword(s):

Mechanical Ventilation ◽

Energy Expenditure ◽

Critically Ill ◽

Indirect Calorimetry ◽

Critically Ill Patients ◽

Invasive Mechanical Ventilation ◽

Resting Energy Expenditure ◽

Prediction Equations ◽

Penn State ◽

Resting Energy

Objectives: to compare the accuracy among the resting energy expenditure (REE) calculated by using prediction equations by Harris – Benedict (H-B), Harris – Benedict with stress factor 1.2 (H-Bx1.2), Penn State 2003 (PS2003), 25kcal/kg and 30 kcal/kg versus REE measured by indirect calorimetry (IC). Patients: 40 mechanically ventilated patients from the Emergency Department at Bach Mai Hospital between April 2016 and October 2016. Methods: a prospective observatory study. REE of all patients were measured by IC and compared with REE calculated by prediction equations. Pearson ratio was used to assess correlation between measured and calculated REE. Results: the accuracy of the estimated equation was 37.5% (H-B); 35% (H-Bx1.2); 47.5% (PS2003); 25% (25kcal/kg); 32.5% (30 kcal/kg). Penn State 2003 was estimated accurately in 60% among female patients and 64.7% among patients with BMI<18.5. There was a proportional correlation between H-B and H-Bx1.2 (r=0.56; p<0.001) and PS2003 (r=0.48; p<0.001) and 25kcal/kg and 30 kcal/kg (r=0.48; p<0.001). Conclusions: Among prediction equations vs IC, PS2003 had the highest accuracy and correlation, therefore, it should be the tool of choice on the critically ill patients who were female and/or whose BMI <18.5 where IC was not available. Key words: Energy expenditure, indirect calorimetry, critically ill patients, prediction equations, invasive mechanical ventilation.

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