Harris-Benedict Formula Research Articles

Changing laws of rest energy expenditure in critically ill patients and the intervention effect for nutritional support: a prospective study

To investigate the changing laws of rest energy expenditure (REE) in intensive care unit (ICU) patients and the intervention effect for nutritional support. A prospective randomized control trial was conducted. Fifty-eight critically ill patients who were expected to be able to receive sustained enteral and (or) parenteral nutrition for more than 7 days admitted to ICU of the First Affiliated Hospital of Bengbu Medical College from December 2016 to June 2017 were enrolled. The patients were divided into REE group (n = 29) and HBREE group (n = 29) according to the random number table. On the 1st to 7th day after ICU admission, the indirect calorimetry and the Harris-Benedict (HB) formula were used to obtain the REE and HBREE values, and nutritional support was given according to REE and HBREE values respectively. The data of hemoglobin (Hb), albumin (Alb), prealbumin (PA), C-reactive protein (CRP), oxygenation index (OI) on 1st, 3rd, 5th, 7th and discharged day, and insulin dosage, vasopressor time, mechanical ventilation time, the length of ICU stay, and 28-day mortality were collected. (1) At the beginning, the REE level was high, and then decreased gradually with the extension of hospitalization, and the decline was obvious on the 2nd to 3rd day (kJ/d: 7 088.38±559.41, 6 751.34±558.72 vs. 7 553.44±645.55, both P < 0.05), and was stable from the 5th day, the changing laws showed high at first, then the low, the first rapid decline, then the slow decline, and then reached the steady, there was a 2-day plateau in the middle. During the first 2 days, the REE value was significantly higher than the HBREE value (kJ/d: 7 553.44±645.55 vs. 6 759.21±668.14, 7 088.38±559.41 vs. 6 759.21±668.14, both P < 0.01); on the 3rd, 4th day, the REE value was almost the same as the HBREE value (kJ/d: 6 751.34±558.72 vs. 6 759.21±668.14, 6 568.03±760.19 vs. 6 759.21±668.14, both P > 0.05). After that, the REE value was significantly lower than the HBREE value (kJ/d: 6 089.55±560.70 vs. 6 759.21±668.14, 5 992.55±501.82 vs. 6 759.21±668.14, 5 860.84±577.59 vs. 6 759.21±668.14, all P < 0.01). (2) After the initiation of nutritional support, Hb in the REE group (the first 3 days) and HBREE group (the first 7 days) all increased slowly in the early stage. It increased obviously on the 5th day in the REE group. Compared with the REE group, Hb increased more slowly in the HBREE group, however, there was no difference between the two groups at the time of discharge (g/L: 113.75±17.28 vs. 110.86±15.35, P > 0.05). PA and OI all enhanced significantly on the 3rd day since the nutritional support was initiated, but the daily increase of the REE group was significantly higher than that of the HBREE group [3rd day, PA (mg/L): 110.38±27.65 vs. 96.28±18.06, OI (mmHg, 1 mmHg = 0.133 kPa): 259.29±49.36 vs. 231.74±28.02, both P < 0.05]. The Alb and CRP in the REE group began to improve on the 3rd day, while the index in the HBREE group was delayed on the 5th day, overall, at the time of discharge, the PA, CRP and OI were lower in the HBREE group than in the REE group [PA (mg/L): 252.28±56.94 vs. 295.86±57.26, CRP (mg/L): 73.14±17.63 vs. 56.52±14.91, OI (mmHg): 353.59±70.36 vs. 417.52±71.58, all P < 0.01]. (3) The vasopressor was used in both groups for less than 3 days, but the REE group was shorter (days: 2.26±0.82 vs. 2.95±1.22, P < 0.05), the insulin dosage in the HBREE group was much more than that in the REE group (U: 101.97±21.05 vs. 84.59±22.21, P < 0.01); compared with the REE group, the time of mechanical ventilation and the length of ICU stay in the HBREE group were longer (hours: 113.07±25.96 vs. 93.41±27.25, days: 10.41±3.11 vs. 8.45±2.44, both P < 0.01). There was no significant difference in the 28-day mortality between the REE group and HBREE group (17.24% vs. 24.14%, P > 0.05). Indirect calorimetry can more accurately grasp the changing laws of REE in critically ill patients. Nutritional support with REE value can make relevant nutritional indicators as good as possible, and reduce insulin dosage, shorten vasopressor use time, the length of ICU stay and mechanical ventilation time, but does not change the 28-day mortality.

Design of expert system to determine the proper diet using harmony search method

Excess or lack of nutrients contained in food will cause a problem in the body. To solve this problem easily, a computerized system is needed that can provide some advice on the amount and type of food that needed to be consumed. The aim of this study is to design an expert system which addresses individual diet based on calorie activities and body needs. This study uses the Prototype as a software development methodology and Data Flow Diagram (DFD) as a software model. This expert system uses a harmony search algorithm to determine the amount of food with Harris-Benedict formula to calculate the body’s calorie needs. The results of functional system testing and based on the assessment of nutritionists, this expert system have been worked well for people with normal body metabolism.

Consistency of indirect calorimetry and HB coefficient method for measuring energy expenditure of patients with sepsis

Objective To evaluate the difference and correlation of 24 h energy expenditure in patients with sepsis by indirect calorimetry (IC) and HB coefficient equation. Methods A prospective comparative study including 60 patients with sepsis who was suitable for nutritional support and respiratory indirect calorimetry in the intensive care unit (ICU) from January to October 2015 was conducted. Resting energy expenditure (REE) was measured simultaneously by respiratory indirect calorimetry and HB coefficient (Harris-Benedict formula×stress coefficient) in 60 patients with sepsis at 0 day, 3 day, 7 day, and 14 day after nutritional support, and the differences in dynamic REE were compared between the two methods. The consistency of REE by indirect calorimetry (IC) and HB coefficient equation was evaluated by Bland-Altman. The correlation of IC and HB methods was determined by Pearson analysis. The linear regression equation was determined by linear regression analysis. Results Within 2 weeks after nutritional support, 188 times of measures by IC method and HB method respectively were finished in all patients with sepsis. The dynamic REE in respiratory indirect calorimetry group was significantly higher than that in HB coefficient method group (P<0.05). The average bias of REE between the IC method and the HB method was (1 930.9±597.7)kJ/24 h. For the consistency boundaries was over large and beyond the scope of clinical acceptance, there was a bias between the two methods and they could not directly substituted. There was a linear correlation of REE between the IC method and the HB coefficient (r=0.757, P=0.000). The equation associated with the HB coefficient method is fitted using a one-way regression: Y=1.17X+ 834.11 (kJ/24 h), and X was the 24 h energy expenditure measured by the HB coefficient method. Conclusion The energy metabolism of patients with sepsis is not obvious in the first 2 weeks. The HB coefficient method significantly underestimates the 24 h energy expenditure of patients with sepsis. The prediction equation can be used to correct the HB coefficient method and improve the HB coefficient method to predict the energy expenditure of patients with sepsis. Key words: Sepsis; Energy Consumption; HB coefficient; Respiratory indirect calorimetry; Correction formula

A comparative study of the respiratory indirect calorimetry and HB coefficient method for the guidance of the target energy in patients with sepsis

Objective To explore the effects of nutritional supports following target energy measured by respiratory indirect calorimetry and HB coefficient method respectively on the nutrition and immune indexes of patients with sepsis. Methods A prospective comparative study of 60 patients with sepsis who was suitable for nutritional support and respiratory indirect calorimetry in the intensive care unit (ICU) of the hospital from January 2015 to October 2015 was conducted. Resting Energy Expenditure (REE) was measured simultaneously by respiratory indirect calorimetry (n=30) and HB coefficient (Harris-Benedict formula×stress coefficient, n=30) in patients with sepsis and the nutritional support was given according to the MREE measured by the two methods. The nutritional and immune indexes were obtained at 0 day, 3 day, 7 day, and 14 day after nutritional support. The nutritional and immune indexes at 0 day were considered as the baseline and the differences in the nutritional and immune indexes between the baseline and 3 day, 7 day and 14 day were expressed as a Δ. Values of Δ were compared between the two goups. Results With nutritional support for 3 days, Δalbumin, Δ prealbumin, Δthe total T lymphocytes, Δassist/induction of T cells and ΔIgG were higher in the respiratory indirect calorimetry group than in the HB coefficient group (P<0.05). With nutritional support for 7 days, Δalbumin, ΔT lymphocytes, ΔIgM were higher in the respiratory indirect calorimetry group than in the HB coefficient group (P<0.05). With nutritional support for 14 days, Δtransferrin, Δsuppression/cytotoxic T cells, ΔIgG, ΔIgA, ΔC3 andΔC4 were higher in the respiratory indirect calorimetry group than in the HB coefficient group(P<0.05). Conclusion Nutritional support with REE measured by respiratory indirect calorimetry in patients with sepsis is more effective on nutritional and immune related indexes improvement have different degrees of improvement, thus respiratory indirect calorimetry is more suitable to guide the target energy of sepsis patients. Key words: Sepsis; Target energy; Respiratory indirect calorimetry; HB coefficient; Nutrition

Application value of resting energy monitoring in nutritional support therapy for mechanical ventilation patients

To investigate the value of resting energy expenditure (REE) monitoring in nutritional support therapy of critical patients on mechanical ventilation. A prospective randomized controlled trial was conducted. Sixty critical patients [acute physiology and chronic health evaluation II score (APACHE II) > 15] on ventilation admitted to intensive care unit (ICU) of Dalian Friendship Hospital from September 2016 to October 2018 were enrolled. The enrolled patients were randomly divided into Harris-Benedict formula (HB formula) group and indirect energy measurement (metabolic vehicle) group with 30 patients in each group. The HB formula group was used traditional HB formula to determine the energy supply and ratio of nutritional support therapy, and the metabolic vehicle group was regularly measured the energy supply and proportion of nutritional support therapy. Serum albumin (ALB), total protein (TP), lymphocyte ratio, blood glucose, blood gas analysis parameters and REE value were determined at 3, 5, 7, 9, and 11 days of nutritional support therapy. The value of REE at 3 days of nutritional support therapy in metabolic vehicle group was significantly higher than that in HB formula group (kJ/d: 7 850.4±947.3 vs. 6 915.3±875.7, P < 0.05). With the time of nutritional support treatment prolonged, the REE value of metabolic vehicle group was decreased gradually, and after 7 days, the patient's condition was stable and improved, and the REE value tended to be stable gradually, it was significantly lower than that of HB formula group at 11 days (kJ/d: 5 046.3±493.3 vs. 6 915.3±875.7, P < 0.05). There was no significant difference in blood gas analysis or plasma protein before nutritional support therapy between the two groups. After 5 days of nutritional support therapy, the respiratory function of critical patients in both groups was improved, and the lymphocyte ratio and plasma protein parameters were alleviated. After 11 days of nutrition support therapy, the respiratory function of critical patients in both groups was further improved, the ventilator model was adjusted to continuous positive airway pressure (CPAP) mode, the lymphocyte ratio and plasma protein parameters were improved, and the skin color and elasticity were improved, the granulation of the wound was fresh and healed well, and the plasma protein level was increased obviously, ALB level in metabolic vehicle group was significantly higher than that in HB formula group (g/L: 31.8±2.5 vs. 26.7±2.3, P < 0.05). In the metabolic vehicle group, REE value was decreased from the maximum level on the 3rd day (kJ/d: 7 850.4±947.3) to a stable level after 11 days (kJ/d: 5 046.3±493.3), and its energy ratio changed significantly, from carbohydrate : fat of 77% : 21% with protein consumption gradually transition in the early (3 days) to carbohydrates : fat of 56% : 44% without protein consumption in the later stage (11 days), which showed the tendency of energy consumption was reasonable. The energy metabolism rule of critical patients on ventilation could be determined by using the accurate metabolic vehicle and dynamic monitoring of REE value, which could be used for the implementation of nutritional support therapy.

The significance of different predictive equations for resting energy expenditure in patients receiving invasive mechanical ventilation

To calculate resting energy expenditure (REE) in patients receiving invasive mechanical ventilation and compare different predictive equations with indirect calorimetry(IC).A total of 60 patients in intensive care unit(ICU) were enrolled. Measure calculating daily REE in the first week included IC, Harris-Benedict formula, Penn State formula and Swinamer formula. Daily REE did not exhibit significant difference in the first week of mechanical ventilation by IC (all P>0.05).All patients' REE values by IC were higher than those by Harris-Benedict formula (all P<0.01). By Penn State formula, REE in day l, 2, and 5 were comparable (all P>0.05) with those by IC, whereas the consistency between the two methods was poor. Similarly, daily REE by Swinamer formula calculation in the first week did not show significant difference (all P>0.05), with acceptable consistency as IC. Resting energy expenditure in patients receiving invasive mechanical ventilation dose not significantly change during the first week. Swinamer formula is more accurate than other equations when IC is considered as the standard method.

Nutrient Recommendations for Cancer Patients Treated with Pelvic Radiotherapy, with or without Comorbidities.

Radiotherapy is one of the main treatment options used in pelvic cancers. Ionizing radiation induces damage to surrounding tissues, resulting in disruption of normal physiological functions and symptoms such as diarrhea, tenesmus, incontinence, and rectal bleeding, which can all significantly alter the patient's quality of life. These patients are at increased risk of developing protein-calorie malnutrition and micronutrient deficiencies. Therefore, designing a proper nutritional intervention plan, with an optimal proportion of protein, fat, and carbohydrates, is required to reduce or even reverse the patients' poor nutritional status, increase their tolerance and response to oncology treatment, decrease the rate of complications and improve their quality of life. The aim of this review was to establish a nutritional plan that includes recommendations on macronutrient proportions and micronutrient intake in patients receiving pelvic radiotherapy. The following nutritional plan has been recommended in the literature: Energy: 28-31 kcal/kg/day, using the Harris-Benedict formula adjusted for body weight in obese patients; protein: 20-30%; fat: 30-40%; and carbohydrates: 40-50%. The maintenance of adequate levels of Vitamin D, Vitamin E, Vitamin A, calcium, magnesium, thiamin, riboflavin, and niacin must be emphasized. Physical activity must also be increased to maintain muscle mass. Nutrient requirements must be established in an integral manner, considering the patient's age, nutritional status, and the presence of comorbidities. Unnecessary dietary restrictions should be avoided to ensure an adequate nutritional status.

Resting energy expenditure and body composition in patients with head and neck cancer: An observational study leading to a new predictive equation.

Patients with head and neck cancer have changes in body composition and resting energy expenditure (REE) related to significant inflammatory processes. We investigated REE and body composition in a population of patients with head and neck cancer, comparing the measured REE with predicted energy expenditure and deriving an equation of anthropometric values and body composition. This retrospective, observational, descriptive study of a single center included patients with head and neck cancer. We evaluated nutritional status by body mass index (BMI) and Patient-Generated Subjective Global Assessment (PG-SGA), body composition by electric bioimpedance, and REE by indirect calorimetry (IC). We included 140 patients, most of whom were men (80.7%), 60 y or older (58.6%), and had advanced disease (77.9%). Most were malnourished by BMI standards (77.9%) and severely malnourished according to the PG-SGA (49.3%), with a fat-free mass below the ideal values (82.9%) associated with sarcopenia (92.1%). Hypermetabolism was 57%. When comparing REE with the Harris-Benedict formula, we found the agreement limits from -546 613 to 240 708, the mean difference was -152 953 (95% confidence interval [CI], -185 844 to -120 062) and Pitman's variance test was r = -0.294 (P = 0.001). When we included the activity factor and the thermogenesis factor in REE and compared with Harris-Benedict, we found the agreement limits from -764.423 to 337.087, a mean difference of -213.668 (95% CI -259.684 to -167.652), and the Pitman's variance text at r = -0.292 (P = 0.001). Predictive equations, generally recommended by guidelines, are imprecise when compared with IC measures. Therefore, we suggest a new predictive equation.

Measurements of resting energy expenditure in surgical critically ill patients with mechanical ventilator

Objective To compare the differences between measured resting energy expenditure calculated by the indirect calorimetry with the resting energy expenditure calculated by the Harris-Benedict formula and weight formula in the mechanically ventilated surgical critically ill patients in SICU. Methods Patients mechanically ventilated in SICU of Xuanwu Hospital, from April 2014 to April 2015 were measured resting energy expenditure by the indirect calorimetry with the resting energy expenditure calculated by the Harris-Benedict formula and weight formula in the 1st, the 3rd and the 5th day. There were twenty-nine patients enrolled, thirteen males and sixteen females, measured the resting energy expenditure 188 times.The distribution of metabolism level was studied, and the resting energy expenditure measured by three methods were calculated and evaluated by paired sample t test. Results There were 177 times(62.24%)of low metabolism level, 59 times(31.38%)of normal metabolism level, and 12 times(6.38%)of high metabolism level. Eighteen patients used these three methods to calculate the energy expenditure on 1st, 3rd and 5th day: indirect calorimetry (1 627.11±323.63) kcal, (1 614.67±308.93) kcal, (1 576.11±263.96) kcal; Weight formula (1 479.44±200.24) kcal, (1 488.40±227.72) kcal, (1434.14±216.56) kcal; Harris-Benedict formula (1 777.43±253.00) kcal, (1 730.08±265.18) kcal, (1 689.33±236.69) kcal.The results calculated from Harris-Benedict formula and the weight formula were significantly different from calculated from indirect calorimetry(P<0.05). Resting energy expenditure by Harris-Benedict formula was significantly higher than calculated from indirect calorimetry (All P<0.05). Resting energy expenditure by weight formula was significantly lower than calculated from indirect calorimetry(All P<0.05). Conclusions Although Harris-Benedict formula and weight formula is convenient in clinical use, while the results calculated by them is significant different from the results calculated by indirect calorimetry. So clinical nutrition support should rely on indirect calorimetry as far as possible. Key words: Energy metabolism; Nutritional support; Indirect calorimetry; Harris-Benedict formula; Ventilators, mechanical

Influence of chemotherapy on total energy expenditure in patients with gastrointestinal cancer: A pilot study.

Resting energy expenditure (REE) and physical activity (PA) undergo variations during chemotherapy. The aim of this study was to use a metabolic Holter (SenseWear Armband [SWA]) to assess REE, total energy expenditure (TEE), and PA changes in patients undergoing chemotherapy to ensure the appropriate calorie intake. To our knowledge, this is the first study to do so. Eight patients with gastrointestinal tumors and a Karnofsky performance status of >50 underwent evaluation of the body mass index; REE, TEE, metabolic equivalent, and sleep efficiency were evaluated by SWA. Fat-free mass and fat mass were measured by bioelectrical impedance analysis, muscle strength by handgrip, and dietary intake by food diary. All evaluations were performed before chemotherapy (T0), at mid-treatment (T1), and at the end of treatment (T2). A calorie-equivalent diet to the TEE was recommended to all patients. At T0, a body weight loss of 15.1 ±7.2% in the previous 6mo was observed in all patients. Two patients did not complete treatment. During chemotherapy, thanks to the nutritional counseling, the remaining patients increased their calorie intake (P=0.006) and no significant change was observed in other parameters. The REE calculation measured by SWA was correlated to the Harris-Benedict formula (P≤0.002). The present data excluded significant variations of REE and PA in the course of chemotherapy in patients who do not experience weight loss and who have a Karnofsky performance status of >50. Nutritional counseling based on SWA measurements is useful to support nutritional status in patients undergoing chemotherapy.

Resting energy expenditure in the risk assessment of anticancer treatments

Alterations of nutritional and performance status (PS) are associated with higher risk of chemotherapy toxicity. Increased resting energy expenditure (REE) is frequent in cancer patients and may contribute to cachexia. We investigated whether abnormal energetic metabolism could predict early acute limiting toxicities (ELT) of anticancer treatments. In this observational monocentric study, REE was measured by indirect calorimetry before treatment initiation. Based on the ratio of measured REE to REE predicted by the Harris-Benedict formula, patients were classified as hypometabolic (<90%), normometabolic (90-110%) or hypermetabolic (>110%). Body mass index, weight loss, PS, albumin, transthyretin, C-reactive protein (CRP) and muscle mass (CT-scan) were studied. Were defined as ELT any unplanned hospitalization or any adverse event leading to dose reduction or discontinuation during the first cycle of treatment. We enrolled 277 patients: 76% had metastatic disease; 89% received chemotherapy and 11% targeted therapy; 29% were normometabolic, 51% hypermetabolic and 20% hypometabolic. Fifty-nine patients (21%) experienced an ELT. Toxicity was associated with abnormal metabolism (vs normal: OR=2.37 [1.13-4.94], p=0.023), PS (2-3 vs 0-1: OR=2.04 [1.12-3.74], p=0.023), albumin (<35 vs ≥35g/l: OR=2.39 [1.03-5.54], p=0.048), and inflammation (CRP ≥10 vs <10mg/l: OR=2.43 [1.35-4.38], p=0.004). To predict toxicity, the most sensitive parameter was the REE (83%) followed by PINI (63%), GPS (59%), CRP (55%), PS (41%), NRI (37%), and albumin (16%). In multivariate analysis, elevated CRP was an independent predictor of toxicity (p=0.047). Abnormal basal energy metabolism identifies patients at higher risk of treatment-related acute complications.

Accuracy of Prediction Formulae for the Assessment of Resting Energy Expenditure in Hospitalized Children.

The resting energy expenditure (REE) of ill children is commonly estimated from prediction formulae developed in healthy children. The aim of the present study was to evaluate the accuracy of commonly employed REE prediction formulae versus indirect calorimetry in hospitalized children. We performed a cross-sectional study of 236 infants, children, and adolescents consecutively admitted to the Intermediate Care, Nephrology, Intensive Care, Emergency, and Cystic Fibrosis Units of the De Marchi Pediatric Hospital (Milan, Italy) between September 2013 and March 2015. REE was measured by indirect calorimetry and estimated using the World Health Organization (WHO), Harris-Benedict, Schofield, and Oxford formulae. The mean (standard deviation) difference between the estimated and measured REE was: -1 (234) kcal/day for the WHO formula; 82 (286) kcal/day for the Harris-Benedict formula; 2 (215) kcal/day for the Schofield-weight formula; -2 (214) kcal/day for the Schofield-weight and height formula; and -5 (221) kcal/day for the Oxford formula. Even though the WHO, Schofield, and Oxford formulae gave accurate estimates of REE at the population level (small mean bias), all the formulae were not accurate enough to be employed at the individual level (large SD of bias). The WHO, Harris-Benedict, Schofield, and Oxford formulae should not be used to estimate REE in hospitalized children.

A Proper Enteral Nutrition Support Improves Sequential Organ Failure Score and Decreases Length of Stay in Hospital in Burned Patients

Background:Severe burned patients developed metabolic imbalances and systemic inflammatory response syndrome (SIRS), which can lead to malnutrition, impaired immunologic response, multiple organ failure and death. Studies have shown that providing an early and adequate nutrition support can lower hypermetabolic response and improve the outcome. Unfortunately, little emphasis has been given to the role of nutritional support, especially for demonstrating the importance of a proper nutritional support in determining the outcome of critically burned patients.Objectives:This study was designed to determine the possible protective effect of early and adequate nutrition support on sequential organ failure assessment (SOFA) score and length of stay (LOS) in hospital, in thermal burn victims.Patients and Methods:Thirty patients with severe thermal burn (More than 20% of total body surface area [TBSA] burn), on the first day in the intensive care unit, joined this double-blinded randomized controlled clinical trial. Patients were randomly divided into two groups: control group (group C, 15 patients) received hospital routine diet (liquid and chow diet, ad libitum) while intervention group (group I, 15 patients) received commercially prepared solution, with oral or tube feeding. The caloric requirement for these patients was calculated, according to the Harris-Benedict formula. The SOFA score was also measured on admission (SOFA0), day 2 (SOFA1), day 5 (SOFA2) and day 9 (SOFA3), consequently. The difference between the last measurement (SOFA3) and day 2 (SOFA1) was calculated.Results:The results showed that there was a significant change between SOFA3 and SOFA1, {-1[(-1) – 0], P = 0.013 vs. -1 [(-2) - 0], P = 0.109}. Mean LOS in hospital, for patients consuming commercial standard food, also proved to be shorter than those consuming hospital routine foods (17.64 ± 8.2 vs. 23.07 ± 11.89).Conclusions:This study shows that an adequate nutritional support, in patients with severe burn injury, can improve SOFA score. It is also more cost-effective, resulting in a shorter LOS in hospital.

Assessment of need in nutritional support in patients with the consequences of central nervous system injuries

Traumatic brain injury (TBI) and spinal cord injury (SCI) are most common causes of death and disability in young patients. Metabolic changes occur immediately after the acute injury of the central nervous system. However hypermetabolic response in SCI is less pronounced compared to that in TBI that could be explained by the weakness of denervated muscles and hypodynamia. Following SCI, the level of resting energy expenditure is lower comparison to that calculated using the Harris-Benedict formula. Indirect calorimetry corresponded to class II (B) medical evidence, is recommended as a method for assessment of energy expenditure in the acute stage of TBI and SCI as well as in their consequences. Nutritional support is favorable and safe and therefore, it should be used as soon as possible. Many studies provide evidence that nutritional support leads to the replenishment of energy expenditure, reduce catabolic processes and nitrogen loss thus minimizing the risk of complications that in future decrease the extent of disability and increase quality-of-life of patients with the consequences of central nervous system injuries.

A Study on the Body Composition, Physical Activity Level, Basal Metabolic Rate, and Daily Energy Expenditure of Elderly in Busan

Objectives: The objectives of the study were to assess body composition, physical activity level (PAL), basal metabolic rate (BMR), and daily energy expenditure (DEE) and to examine associations between PAL and body composition, BMR, and DEE of elderly in Busan. Methods: A cross-sectional study was conducted among 226 elderly aged 65-93 years. Body composition was measured by Inbody 720. PAL was calculated by daily activity diary. BMR was calculated by Harris-Benedict (H-B) formula, Dietary Reference Intakes (DRI) formula, and Inbody 720 measurement. DEE was calculated by H-B formula, DRI formula, Inbody 720 measurement, and estimated energy requirements (EER) formula. Results: The mean fat free mass (FFM) in elderly men was significantly higher than that in elderly women (p<0.001). The mean percent body fat and fat mass (FM) in elderly women were significantly greater than those in elderly men (p<0.001, p<0.001). The mean PAL in elderly men (1.59) was significantly higher than that in elderly women (1.53) (p<0.001). The mean DEEs calculated by 3 methods except for H-B formula in elderly men were higher than EER for elderly men (2000kcal). The mean DEEs calculated by 4 different methods in elderly women were higher than EER for elderly women (1600kcal). Age showed significantly negative correlations with height (p<0.001, p<0.001), FFM (p<0.001, p<0.001), BMRs calculated by H-B formula (p<0.001, p<0.001), DRI formula (p<0.001, p<0.001) and Inbody 720 measurement (p<0.05 p<0.01) and DEEs calculated by H-B formula (p<0.001, p<0.001), DRI formula (p<0.001, p<0.001), Inbody 720 measurement (p<0.05, p<0.05), and EER formula (p<0.001, p<0.001) in elderly men and elderly women. PAL showed significantly positive correlations with FFM (p<0.05), BMR by Inbody 720 measurement (p<0.05) in elderly men and negative correlations with FM (p<0.05) in elderly women. Conclusions: Based on the results, PAL was associated with greater FFM in elderly men and lesser FM in elderly women. Therefore, nutritional education to increase physical activity for health promotion in late life is needed in the elderly. Korean J Community Nutr 21(2): 178~189, 2016

PTU-146 The use of diet diaries and a gastric accommodation test prior to hospital discharge for predicting intake after discharge following upper gastrointestinal surgery: Abstract PTU-146 Table 1

<h3>Introduction</h3> Patients undergoing upper gastrointestinal surgery are often malnourished and following hospital discharge eat poorly despite dietetic input. The ‘slow satiety’ drinking test has been used to assess impaired gastric accommodation in functional dyspepsia. We examined if a drinking test done along with a 2 day diet diary could predict dietary intake post hospital discharge. <h3>Method</h3> Prior to discharge, patients undergoing an oesophagectomy or total gastrectomy for cancer completed a 2 day dietary diary and underwent a gastric accommodation test. The accommodation test comprised of drinking 20 ml/min of polymeric sip feed until they felt comfortably full. After hospital discharge patients completed 2 day dietary diaries at 3, 6 and 12 weeks. The diaries were analysed using Dietplan 6 and tabulated. We calculated energy intake as absolute intake (Kcal) and% of calculated requirement (using the Harris-Benedict formula). The accommodation tests (volume of feed and time taken) were correlated (Pearson’s) with energy intake at hospital discharge. The accommodation test results and energy intake at hospital discharge were also correlated with energy intake at 3, 6 and 12 weeks post discharge. <h3>Results</h3> 28 patients (22 men), median age 66 (IQR: 60–74), were recruited (Oesophagectomy = 18 Gastrectomy 10). There was no correlation between the accommodation test and actual energy intake or% of required energy intake at hospital discharge. Dietary energy intake (Kcal) at hospital discharge did not correlate with post discharge energy intake, but when expressed as a% of calculated requirements there was a correlation at 6 and 12 weeks. The volume of feed consumed and time taken to drink the sip feed for the accommodation test did not correlate with post discharge dietary intake. <h3>Conclusion</h3> Energy intake at hospital discharge was modest and increased slowly to reach 90% of requirements at 12 weeks. There was only a weak correlation between dietary records done just prior to hospital discharge and those done at 6 and 12 weeks. There was no correlation between the gastric accommodation test and post discharge dietary intake. Neither the gastric accommodation test or 2 day dietary records done just before hospital discharge after upper gastrointestinal surgery predicted post discharge dietary intake. <h3>Disclosure of interest</h3> None Declared.

Risk assessment of anticancer treatments beyond performance status: A prospective study in 277 cancer patients.

9620 Background: Alterations of performance status (PS) and of nutritional status are predictors of acute toxicity following anticancer treatment. Resting energy expenditure (REE) is often increased in cancer patients and may be a major determinant for the alteration of nutritional status and the development of precachexia and cachexia. We investigated whether abnormal metabolism could predict early acute toxicity (EAT). Methods: In this prospective observational monocentric study, REE was measured by indirect calorimetry before anticancer treatment initiation. C-Reactive Protein (CRP), albumin, transthyretin and PS were collected. Measured REE was compared with predicted REE as defined by the Harris-Benedict formula. Patients were classified as hypometabolic (REE < 90%), normometabolic (90-110%) or hypermetabolic ( > 110%). Toxicity was assessed after the first cycle of treatment. An EAT was defined as any event leading to unplanned hospital admission, dose reduction, treatment delay ( > 7 days) or discontinuation. Results: A total of 277 patients (pts) with solid tumors (gastro-intestinal 25%, genitourinary 23%, thoracic 22%) were included. Sex ratio: 1.25; median age: 63 years (20-91). Most of the pts (211; 76%) had locally advanced or metastatic disease and were treated with chemotherapy (246; 89%) or tyrosine-kinase inhibitor (30; 11%). Calorimetry revealed pts with either normo- (29%), hyper- (51%) or hypometabolism (20%). A subset of 59 pts (21%) experienced an EAT. The occurrence of EAT was associated with poor PS (2-3 vs 0-1: OR = 2.04 [1.12-3.73], p = 0.029), low albumin ( < 35 vs ≥ 35g/l: OR = 2.39 [1.03-5.54], p = 0.048), inflammation (CRP ≥ 10 vs < 10mg/l: OR = 2.43 [1.35-4.37], p = 0.004) and abnormal metabolism (abnormal vs normal: OR = 2.36 [1.13-4.95], p = 0.023). In multivariate analysis, elevated CRP was an independent predictor of EAT (p = 0.047). The REE was associated with higher sensitivity (83%) than CRP (55%), PS (41%) and albumin (17%) to predict EAT. Conclusions: Pts with abnormal metabolism experience more early acute toxicity. The measurement of resting energy expenditure might improve the detection of patients at risk for toxicity and missed with the standard clinical evaluation.

Healthcare-associated infections are associated with insufficient dietary intake: an observational cross-sectional study.

BackgroundIndicators to predict healthcare-associated infections (HCAI) are scarce. Malnutrition is known to be associated with adverse outcomes in healthcare but its identification is time-consuming and rarely done in daily practice. This cross-sectional study assessed the association between dietary intake, nutritional risk, and the prevalence of HCAI, in a general hospital population.Methods and findingsDietary intake was assessed by dedicated dieticians on one day for all hospitalized patients receiving three meals per day. Nutritional risk was assessed using Nutritional Risk Screening (NRS)-2002, and defined as a NRS score ≥ 3. Energy needs were calculated using 110% of Harris-Benedict formula. HCAIs were diagnosed based on the Center for Disease Control criteria and their association with nutritional risk and measured energy intake was done using a multivariate logistic regression analysis. From 1689 hospitalised patients, 1024 and 1091 were eligible for the measurement of energy intake and nutritional risk, respectively. The prevalence of HCAI was 6.8%, and 30.1% of patients were at nutritional risk. Patients with HCAI were more likely identified with decreased energy intake (i.e. ≤ 70% of predicted energy needs) (30.3% vs. 14.5%, P = 0.002). The proportion of patients at nutritional risk was not significantly different between patients with and without HCAI (35.6% vs.29.7%, P = 0.28), respectively. Measured energy intake ≤ 70% of predicted energy needs (odds ratio: 2.26; 95% CI: 1.24 to 4.11, P = 0.008) and moderate severity of the disease (odds ratio: 3.38; 95% CI: 1.49 to 7.68, P = 0.004) were associated with HCAI in the multivariate analysis.ConclusionMeasured energy intake ≤ 70% of predicted energy needs is associated with HCAI in hospitalised patients. This suggests that insufficient dietary intake could be a risk factor of HCAI, without excluding reverse causality. Randomized trials are needed to assess whether improving energy intake in patients identified with decreased dietary intake could be a novel strategy for HCAI prevention.

Energy expenditure and balance among long term liver recipients

Excessive weight gain in patients undergoing liver transplantation has been well documented. The etiology for this complication is not well defined, although it has a high prevalence in post-transplant patients. Reduced energy expenditure may be related to excessive weight gain. Thus, the assessment of the resting energy expenditure (REE) in this patient population is of utmost importance. Therefore, patients who underwent liver transplantation had their REEs measured by indirect calorimetry (IC). These results were compared with the demographic, socioeconomic, clinical, anthropometric, dietary and lifestyle variables assessed by uni- and multivariate statistical analyses. The REEs were also compared to estimates using the Harris-Benedict formula, and the patients were classified as hypo-, normo- and hypermetabolic. We evaluated 42 patients with an average of 6.5 years post-transplant and an REE of 1449.7kcal/day (measured by IC) or 1404.5kcal/day (predicted by the HB formula). There was great correlation between the methods, and the best predictors of REE were age, weight, amount of lean mass and amount of total body water. Excessive weight was observed in 57% of patients, and obesity was observed in 26.2%. Underreporting of energy intake was observed in 65.8% of patients, and most patients (92.7%) were classified as sedentary or less active. No patient was classified as hypometabolic. These results indicate that hypometabolism should be discarded as cause of the high prevalence of overweight and obese patients in the population undergoing LT. However, energy consumption and low levels of physical activity may be risk factors.

Weight loss and resting energy expenditure in male patients with newly diagnosed esophageal cancer

ObjectivesCancer cachexia is associated with impaired nutritional status and systemic inflammation. The goal of this study was to evaluate the nutritional status and resting energy expenditure (REE) changes in patients with newly detected esophageal cancer, and the influence of weight loss on REE. MethodsFifty-six patients and 30 healthy controls were prospectively enrolled, and patients were further divided into weight-stable (WS) and weight-loss (WL) subgroups. Body composition, measured REE (mREE), and the ratio of mREE to predicted REE (pREE) by Harris-Benedict formula were assessed. Blood levels of hemoglobin, albumin, prealbumin, high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-alpha (TNF-α), and interleukin (IL)-6 were measured in patients. ResultsCancer patients had lower body mass index (BMI) and percentage of fat mass, but higher mREE and percentage of mREE/pREE compared with healthy controls (P < 0.05). WS (n = 32) and WL patients (n = 24) had similar BMI and body composition indices, but the latter had obviously higher mREE, mREE per kilogram body weight (mREE/BW), percentage of mREE/pREE, hs-CRP and IL-6 levels, and lower albumin and prealbumin levels. Percentage of weight loss was positively correlated with REE/BW, hs-CRP, and IL-6 level (r = 0.238, P = 0.044; r = 0.446, P = 0.01; r = 0.196, P = 0.047, respectively). ConclusionImpaired nutrition status, elevated energy expenditure, and higher inflammation status tend to be apparent in weight-losing patients with newly diagnosed esophageal cancer, which suggested that early recognition of body weight change and routine nutritional risk screening followed by adequate nutrition intervention should be applied in these patients.