危重病儿童机械通气后静息能量消耗变化

目的了解危重病儿童机械通气后能量代谢状态,探讨机械通气时间及疾病类别对危重病儿童机械通气后能量代谢的影响。方法以50例儿童重症监护病房机械通气后的危重病儿童为研究对象,开始机械通气治疗第1、3、5、7天,采用美国麦加菲营养能量代谢测定系统测定静息能量消耗值,分别记作实测值1、实测值3、实测值5、实测值7;运用Schofield-H邢汀公式计算入选患儿的预测静息能量消耗值。结果50例患儿实测值．和Schofield—HTWT公式预测值分别为（96．80±42．63）和（110．67±38．35）kJ／d。其中35例（70％）患儿的实测值低于90％Schofield—HTwT预测值。22例患儿的实测值,、实测值,、实测值,、实测值,分别为（100．53±50．24）、（113．80±49．19）、（117．99±50．57）、（115．05±50．18）kJ／d,4个不同时间点比较差异无统计学意义（F=1．267,P=0．292）。先天性心脏病儿童和非先天性心脏病儿童实测值,分别为（75．66±31．23）和（113．40±28．40）kJ／d,两不同疾病类别比较差异具有统计学意义（F=10．423,P=0．002）。结论危重病儿童机械通气后大多数呈现低代谢状态;危重病儿童机械通气后的静息能量消耗在开始通气1周内并不随机械通气时间而改变;机械通气后的危重病儿童中,先天性心脏病儿童的静息能量消耗比非先天性心脏病儿童的静息能量消耗明显降低。     

Hypocaloric enteral tube feeding in critically ill obese patients

OBJECTIVE: We respectively compared the nutritional and clinical efficacies of eucaloric and hypocaloric enteral feedings in 40 critically ill, obese patients admitted to the trauma or surgical intensive care unit. METHODS: Adult patients, 18 to 69 years old, with weights greater than 125% of ideal body weight, normal renal and hepatic functions, and who received at least 7 d of enteral tube feeding were studied. Patients were stratified according to feeding group: eucaloric feeding (>or=20 kcal/kg of adjusted weight per day; n = 12) or hypocaloric feeding (<20 kcal/kg of adjusted weight per day; n = 28). The goal protein intake for both groups was approximately 2 g/kg of ideal body weight per day. Clinical events and nutrition data were recorded for 4 wk. RESULTS: Patients were similar according to sex, age, weight, body mass index, Second Acute Physiology and Chronic Health Evaluation score, Trauma score, and Injury Severity Score. The hypocaloric feeding group received significantly fewer calories than the eucaloric group (P相似文献   

Resting energy expenditure in cancer patients before and after gastrointestinal surgery.

The aim of this study was to assess the impact of surgical trauma on energy metabolism in cancer patients. Therefore, resting energy expenditure (REE) was determined before and after surgery in patients with newly detection gastric and colorectal cancer. Preoperative REE was measured in 104 patients. In 65 of these 104 patients REE was also measured on the seventh or eighth postoperative day. Postoperative REE was significantly higher than preoperative REE (mean +/- SD: 1471 +/- 238 vs 1376 +/- 231 kcal; p less than 0.001). After surgery 22 patients were hypermetabolic (REE greater than or equal to 115% predicted energy expenditure) compared with seven hypermetabolic patients before surgery. This hypermetabolism in the postoperative state can be explained by the administration of total parenteral nutrition (TPN), by an increased body temperature mainly as a consequence of postoperative complications and by the surgical trauma itself. Patients who received preoperative TPN (n = 12) showed a 10% increase in REE. Thirteen patients suffered from minor and major postoperative complications; postoperative REE in this group was increased by 10%. Forty patients who had undergone uncomplicated surgery showed a slight but significant increase of 3% in REE after operation. We conclude from this study that the increase in REE resulting from surgical trauma itself is modest at the seventh to eighth postoperative day. Therefore, energy requirements for patients undergoing major elective surgical stress are lower than generally presumed.     

Immunonutrition in the intensive care unit. A systematic review and consensus statement

OBJECTIVE: To systematically review the effects of enteral nutrition with pharmaconutrients-enriched diets in critically ill patients and to establish recommendations for their use. DATA SOURCES: Computerized bibliographic search of published research and citation review of relevant articles. STUDY SELECTION: Randomized clinical trials of critically ill patients treated with enteral nutrition comparing diets enriched with pharmaconutrients vs not enriched diets were included. Infectious complications and outcome variables (days on mechanical ventilation, ICU and hospital length of stay and mortality) were evaluated. Studies were classified in four subgroups according to the patient's primary diagnosis: surgical, trauma, burned or medical. DATA EXTRACTION: A group of experts in methodology performed data extraction and statistical processes. A global analysis of the studies was done and also a separate study for each subgroup. Results of the meta-analysis were discussed within a 'clinical group' of clinicians with experience in the nutritional support of ICU patients, in order to find agreement about recommendations for the use of pharmaconutrients-enriched diets in critically ill patients. RESULTS: Independent review of 267 articles identified 26 relevant primary studies. Global results indicate that there was a reduction in infection rate in the pharmaconutrition group, considering the appreciated lower incidence in abdominal abscesses (OR: 0.26, CI: 0.12-0.55) (P=0.005), nosocomial pneumonia (OR: 0.54, CI: 0.35-0.84) (P=0.007) and bacteremia (OR: 0.45, CI: 0.35-0.84) (P=0.0002). Also, patients treated with pharmaconutrition diets have a reduction in time on mechanical ventilation (mean 2.25 days, CI: 0.5-3.9) (P=0.009), ICU length of stay (mean reduction of 1.6 days, CI: 1.9-1.2) (P<0.0001) and hospital length of stay (mean reduction of 3.4 days, CI: 4.0-2.7) (P<0.0001). No effects were appreciated on mortality (OR: 1.10, CI: 0.85-1.42) (P=0.5). Nevertheless, the separate analysis for each subgroup showed that the reported beneficial effects were not the same for each patient population. Also, the clinician panel of experts identifies several problems in the published data about enteral pharmaconutrition in critically ill patients. In spite of the subgroup differences and of the problems detected, the clinician group considered that the appreciated results could support a Grade B recommendation for the use of these formulas in ICU patients. CONCLUSIONS: Considering the beneficial effects and the absence of detrimental ones, the use of diets enriched with pharmaconutrients could be recommended in ICU patients requiring enteral feeding. Nevertheless, more investigation is needed in this field in order to find the more appropriate population of patients that can benefit from this nutritional therapy.     

An evaluation of resting energy expenditure in hospitalized, severely underweight patients.

A prospective trial was conducted with 14 hospitalized patients who were severely underweight with a mean weight of 40.9+/-5.1 kg and 70.7+/-7.8% of ideal body weight, to compare estimates of resting energy expenditure (REE) with measured values. The 9 women and 3 men, whose mean age was 66.5+/-13.9 y, underwent nutritional assessment and measurement of their REE by indirect calorimetry using the Sensormedics Deltatrac MBM100 indirect calorimeter. Their REE was also estimated by the Harris-Benedict formula (mean 1032+/-66 kcal/d) as well as a previously established empirical formula where REE = 25 x body weight in kg (mean 1023+/-129 kcal/d). Results by both estimates were significantly lower than the measured resting energy expenditure (MREE) in this group of patients (P<0.0001). The percentage difference between MREE and estimated REE by the Harris-Benedict formula was 18.4+/-9.4% and 20.9+/-7.5% by the empirical formula. The MREE exceeded the estimated REE in each individual. The correlation between MREE and body weight (r2 = 0.558, r = 0.005) was better than that between MREE and estimated REE by Harris-Benedict formula (r2 = 0.275, P = 0.08) suggesting that weight was the principal determinant rather than the other components (height, age, sex) of the Harris-Benedict formula. Our data shows that commonly employed formulae routinely underestimate the energy needs of severely underweight patients below 50 kg in body weight. The Harris-Benedict equation had limited predictive value for the individual, explaining approximately 25% of the variance in energy expenditure. Given the particular importance of matching energy intake to needs in this group of patients with limited reserves, many of whom are critically ill, we suggest an empirical equation using 30-32 kcal/kg be used to estimate the energy requirements of severely underweight patients when direct measurements are unavailable or clinically less imperative.     

Comparison of indirect calorimetry, the Fick method, and prediction equations in estimating the energy requirements of critically ill patients

BACKGROUND: Accurate measurement of resting energy expenditure (REE) is helpful in determining the energy needs of critically ill patients requiring nutritional support. Currently, the most accurate clinical tool used to measure REE is indirect calorimetry, which is expensive, requires trained personnel, and has significant error at higher inspired oxygen concentrations. OBJECTIVE: The purpose of this study was to compare REE measured by indirect calorimetry with REE calculated by using the Fick method and prediction equations by Harris-Benedict, Ireton-Jones, Fusco, and Frankenfield. DESIGN: REEs of 36 patients [12 men and 24 women, mean age 58+/-22 y and mean Acute Physiology and Chronic Health Evaluation II score 22+/-8] in a hospital intensive care unit and receiving mechanical ventilation and total parenteral nutrition (TPN) were measured for > or = 15 min by using indirect calorimetry and compared with REEs calculated from a mean of 2 sets of hemodynamic measurements taken during the metabolic testing period with an oximetric pulmonary artery catheter. RESULTS: Mean REE by indirect calorimetry was 8381+/-1940 kJ/d and correlated poorly with the other methods tested (r = 0.057-0.154). This correlation did not improve after adjusting for changes in respiratory quotient (r2 = 0.28). CONCLUSIONS: These data do not support previous findings showing a strong correlation between REE determined by the Fick method and other prediction equations and indirect calorimetry. In critically ill patients receiving TPN, indirect calorimetry, if available, remains the most appropriate clinical tool for accurate measurement of REE.     

Assessment of resting energy expenditure in mechanically ventilated patients

BACKGROUND: Usual equations for predicting resting energy expenditure (REE) are not appropriate for critically ill patients, and indirect calorimetry criteria render its routine use difficult. OBJECTIVE: Variables that might influence the REE of mechanically ventilated patients were evaluated to establish a predictive relation between these variables and REE. DESIGN: The REE of 70 metabolically stable, mechanically ventilated patients was prospectively measured by indirect calorimetry and calculated with the use of standard predictive models (Harris and Benedict's equations corrected for hypermetabolism factors). Patient data that might influence REE were assessed, and multivariate analysis was conducted to determine the relations between measured REE and these data. Measured and calculated REE were compared by using the Bland-Altman method. RESULTS: Multivariate analysis retained 4 independent variables defining REE: body weight (r(2) = 0.14, P < 0.0001), height (r(2) = 0.11, P = 0.0002), minute ventilation (r(2) = 0.04, P = 0.01), and body temperature (r(2) = 0.07, P = 0.002): REE (kcal/d) = 8 x body weight + 14 x height + 32 x minute ventilation + 94 x body temperature - 4834. REE calculated with this equation was well correlated with measured REE (r(2) = 0.61, P < 0.0001). Bland-Altman plots showed a mean bias approaching zero, and the limits of agreement between measured and predicted REE were clinically acceptable. CONCLUSION: Our results suggest that REE estimated on the basis of body weight, height, minute ventilation, and body temperature is clinically more relevant than are the usual predictive equations for metabolically stable, mechanically ventilated patients.     

24-hour indirect calorimetry in mechanically ventilated critically ill patients.

BACKGROUND: Energy imbalance in critically ill, mechanically ventilated patients may lead to medical complications. The nutrition care team needs accurate, noninvasive, rapid methods to estimate energy requirements. We investigated whether brief measurements of indirect calorimetry at any time of the day would give valid estimates of 24-hour energy expenditure (EE). METHODS: EE of 12 mechanically ventilated critically ill patients (6 men, 6 women, mean +/- SD age 67 +/- 18 years, weight 70.2 +/- 8.8 kg) was recorded every minute during 24 hours by indirect calorimetry. All patients were continuously fed enteral nutrition. RESULTS: Mean +/- SD EE was 1658 +/- 279 kcal/d (6941 +/- 1167 kJ/d). Within patients, EE during the day fluctuated by 234 kcal in the most constant patient to 1190 kcal in the least constant patient, with a mean fluctuation of 521 kcal (12 patients). No statistically significant difference (p = .53) in mean EE between morning (6-12 hours, 1676 kcal), afternoon (12-18 hours, 1642 kcal), evening (18-24 hours, 1658 kcal), and night (0-6 hours, 1655 kcal) was found. A 2-hour instead of a 24-hour measurement resulted in a maximal error of 128 kcal (536 kJ), which was <10% of the average EE. The maximal error decreased with longer time intervals. CONCLUSIONS: In mechanically ventilated critically ill patients, 24-hour indirect calorimetry measurements can be replaced by shorter (>/=2 hours) measurements. Time of day did not affect EE.     

Accurate determination of energy needs in hospitalized patients

OBJECTIVE: To evaluate the accuracy of seven predictive equations, including the Harris-Benedict and the Mifflin equations, against measured resting energy expenditure (REE) in hospitalized patients, including patients with obesity and critical illness. DESIGN: A retrospective evaluation using the nutrition support service database of a patient cohort from a similar timeframe as those used to develop the Mifflin equations. SUBJECTS/SETTING: All patients with an ordered nutrition assessment who underwent indirect calorimetry at our institution over a 1-year period were included. INTERVENTION: Available data was applied to REE predictive equations, and results were compared to REE measurements. MAIN OUTCOME MEASURES: Accuracy was defined as predictions within 90% to 110% of the measured REE. Differences >10% or 250 kcal from REE were considered clinically unacceptable. STATISTICAL ANALYSES PERFORMED: Regression analysis was performed to identify variables that may predict accuracy. Limits-of-agreement analysis was carried out to describe the level of bias for each equation. RESULTS: A total of 395 patients, mostly white (61%) and African American (36%), were included in this analysis. Mean age+/-standard deviation was 56+/-18 years (range 16 to 92 years) in this group, and mean body mass index was 24+/-5.6 (range 13 to 53). Measured REE was 1,617+/-355 kcal/day for the entire group, 1,790+/-397 kcal/day in the obese group (n=51), and 1,730+/-402 kcal/day in the critically ill group (n=141). The most accurate prediction was the Harris-Benedict equation when a factor of 1.1 was multiplied to the equation (Harris-Benedict 1.1), but only in 61% of all the patients, with significant under- and over-predictions. In the patients with obesity, the Harris-Benedict equation using actual weight was most accurate, but only in 62% of patients; and in the critically ill patients the Harris-Benedict 1.1 was most accurate, but only in 55% of patients. The bias was also lowest with Harris-Benedict 1.1 (mean error -9 kcal/day, range +403 to -421 kcal/day); but errors across all equations were clinically unacceptable. CONCLUSIONS: No equation accurately predicted REE in most hospitalized patients. Without a reliable predictive equation, only indirect calorimetry will provide accurate assessment of energy needs. Although indirect calorimetry is considered the standard for assessing REE in hospitalized patients, several predictive equations are commonly used in practice. Their accuracy in hospitalized patients has been questioned. This study evaluated several of these equations, and found that even the most accurate equation (the Harris-Benedict 1.1) was inaccurate in 39% of patients and had an unacceptably high error. Without knowing which patient's REE is being accurately predicted, indirect calorimetry may still be necessary in difficult to manage hospitalized patients.     

Validation of a new method for estimating resting energy expenditure of non-ambulatory tube-fed patients with severe neurodevelopmental disabilities

OBJECTIVE: We assessed the bias and precision of the Arlington Developmental Center (ADC) equations derived from our previous study and the Harris-Benedict equations for estimating resting energy expenditure in non-ambulatory, tube-fed patients with severe neurodevelopmental disabilities. METHODS: Fifteen non-ambulatory patients with neurodevelopmental disabilities referred to the nutrition consult service for evaluation of enteral tube feeding via a permanent ostomy who had a steady-state resting energy expenditure measurement performed by indirect calorimetry were included in the study. The predicted energy expenditure values were compared with the measured resting energy expenditure values and evaluated for bias and precision. RESULTS: Both ADC equations were more precise (95% confidence interval [CI]: 9-22% and 10-18% error, respectively) for the total population than the Harris-Benedict equations (95% CI: 17-40% error). The ADC-2 equation was precise (95% CI: 7-15% error) and unbiased (95% CI: -5 to 139 kcal/d) in contrast to the Harris-Benedict equations (95% CI: 23-54% error; bias, +230 to 365 kcal/d) for patients with cerebral palsy and fixed upper extremity contractures. The Harris-Benedict equations were precise and unbiased (95% CI: 3-14% error; bias, -182 to 39 kcal/d) for patients with cerebral palsy with preservation of upper body movement, whereas the ADC equations were biased toward underprediction and associated with greater error (95% CI: -367 to -73 kcal/d and 7-26% error; 95% CI: -379 to -109 kcal/d and 9-27% error, respectively). CONCLUSIONS: The ADC-2 equation was unbiased and more precise in non-ambulatory adult patients with severe neurodevelopmental disabilities and fixed upper extremity contractures, whereas the Harris-Benedict equations were more precise and unbiased for those with preservation of limited functional and non-functional upper extremity movement.     

The effect of severe undernutrition and subsequent refeeding on whole-body metabolism and protein synthesis in human subjects

BACKGROUND: To determine the consequences of severe undernutrition and refeeding on whole-body metabolism and protein synthesis. METHODS: Respiratory quotient (RQ), resting energy expenditure (REE), and whole-body protein synthesis (WBPS) were assessed in undernourished patients, with anorexia nervosa (n = 8) or with coexistent disease (n = 17). Results were compared with 17 healthy controls. Six anorexic patients and 13 disease patients consented to study after nutrition support. RESULTS: Mean body mass index was 12.46 +/- 0.53 kg/m2 in the anorexia patients and 13.81 +/- 0.40 kg/m2 in the disease patients (controls 23.71 +/- 0.72 kg/m2; p < .001). Compared with controls, RQ was similar in anorexia patients (0.85 +/- 0.05 vs 0.90 +/- 0.05) but lower in the disease patients (0.76 +/- 0.03 vs 0.90 +/- 0.05; p = .02). REE was lower in the patients (anorexia 1058 +/- 134.0 kcal/d, disease 1189 +/- 101.4 kcal/d vs 1828 +/- 89.76 kcal/d; p < .001); however, expressed as kcal/kg/d, it was higher (anorexia 32.17 +/- 4.25, disease 31.30 +/- 2.14 vs 25.07 +/- 1.00; p < .05). WBPS was lower in the patients (anorexia 140.9 +/- 10.54 g/d, disease 119.8 +/- 8.57 g/d vs 305.0 +/- 21.64 g/d; p < .001); however, when expressed as g/kg/d, the anorexia patients were similar to controls, whereas the disease patients were lower (3.11 +/- 0.24 vs 4.27 +/- 0.32; p < .05). Refeeding increased RQ in the disease patients (0.84 +/- 0.03 vs 0.76 +/- 0.03; p < .05), and normalized REE (anorexia 27.65 +/- 3.05 kcal/kg/d, disease 28.90 +/- 1.85 kcal/kg/d). WBPS increased in the disease patients (173.6 +/- 16.38 g/d vs 116.5 +/- 10.15 g/d; p < .01). CONCLUSIONS: Undernutrition is associated with increased REE (kcal/kg/d). Reduction in RQ and protein synthesis (g/kg/d) was evident in those patients with coexistent disease. Refeeding resulted in normalization of RQ, REE (kcal/kg/d), and protein synthesis (g/kg/d).     

Energy expenditure in children with severe head injury: lack of agreement between measured and estimated energy expenditure.

BACKGROUND: The purpose of this study was to test the hypotheses that estimates of resting energy expenditure (REE) vary significantly from measured energy expenditure in a population of head-injured children and are not accurate for use in determining nutrition needs in this population. METHODS: This is a retrospective study of 30 children with severe head injury, with Glasgow Coma Scale (GCS) score of <8 and needing mechanical ventilation. Measured REE was obtained using indirect calorimetry. Estimated REEs were calculated using Harris-Benedict, World Health Organization (WHO), Schofield, and White formulas. Severity of illness was calculated using Pediatric Risk of Mortality (PRISM) score. Agreement between measured REE and estimated REE was tested using the Bland-Altman method. Correlation coefficient between PRISM score and measured REE was calculated using Spearman test. RESULTS: More than half of the estimates of REE differed from measured REE by >10%. Significant disagreement between estimated REE and measured REE was demonstrated using the Bland-Altman method. There was no correlation between severity of illness and measured REE to explain the inaccuracies of REE estimates. CONCLUSION: Energy expenditure in critically ill children cannot be estimated accurately; hence, nutrition for critically ill children with head injury should be provided according to measurement of REE to avoid the consequences of overfeeding or malnutrition.     

Resting energy expenditure in patients with isolated head injuries and spontaneous intracranial haemorrhages

Indirect calorimetry was performed during the first seven days in 39 neurosurgical patients with isolated head injuries (N = 20) and with spontaneous intracranial haemorrhage (N = 19). All patients were artificially ventilated and received total parenteral nutrition during the whole study period. In the trauma group resting energy expenditure (REE) varied from 473-2172 kcal/m(2)/day and in patients with spontaneous haematomas from 552-1591 kcal/m/day. These were 56-265% (trauma) and 61-192% (spontaneous haemorrhages) of predicted basal metabolic rates (BMR). Patients with head injuries showed higher REE values than patients with spontaneous haemorrhage, which was significant (p < 0.001) for the differences between the two study groups and for coma grade II patients. Deeper coma resulted in lower energy expenditure in patients with head injuries but the decrease was significant only from coma grade I to II. The authors conclude that REE rarely exceeds 30% of predicted BMR in patients with spontaneous haemorrhage and 50% in trauma patients. However, the effect of coma on REE should be taken into account when devising nutritional support in this group of patients.     

Plasma 25‐Hydroxyvitamin D Levels at Initiation of Care and Duration of Mechanical Ventilation in Critically Ill Surgical Patients

Objective: Limited data exist regarding the relationship between plasma 25‐hydroxyvitamin D levels and duration of respiratory support. Our goal was to explore whether vitamin D status at the time of intensive care unit (ICU) admission is associated with duration of mechanical ventilation in critically ill surgical patients. Materials and Methods: We analyzed data from a prospective cohort study involving 210 critically ill surgical patients. To explore the relationship between admission plasma 25‐hydroxyvitamin D levels and duration of mechanical ventilation, we performed a Poisson regression while controlling for clinically relevant covariates. Only patients who required ≥48 hours of mechanical ventilation and survived ≥24 hours after discontinuation of respiratory support were included in the analytic cohort. Results: Ninety‐four patients met inclusion criteria. Mean (standard deviation) plasma 25‐hydroxyvitamin D level was 16 (7) ng/mL and median (interquartile range) duration of mechanical ventilation was 4 (2–7) days. Poisson regression analysis, adjusted for age, sex, race, body mass index, primary surgical service, Acute Physiology and Chronic Health Evaluation II score, and season of ICU admission, demonstrated an inverse association of plasma 25‐hydroxyvitamin D levels with duration of mechanical ventilation (incident rate ratio per 10 ng/mL, 0.66; 95% confidence interval, 0.54–0.82). Conclusions: In our cohort of critically ill surgical patients, plasma 25‐hydroxyvitamin D levels measured on ICU admission were inversely associated with the duration of respiratory support. Randomized controlled trials are needed to assess whether vitamin D supplementation can influence duration of mechanical ventilation in surgical ICU patients.     

Energy expenditure in patients with multiple organ failure

We measured the level of resting energy expenditure (BEE) and its evolution in patients with multiple organ failure (MOF). We studied 30 patients requiring mechanical ventilation and sedation. REE was measured by means of a closed circuit method on days 1-5, 7, 10 and 14 after initiating the protocol. REE values between 115% and 145% of the REE calculated from the Harris-Benedict's formula were considered as moderate hypermetabolism and values above 145% as severe hypermetabolism. A predictive formula for determining caloric requirements was developed and validated in another 25 MOF patients. In the study group, 25 patients presented moderate hypermetabolism (83%) and two severe hypermetabolism(7%). Mean REE in the whole group was stable but individual patients may have had a large variability in REE. The anthropometric variables, body temperature and reason for admission predicted the REE with a coefficient of determination of 0.73, according to the model: REE= -3295 + 105.5S - 8A + 11.7 W + 7.7 H + 93.2 T + 123.1 Tr - 145.6 Su where: S = sex (male = 1, female = 0); A: age in years; W: weight in Kg; H: height in cm; T: temperature in degrees C; Tr: trauma (Tr = 1); Su: surgical (Su = 1). The reliability of the model, taken from the validation group, showed that the shrinkage was 0.8%. In conclusion, when MOF patients are sedated they present moderate hypermetabolism. Day-to-day variability of REE in the individual patients and the large variability in estimating REE with our formula preclude its clinical utility and we recommend to measure REE in MOF patients.     

Short-term overfeeding increases resting energy expenditure in patients with HIV lipodystrophy

BACKGROUND: HIV lipodystrophy and other lipodystrophy syndromes are characterized by extensive loss of subcutaneous adipose tissue. Lipodystrophy syndromes are also associated with increased resting energy expenditure (REE). This hypermetabolism may be an adaptive response to an inability to store triacylglycerol fuel in a normal manner. OBJECTIVE: This study was done to determine whether REE increases significantly after short-term overfeeding in patients with HIV lipodystrophy. DESIGN: REE was measured in HIV-infected patients with lipodystrophy (n = 9) and in HIV-infected (n = 10) and healthy (n = 9) controls after 3 d on a eucaloric diet and again after 3 d on a diet of similar composition but increased in calories by 50%. RESULTS: After 3 d of eucaloric feeding, REE was significantly higher in patients with HIV lipodystrophy [33.2 +/- 0.27 kcal/kg lean body mass (LBM)] than for both HIV-infected and healthy controls (29.9 +/- 0.26 and 29.6 +/- 0.27 kcal/kg LBM, respectively; P < 0.01). Furthermore, after 3 d of overfeeding, REE increased significantly in patients with HIV lipodystrophy but not in the control groups (33.2 +/- 0.27 vs 34.7 +/- 0.27 kcal/kg LBM; P < 0.01). Finally, postprandial thermogenesis did not differ among the groups after a "normal" test meal but tended to be higher in patients with HIV lipodystrophy than in healthy controls after a large test meal. CONCLUSIONS: Adaptive thermogenesis in the resting component of total daily energy expenditure and in the postprandial period may be a feature of the HIV lipodystrophy syndrome and may be due to an inability to store triacylglycerol fuel in a normal manner.     

How Accurate Are Resting Energy Expenditure Prediction Equations in Obese Trauma and Burn Patients?

BACKGROUND: While the prevalence of obesity continues to increase in our society, outdated resting energy expenditure (REE) prediction equations may overpredict energy requirements in obese patients. Accurate feeding is essential since overfeeding has been demonstrated to adversely affect outcomes. OBJECTIVES: The first objective was to compare REE calculated by prediction equations to the measured REE in obese trauma and burn patients. Our hypothesis was that an equation using fat-free mass would give a more accurate prediction. The second objective was to consider the effect of a commonly used injury factor on the predicted REE. METHODS: A retrospective chart review was performed on 28 patients. REE was measured using indirect calorimetry and compared with the Harris-Benedict and Cunningham equations, and an equation using type II diabetes as a factor. Statistical analyses used were paired t test, +/-95% confidence interval, and the Bland-Altman method. RESULTS: Measured average REE in trauma and burn patients was 21.37 +/- 5.26 and 21.81 +/- 3.35 kcal/kg/d, respectively. Harris-Benedict underpredicted REE in trauma and burn patients to the least extent, while the Cunningham equation underpredicted REE in both populations to the greatest extent. Using an injury factor of 1.2, Cunningham continued to underestimate REE in both populations, while the Harris-Benedict and Diabetic equations overpredicted REE in both populations. CONCLUSIONS: The measured average REE is significantly less than current guidelines. This finding suggests that a hypocaloric regimen is worth considering for ICU patients. Also, if an injury factor of 1.2 is incorporated in certain equations, patients may be given too many calories.     

Resting Energy Expenditure in Critically Ill Patients With Spontaneous Intracranial Hemorrhage

Background: Data on energy requirements of patients with spontaneous intracranial hemorrhage (SICH) are scarce. The objective of this study was to determine the resting energy expenditure (REE) in critically ill patients with SICH and to compare it with the predicted basal metabolic rate (BMR). Methods: In 30 nonseptic patients with SICH, the REE was measured during the 10 first posthemorrhage days with the use of indirect calorimetry (IC). Predicted BMR was also evaluated by the Harris‐Benedict (HB) equation. Bland‐Altman analysis was used to evaluate the agreement between measured and predicted values. The possible effect of confounding factors (demographics, disease, and severity of illness score) on the evolution of continuous variables was also tested. Results: mean predicted BMR, calculated by the HB equation, was 1580.3 ± 262 kcal/d, while measured REE was 1878.9 ± 478 kcal/d (117.5% BMR). Compared with BMR, measured REE values showed a statistically significant increase at all studied points (P < .005). Measured and predicted values showed a good correlation (r = 0.73, P < .001), but the test of agreement between the 2 methods with the Bland‐Altman analysis showed a mean bias (294.6 ± 265.6 kcal/d) and limits of agreement (–226 to 815.29 kcal/d) that were beyond the clinically acceptable range. REE values presented a trend toward increase over time (P = .077), reaching significance (P < .005) after the seventh day. Significant correlation was found between REE and temperature (P = .002, r = 0.63), as well as between REE and cortisol level (P = .017, r = 0.62) on the 10th day. No correlation was identified between REE and depth of sedation, as well as Acute Physiology and Chronic Health Evaluation II, Glasgow Coma Scale, and Hunt and Hess scores. Conclusions: During the early posthemorrhagic stage, energy requirements of critically ill patients with SICH are increased, presenting a trend toward increase over time. Compared with IC, the HB equation underestimates energy requirements and is inefficient in detecting individual variability of REE in this group of patients.