Malnutrition, nutritional indices, and early enteral feeding in critically ill children

APPLIED NUTRITIONAL INVESTIGATION

Malnutrition, Nutritional Indices, and Early Enteral Feeding in Critically Ill Children George Briassoulis, MD, PhD, Nikos Zavras, MD, PhD, and Tassos Hatzis, MD, PhD From the Pediatric Intensive Care Unit, “Aghia Sophia” Children’s Hospital, Athens, Greece We measured the incidences of protein and fat depletions and the frequencies of acute and chronic protein– energy malnutrition during stress states in children and investigated the influence of early enteral feeding on nutrition indices and acute-phase proteins. Seventy-one, consecutively enrolled, critically ill children received early enteral feeding (energy intakes equal to 0.50, 1, 1.25, 1.5, and 1.5 of the predicted basal metabolic rates on days 1 through 5, respectively) through nasogastric tubes. On the first day of the study, 16.7% of the patients already were depleted of protein and 31% of fat stores. Overall, 16.9% were at risk for chronic protein– energy malnutrition and 21.1% for acute protein– energy malnutrition, whereas 4.2% and 5.6% already had chronic and acute, respectively protein– energy malnutrition. Only 22.7% of patients without protein deficiencies versus 37% of those at risk or already deficient developed multipleorgan system failure. Transferrin and prealbumin levels improved at the end of the period of early enteral feeding (187 ⫾ 6.6 versus 233 ⫾ 7 mg/dL, P ⬍ 0.0001; 15.1 ⫾ 2 versus 21.9 ⫾ 2.9 mg/dL, P ⬍ 0.0001; respectively); survivors had higher prealbumin levels than non-survivors (22.3 versus 15.5 mg/dL). With logistic regression analysis, only repleted energy, not anthropometric or nutrition indices, was independently associated with survival (P ⫽ 0.05). These results reinforce the observation that critically ill children are at risk for fat or protein depletion and development of malnutrition, which is associated with increased morbidity and mortality. We conclude that early enteral nutrition improves nutrition indices and outcomes. Nutrition 2001;17:548 –557. ©Elsevier Science Inc. 2001 KEY WORDS: nutrition, malnutrition, critically ill, children, enteral feeding, fat stores, protein stores

INTRODUCTION Critically ill children are at increased risk for malnutrition, shortterm morbidity, and mortality. Acute (APEM) or chronic (CPEM) protein– energy malnutrition reduces the number and function of T cells, phagocytic cells, and secretory immunoglobulin-A antibody response.1 In addition, levels of many complement components are reduced, and deficiencies of trace minerals and vitamins are associated with profound impairment of cell-mediated immunities such as lymphocyte stimulation response, decreased ratios of CD4⫹ to CD8⫹ cells, and decreased chemotaxis of phagocytes. The metabolic demands of critical illness and underfeeding can cause malnutrition in seriously ill children. In particular, APEM in critically ill children has been associated with increased physiologic instability and increased quantity of care.2 In addition, malnutrition and nutrient deficiencies are common early in the course of critical illnesses in children.3 However, there are no firm data on the nutrition requirements for critically ill patients during the different stages of illness. Some investigators have suggested that no nutrition support for the first week or two is not harmful and might be better than inappropriate nutrition support with all its risks.4 In an adult, however, during the first 24 h of fasting, about 300 kcal of protein and 1600 kcal of fat are consumed. The body breaks down its own reserves to supply energy and precursors for the synthesis of glucose. Because autocannibalism can continue

Correspondence to: George Briassoulis, MD, PhD, Pediatric Intensive Care Unit, “Aghia Sophia” Children’s Hospital, Levadias and Thivon Streets, 11527 Athens, Greece. E-mail: [email protected] Date accepted: January 19, 2001 Nutrition 17:548 –557, 2001 ©Elsevier Science Inc., 2001. Printed in the United States. All rights reserved.

undetected, substrate supply can rapidly become insufficient to support local organ and overall energy needs. It has been estimated that an organism dies after using 80% of its fuel reserves. Thus, complete starvation in healthy adults results in death within approximately 70 d.5 In children, that period is considerably reduced, because of smaller body stores, to approximately 32 d for a full-term infant and 5 d for a preterm infant.6 Disease and malnutrition can accelerate the negative consequences of starvation or semistarvation.7 Studies on stressed patients have shown that lack of adequate nutrition worsened the outcome of the critical underlying diseases and contributed to increased mortality and morbidity.8 Reports of poor provision of nutrition in intensive-care units and evidence of malnutrition in critically ill patients are still frequent.9 In pediatric intensive-care units (PICUs), nutrition support in malnourished patients during the acute phase of stress remains a major clinical challenge. Recent significant changes have included a major emphasis on enteral feeding to maintain intestinal absorptive, immune, and barrier functions.10 Although the nature of fuel use in critically ill children has not been defined, recent work has shown that use of carbohydrate and fat was not significantly different in patients with positive or negative nitrogen balance; however protein use was significantly higher in those patients with negative nitrogen balance.11 Studies in adult patients have shown that early enteral feeding (EEF) can reduce or prevent the vicious circle of malnutrition-related morbidity, stimulate immune response, and result in fewer infections in the critically ill.12,13 Our aims were to 1) measure the incidence of protein and fat depletions and the frequency of protein– energy malnutrition in stressed children, 2) examine the relation of severity of illness or other clinical variables, such as comorbidity, origin, and myocardial ejection (EF) and shortening fractions (SF), to the variation of 0899-9007/01/$20.00 PII S0899-9007(01)00578-0

Nutrition Volume 17, Numbers 7/8, 2001

Malnutrition and Nutrition in Critically Ill Children

549

nutrition indices, and 3) investigate the influence of a protocol of EEF on nutrition indices and acute-phase proteins in critically ill children.

equations based on data from indirect calorimetric studies as modified by Seashore18:

MATERIALS AND METHODS

Energy and protein intakes were calculated daily from each patient’s chart. Recommended dietary allowances were estimated by using the tables provided by the Food and Nutrition Board National Research Council.19

Subjects Seventy-one, mechanically ventilated, critically ill children were enrolled in the study after we received approval from the Ethics Committee of the Institutional Review Board of our institution. Informed consent was obtained from the patients’ parents. Patients were included if 1) their expected PICU dependency was at least 5 d, 2) they were on mechanical ventilation (⬎24 h), 3) they did not have primary renal disease, 4) they had no history of chronic gastrointestinal disease, and 5) their enteral feedings had begun within the first 12 h. All patients were acutely and critically ill and required intubation and mechanical ventilation. Eighteeen (25.4%) patients had sepsis, 29 (40.8%) had brain injuries, 9 (12.7%) had acute respiratory failure (bronchiolitis, acute respiratory distress syndrome, or pneumonia), 7 (9.9%) had neuromuscular disease (Guillain–Barre syndrome, juvenile myasthenia gravis crisis, or myelitis), and 8 (11.3%) had burns. Nine patients had histories of cancer or chronic disease (13% comorbidity). EEF Protocol Nutrison Pediatric or Standard (N.V. Nutricia, Zoetermeer, Holland) formula was delivered through nasogastric tubes, starting within the first 12 h of admission. Nutrison Pediatric, proposed for critically ill children up to age 10 y, contained 41% of its energy as lipid; Nutrison Standard, proposed for critically ill children older than 10 y, contained 35% of its energy as lipid. The proportions of essential amino acids from protein were 64% for the Nutrison Pediatric and 48% for the Nutrison Standard (reference amino-acid patterns according to the World Health Organization and the FAO). Hourly EEF amounts were calculated according to a protocol for meeting a patient’s predicted basal metabolic rate (PBMR) by the second day of critical illness and then exceeding that level by 50% while the patient remained in stress (energy intakes equal to 0.50, 1, 1.25, 1.5, and 1.5 of the PBMR on days 1 through 5, respectively). No patient received total parenteral nutrition. Data Collection Collected data were demographics, clinical diagnoses, and vital signs. Patients were classified a priori into the following diagnostic categories: sepsis, brain injury, respiratory failure, neuromuscular disease, and burns. Sepsis, septic shock, and systemic inflammatory response syndrome (SIRS) were defined by using the criteria developed by consensus of the American College of Chest Physicians and the Society of Critical Care Medicine.14 All patients with sepsis and septic shock were classified as the sepsis group. Severity of illness was assessed by the Pediatric Risk of Mortality (PRISM) score,15 the Therapeutic Intervention Scoring System (TISS) modified for children,16 and indices of organ failure. Multiple-organ system failure (MOSF) was defined by using the criteria of Wilkinson et al.17 Upon admission, all patients had bedside, two-dimensional echocardiograms (Ultramark 8 Ultrasound System, Advanced Technology Laboratory, Squibb, WA, USA) with standard views as recommended by the American Society of Echocardiography. Echocardiographic measurements included the objective indices of myocardial contractility, EF and SF, which are thought to be early sensitive markers of illness severity, especially of cardiac performance and thereby splanchnic perfusion, in critically ill patients. We estimated PBMR with

PBMR ⫽ (55 ⫺ [2 ⫻ age in years]) ⫻ weight in kilograms.

Malnutrition and Anthropometry Children were classified as normal, chronically malnourished, or acutely malnourished. CPEM and APEM were evaluated by using weight, recumbent length, and age. Acute nutrition status was evaluated by using the ratio of weight to the 50th percentile weight for length. The degree of APEM was defined by interpreting the Waterlow stages for that ratio20 as previously described3 and shown in the Appendix. Chronic nutrition status was evaluated by using the ratio of length to the 50th percentile length for age. That ratio was placed into Waterlow stages for chronic nutrition status21 and interpreted as previously described3 and shown in the Appendix. The interpretation of the Waterlow stages is consistent with the recommendations of Waterlow et al.22 and is essentially the same as that used by Merrit and Sunkind.23 Anthropometric measurements were midarm circumference (MAC), cutaneous triceps skinfold thickness (TSF), midarmmuscle circumference (MMC), midarm-muscle area (MMA), and midarm-fat area (MFA). Fat stores were measured with TSF and MFA and somatic protein stores with MMC and MMA. Fat and protein stores were classified as normal, nutritionally at risk, or deficient, as defined by Friscancho24 and Ryan and Martinez25 (for the original definitions we used to estimate the nutrition status of our population, see the Appendix). Normal values for weight for length and length for age were derived from the Standards of the National Center of Health Statistics.26 Normal values for TSF, MAC, MMA, and MFA were derived from the Standards of the Ten-State Nutritional Survey.27 All anthropometric measurements were taken at the beginning of enteral feeding and were not repeated because the severity of illness might make repeated measurements unrealistic (development of edema), whereas the feeding period was too brief to cause significant alterations. Metabolic Response to Stress Mediators Blood samples were drawn on days 1 and 5 of EEF. The measured stress mediators were the acute-phase proteins C-reactive protein (CRP) and fibrinogen. Among the biochemical indices of nutrition assessment, we measured visceral levels of albumin, prealbumin, and transferrin. To interpret sequential measurements with changes in the magnitude of the acute-phase reaction, we used a modified form of the Prognostic Inflammatory and Nutritional Index (PINI), a quantitative way of monitoring the relation between “nutrition” markers and acute proteins28: PINI ⫽

(CRP ⫻ fibrinogen) (transferrin ⫻ prealbumin).

Statistical Analysis Normally distributed data are expressed as means ⫾ standard errors of the mean, and non-normally distributed data are expressed as medians and ranges. Statistical analysis was performed with a two-tailed t test for normally distributed, paired data after using Levene’s correction for equality of variances or the Mann– Whitney U and Wilcoxon rank-sum test for non-normally distributed data. One-way analysis of variance was used to compare PINI data across groups. Probability values below 0.05, two-tailed, were

550

Briassoulis et al.

Nutrition Volume 17, Numbers 7/8, 2001

considered significant. When a linear regression was calculated, we used Pearson’s correlation coefficient. Pearson’s chi-square or Fisher’s exact test was used for category data. Multivariate stepwise regression analysis was used to analyze the contribution of the clinical factors—myocardial contractility, anthropometry, and severity of illness—to the variations of nutrition and stress indices. All analyses were done with the Statistical Package for the Social Sciences for Windows (version 8.0, SPSS, Chicago, IL, USA) software.

RESULTS Clinical Characteristics Seventy-one critically ill children (age range ⫽ 2 mo to 17 y, mean ⫾ standard error of the mean ⫽ 71.8 ⫾ 6.8 mo) were in the study. The ratio of males to females was 1.29 to 1. Fifteen patients (21.1%) were admitted directly to the PICU by way of the emergency department, 14 (19.7%) were transferred to wards and subsequently required PICU admission, 5 (7%) were admitted to the PICU because of operations, and 37 (52.1%) were transferred directly to the PICU from peripheral hospitals. Twelve patients had undergone surgery (16.9%). Mean PRISM score on admission was 12.8 ⫾ 0.84 and mean TISS was 27 ⫾ 0.9. Twenty patients developed MOSF (28.2%). The duration of mechanical ventilation was 7 ⫾ 0.9 d (median ⫽ 5 d, range ⫽ 1– 60 d), and mean length of stay in the PICU was 11.8 ⫾ 1.3 d (median ⫽ 8 d, range ⫽ 5–70 d). Four patients (5.6%) died.

Anthropometry At admission, the percentages were 94 for ideal body weight and 96 for ideal body height. Interestingly, 76% of our patients had ideal fat and 62% had ideal lean body mass for their ages. Most did not have comorbidity (cancer or chronic disease in 13% of the total population), which was significantly correlated to the depletion of fat and protein (P ⬍ 0.02). On the first day of the study, 12 patients (16.7%) had depleted fat, 22 (31%) had depleted protein stores, and 5 (7%) were at risk for depletion of fat or protein stores. Overall, 12 patients (16.9%) were at risk for CPEM and 15 (21.1%) for APEM, 3 (4.2%) had CPEM, and 4 (5.6%) had APEM (Fig. 1).

Nutrition Indices and Stress Mediators One hundred forty-two measurements were made in 71 patients. CRP values were higher than the reference values (⬎3.4 mg/L) in 80% of patients on days 1 and 5 and above 60 mg/L in 31% and 32% of patients on days 1 and 5, respectively. Fibrinogen levels were below 200 mg/dL in 28% of patients on day 1 but only 16% on day 5. In contrast, 16% of patients had initial fibrinogen levels above 600 mg/dL, but that percentage decreased to 3% by day 5. On day 1, 47.8% of patients had abnormally low transferrin levels (⬍190 mg/dL), but only 16% did by day 5 (Fig. 2, top). Although only 16% and 4% of patients had low prealbumin levels on days 1 and 5, respectively (reference values ⫽ 10 – 40 mg/dL), 77.4% had borderline levels (⬍15 mg/dL) on day 1 and only 18.8% on day 5 (Fig. 2, bottom). Nutrition indices increased significantly by day 5 of EEF, whereas neither stress mediator differed significantly between days 1 and 5 of the study (Table I). Thus, despite the improvement in the nutrition indices and the restoration of low fibrinogen levels, PINI showed a non-significant decline by the end of the EEF. Among the nutrition and stress indices, prealbumin showed a negative correlation to transferrin on days 1 and 5 (r ⫽ ⫺0.30, P ⬍ 0.01, and r ⫽ ⫺0.33, P ⬍ 0.01, respectively), whereas CRP correlated positively to fibrinogen (r ⫽ 0.34, P ⫽ 0.004, and

FIG. 1. Frequency of protein– energy malnutrition, acute (APEM) or chronic (CPEM), in stressed children (for definitions, see Appendix).

r ⫽ 0.35, P ⫽ 0.003, respectively) and negatively to transferrin (r ⫽ ⫺0.25, P ⬍ 0.04, and r ⫽ ⫺0.24, P ⬍ 0.05, respectively; P ⬍ 0.01) on the same days. Relation Between Nutrition and Anthropometry Energy and protein intakes on day 1 were higher in patients with MFAs below the 10th percentile than in those not at risk for fat depletion (28 ⫾ 2.7 versus 21 ⫾ 1 kcal 䡠 kg⫺1 䡠 d⫺1, P ⫽ 0.002, and 0.9 ⫾ 0.1 versus 0.64 ⫾ 0.02 g 䡠 kg⫺1 䡠 d⫺1, P ⬍ 0.03, respectively), and that trend continued throughout the study. Throughout the study, patients at risk for protein depletion did not

Nutrition Volume 17, Numbers 7/8, 2001

Malnutrition and Nutrition in Critically Ill Children

551

TABLE I. PAIRED DIFFERENCES BETWEEN NUTRITION INDICES, STRESS MEDIATORS, AND A MODIFIED NUTRITION INDEX ON POSTSTRESS DAYS 1 AND 5 IN CRITICALLY ILL CHILDREN ON EARLY ENTERAL NUTRITION* Paired samples test Nutrition/stress indices Prealbumin (mg/dL) Transferrin (mg/dL) CRP (mg/dL) Fibrinogen (mg/dL) Nutrition index

Day 1

Day 5

Paired differences

15.1 ⫾ 2 187 ⫾ 6.6 61.4 ⫾ 10 293 ⫾ 18 12.8 ⫾ 2.7

21.9 ⫾ 2.9 233 ⫾ 7 55 ⫾ 8 317 ⫾ 18 7.5 ⫾ 2.1

6.7 ⫾ 1† 45 ⫾ 5.6† 5.9 ⫾ 10 24 ⫾ 22 5.3 ⫾ 3.2

* Mean ⫾ standard error of the mean. † P ⬍ 0.0001. CRP, C-reactive protein.

Relation Between Anthropometric Measurements and Clinical Variables PROTEIN DEPLETION. There was no significant difference in the incidence of protein depletion among diagnostic groups (43% with neuromuscular disease, 33.3% with respiratory failure, 33.3% with sepsis, 27.6% with head injury, and 25% with burns; Fig. 4). Among patients without SIRS, 87% were not at risk for protein depletion versus 68% of those with SIRS (P ⬍ 0.19). Only 10 of 44 (22.7%) patients without protein deficiency developed MOSF, whereas 37% of those at risk or already deficient developed MOSF. Of the patients who transferred directly from the emergency department, 80% were not at risk for developing protein depletion, whereas 60% of those who transferred from other hospitals or the wards were at risk or had developed protein deficiency (P ⫽ 0.14). Patients with comorbidity were at risk, but not significantly, for developing protein deficiency (65.1% versus 37.5% of patients without comorbidity, P ⬍ 0.07). FIG. 2. Incidence of low (⬍190 mg/dL) transferrin (top) and (⬍15 mg/dL) prealbumin (bottom) levels at the beginning and end of a protocol of enteral feeding in critically ill children. *P ⬍ 0.0001.

receive more energy or protein than patients not at risk for depletion. Nutrition Indices, Stress Mediators, and Anthropometry PINI was significantly correlated with protein intake by the end of EEF (r ⫽ 0.23, P ⫽ 0.05; Fig. 3). Neither protein nor energy intake was correlated to transferrin throughout the study. However, the difference of a given recommended dietary allowance for protein was significantly correlated to prealbumin on days 1 (r ⫽ 49, P ⬍ 0.0001) and 5 (r ⫽ 0.25, P ⬍ 0.04). PINI differed among patients with CPEM (lower throughout the study; 13 ⫾ 2.7 versus 0.8 ⫾ 0.5 mg/dL on day 1 and 7.6 ⫾ 2 versus 1 ⫾ 7 mg/dL on day 5 for those with or without CPEM) than among patients with APEM (higher throughout the study; 18.4 ⫾ 14 versus 12 ⫾ 3 mg/dL on day 1 and 9 ⫾ 6 versus 7 ⫾ 2 mg/dL on day 5 for those with or without APEM). Similarly, on day 1, patients who developed protein or fat depletion had lower PINI scores than those who did not (11 ⫾ 2,5 versus 15.7 ⫾ 5.7 mg/dL and 9.6 ⫾ 2 versus 23 ⫾ 9, respectively). Those differences were not statistically significant.

FIG. 3. Correlation of the PINI to protein intake by the end of the early enteral feeding. Lines represent mean fit lines and the 95% regression prediction lines. PINI, Prognostic Inflammatory and Nutritional Index

552

Briassoulis et al.

FIG. 4. Critically ill children at risk for protein depletion or depleted at admission, classified in main diagnostic groups.

FAT DEPLETION. Among diagnostic groups at risk for developing fat depletion, 33.3% of patients had sepsis, 29% had burns, and 44.4% had respiratory failure, whereas most of the patients with head injury (93%) or neuromuscular disease (71%) were not at risk for fat deficiency (P ⫽ 0.002). Only 13 of 54 (24%) patients without fat deficiency developed MOSF, whereas 7 of 17 (41.2%) patients at risk or already deficient developed MOSF (P ⫽ 0.14). Of the patients who were transferred directly from the emergency department, 86.7% were not at risk for developing fat depletion, whereas patients transferred from the wards had developed fat deficiency (66.7%; P ⫽ 0.02; Fig. 5). Patients with comorbidity were at risk of developing fat deficiency (63% versus 17% of patients without comorbidity, P ⬍ 0.02; Fig. 6). PROTEIN– ENERGY MALNUTRITION. There was no difference in the incidence of CPEM or APEM between patients with or

FIG. 5. Fat-store status in critically ill children at admission in relation to their places of origin. *P ⬍ 0.02. ED, emergency department; OR, operating room.

Nutrition Volume 17, Numbers 7/8, 2001

FIG. 6. Sixty-three percent of patients with comorbidity versus 17% without comorbidity were at risk of developing fat deficiencies. *P ⬍ 0.02.

without SIRS, MOSF, or septic shock or between survivors and non-survivors. The risk for developing APEM was significantly greater among patients with histories of cancer or chronic disease (P ⬍ 0.02). Only patients transferred from other hospitals or the operating room had CPEM (P ⫽ 0.02). Patients with comorbidity had a higher incidence of CPEM (25%) than those without comorbidity (1.6%; P ⬍ 0.001). Relation Between Stress Mediators and Clinical Variables SEVERITY OF ILLNESS. We found a negative correlation between initial (first day in PICU) values of PINI and EF (r ⫽ ⫺0.44, P ⫽ 0.01) or SF (r ⫽ ⫺0.41, P ⫽ 0.02; Fig. 7). Initial CRP also was significantly correlated to EF (r ⫽ ⫺0.45, P ⬍ 0.0001), SF (r ⫽ ⫺41, P ⬍ 0.0001), and the probability of death based on

FIG. 7. Correlation between the initial Prognostic Inflammatory and Nutritional Index score and myocardial contractility as examined by ejection (EF; P ⬍ 0.01) and shortening fractions (SF; P ⬍ 0.02).

Nutrition Volume 17, Numbers 7/8, 2001

Malnutrition and Nutrition in Critically Ill Children

553

FIG. 9. Differences in Prognostic Inflammatory and Nutritional Index scores between patients with and without multiple-organ system failure on days 1 and 5 of a protocol of early enteral feeding. *P ⬍ 0.01. MSOF, multiple-organ system failure; PINI, Prognostic Inflammatory and Nutritional Index; EEF, early enteral feeling..

transferred from the wards or peripheral hospitals (F ⫽ 3.4, P ⬍ 0.03). MULTIPLE-ORGAN SYSTEM FAILURE. Although PINI differed between patients with and without MOSF on day 1 (28.7 ⫾ 7 versus 6.3 ⫾ 1.8 mg/dL, P ⬍ 0.01), that difference disappeared by the end of EEF (5.6 ⫾ 2 versus 8.2 ⫾ 2.8 mg/dL, P ⬍ 0.6; Fig. 9). Fibrinogen was higher (349 ⫾ 39 versus 270 ⫾ 19 mg/dL, P ⫽ 0.05) and transferrin slightly lower (179 ⫾ 16 versus 190 ⫾ 7 mg/dL) in patients with MOSF than in those without. Outcome

FIG. 8. Differences in Prognostic Inflammatory and Nutritional Index scores between patients with and without systemic inflammatory response syndrome (top) and those with and without septic shock (bottom) on days 1 and 5 of a protocol of early enteral feeding. *P ⬍ 0.02, **P ⬍ 0.001. EEF, early enteral feeding; PINI, Prognostic Inflammatory and Nutritional Index; SIRS, systemic inflammatory response syndrome.

PRISM (r ⫽ 0.28, P ⬍ 0.02) and TISS (r ⫽ 26, P ⬍ 0.03) scores. Similarly, initial fibrinogen levels were negatively correlated to EF (r ⫽ ⫺0.34, P ⫽ 0.005). SIRS, SEPSIS. PINI on day 1 differed between patients with and without SIRS (18.2 ⫾ 4 versus 5.8 ⫾ 1.8 mg/dL, P ⬍ 0.02) and those with and without septic shock (34 ⫾ 8.6 versus 6 ⫾ 1.6, P ⬍ 0.001). These differences, however, disappeared after 5 d of EEF (7.7 ⫾ 2 versus 7.2 ⫾ 4 and 8.6 ⫾ 4 versus 7.1 ⫾ 2, respectively; Fig. 8). In patients with septic shock, stress mediators were significantly higher (CRP: 150 ⫾ 28 versus 35 ⫾ 6 mg/dL, fibrinogen: 409 ⫾ 45 versus 258 ⫾ 17, P ⬍ 0.001) and nutrition indices lower, but not significantly (prealbumin: 11 ⫾ 0.7 versus 16 ⫾ 2.8 mg/dL, P ⬍ 0.4), than in critically ill patients without septic shock. By one-way analysis, only fibrinogen on day 1 differed significantly across diagnostic groups (F ⫽ 10, P ⬍ 0.0001) and transferrin on day 1 across patients admitted directly to PICU or

By completion of the EEF, higher prealbumin levels were found in survivors than in non-survivors (22.3 versus 15.5 mg/dL, P ⫽ 0.6). In addition, 50% of non-survivors had fat or protein depletion, whereas only 16.9% (fat) or 30% (protein) of survivors had depletions. Regression Analysis When multivariate stepwise regression analysis was performed to determine which factors contributed independently to the variation in nutrition indices by the end of the EEF protocol, only protein intake was correlated to the PINI (r2 ⫽ 0.44, P ⬍ 0.0001). Multivariate stepwise regression analysis showed that the development of MOSF (r2 ⫽ ⫺0.35, P ⬍ 0.01), a high TISS score (r2 ⫽ ⫺0.30, P ⬍ 0.02), and a low EF (r2 ⫽ ⫺0.64, P ⬍ 0.001) contributed independently to low transferrin levels on day 5. Similarly, only the development of APEM (r2 ⫽ 0.31, P ⬍ 0.01) contributed independently to fibrinogen levels on day 5. In the logistic regression analysis, only repleted energy, and not anthropometric or nutrition indices, was independently associated with survival (r2 ⫽ 0.23, P ⫽ 0.05). Subpopulations The 25th, 50th, and 75th age percentiles were 24, 54, and 120 mo (mean versus median age ⫽ 6 versus 4.5 y). The differences between mean and median with regard to weight and body-surface

554

Briassoulis et al.

FIG. 10. Histogram of the distribution of body-surface areas of the study population (SPSS frequency procedure).

area did not differ significantly (24 versus 20 kg and 0.87 versus 0.78 m2, respectively); the population showed a rather normal distribution (Fig. 10). When applying regression analysis to different age subpopulations (younger than 2, 6, or 10 y and older than 10 or 12 y), age was not a factor for those younger than 10 y (always among the excluded variables). In that group, only TISS, MOSF, SIRS, and EF were associated independently with malnutrition. Similarly, PRISM, MOSF, and SF were correlated with malnutrition risk in patients older than 10 y. However, age was associated with prealbumin levels on day 5 in patients older than 10 y (P ⬍ 0.001, n ⫽ 15) or younger than 2 y (P ⬍ 0.02, n ⫽ 15). In those younger than 2 y, depletion of fat stores also was significantly associated with low transferrin levels; in those older than 10 y, APEM was associated with low fibrinogen levels (P ⬍ 0.05).

DISCUSSION Disease-related malnutrition occurs frequently in infants and children, often with more rapid, obvious, and detrimental consequences than in adults. A number of studies have shown that children with newly diagnosed diseases already may be malnourished.29 In critically ill children, the development of malnutrition is even more rapid because an abnormal response to nutrition support is a characteristic of a stress condition. That stress is related mainly to the metabolic alterations that occur in critically ill children, the so-called acute-phase response.30 Thus, nutrient deficiencies and APEM have been reported to be common early in the course of critical illnesses in children, especially in those younger than 2 y.3 Recent studies compared with similar surveys performed up to three decades previously have reported little improvement in nutrition status in pediatric populations in the interim.31 Even today, in the sickest patients with the lowest energy expenditure, energy intake is lower than energy requirements.32 Our patients’ median age (54 mo) shows that a substantial number of our patients was in the high-risk group. Despite a seemingly heterogeneous population, because of the age variation and the discrepancy between the mean and median ages, weight and body-surface area had approximately normal distributions. In fact, the age variation in this study was representative of the PICU population. Regression analysis, however, showed that severity of illness, as assessed by many well-known severity-scoring systems or clinical and laboratory

Nutrition Volume 17, Numbers 7/8, 2001 indices of organ or myocardial failure and systemic inflammatory response (PRISM, TISS, MOSF, SIRS, EF, and SF), rather than age is the main contributing factor to development of malnutrition in critically ill children. In the current study, 9.8% of patients already had CPEM or APEM, 16.9% were at risk for CPEM, and 21.4% were at risk for APEM sometime during the acute phase of the stress state. These findings are in accordance with those of previous studies reporting that 16% to 20% of critically ill, hospitalized children develop significant APEM, some within 48 h of admission to a PICU.2,3 CPEM also occurs in 1% to 20% of critically ill children within 48 h of admission to a PICU.3 Consequences of the metabolic response to stress include the release of cytokines, glucocorticoids, catecholamines, insulin, and insulin-like growth factors, the balance of which may be crucial in regulating the body’s ability to generate an anabolic response.33 Especially in metabolic response to stress, priorities in liver synthesis are modified, with preferential production of acute-phase proteins (such as CRP and fibrinogen) and inhibition of albumin synthesis.34 In addition, lean tissue is catabolized to provide energy substrates for wound and inflammatory reactions. Those changes are driven by a combination of counterregulatory hormones and the direct and indirect actions of the various inflammatory mediators, prostaglandin, and kallikreins.35 On day 1, a high percentage of patients had significantly increased levels of CRP and very low or high levels of fibrinogen. Further, the trend of increased acute-phase proteins during the rest of the study emphasizes the continuation of the stress state of the study patients. Although albumin is the serum protein most commonly measured for assessment of nutrition status because of its approximately 2-wk half-life and reduced degradation during low intake of protein, a diagnosis of nutrition depletion can be missed or delayed if it is based solely on serum albumin levels. Moreover, patients frequently and repeatedly receive human albumin during the course of a critical illness. Instead, transferrin and prealbumin have significantly shorter half-lives (8 d and 2 to 3 d, respectively), and, presumably, their levels are not directly influenced by human albumin or even fluid status shifts.36 Accordingly, we thought that transferrin and prealbumin would be preferable for nutrition assessment of critically ill patients and used them in the modified PINI formula. Nonetheless, the negative correlation of transferrin to prealbumin was an unexpected finding, possibly related to the significantly different half-lives of the two nutrition markers. We are considering the use of retinol-binding protein instead of transferrin in future studies because it has a half-life closer to that of prealbumin (12 h versus 2 d). In our modified PINI formula, we replaced orosomucoid with fibrinogen, a marker proven to be very sensitive to the stress state of ICU patients. Nowadays, fibrinogen and CRP are measured frequently and routinely for early assessment of the metabolic response to stress in critically ill patients. Low-fat feeding, with or without fish oil, does not change the early production of interleukin-6 after burn injury and interleukin-6 does not appear to directly influence protein metabolism in burn patients.37 In contrast, although our patients were still in stress, nutrition indices increased significantly by day 5 of EEF, reflecting the beneficial influence of early enteral nutrition on the altered metabolism. Although this is not a direct influence because repleted protein did not contribute independently to nutrition indices or mediator stress variation, protein intake on day 5 was significantly correlated to the PINI during the stress state (as reflected by the trend of increased stress mediators). In fact, PINI did not show the variability that the stress mediators and nutrition indices showed throughout the study, so that its trend was quite indicative of the improvement of the stress state. Thus, the PINI score is higher in patients with acute malnutrition than in those with chronic malnutrition; it also is higher among patients with MOSF. Although activation of stress mediators provides adequate conditions for tissue repair and infection control, excessive mediator

Nutrition Volume 17, Numbers 7/8, 2001 release can harm by promoting multiple-organ dysfunction syndrome.38 Thus, initial PINI values were significantly correlated to myocardial contractility, whereas MOSF, a high TISS score, and a low EF contributed independently to the low levels of transferrin on day 5. Interestingly, despite the completion of EEF, development of APEM contributed independently to fibrinogen levels throughout the study. For a number of reasons, malnutrition is an important complication in children undergoing intensive treatment for critical illness. The high depletion rate of protein and fat early in our critically ill patients might be explained by the rapidly occurring hepatic and renal gluconeogenesis, lipolysis, and ketonemia. Activation of the adrenocortical system may by elicited by stimulation of CRH in the hypothalamus of stressed individuals.39 Acute starvation in critically ill children always leads to accelerated protein-calorie malnutrition, so that acetyl-CoA, derived from fat and ketones, becomes the primary fuel for most tissues. However, in our study population, which was provided early, adequate, nutrition support, APEM developed in only two patients, one with acute respiratory distress syndrome and another with head injury. In contrast, patients with comorbidity or transferred from other hospitals or the operating room had a high incidence of CPEM. Serious losses of lean body mass can occur, with additional depletion of protein or fat when injury or critical illness occurs in nutritionally depleted children (CPEM) or if, as often happens, the course of critical illness becomes protracted. Overall, at admission, 31% and 17% of our critically ill patients already had depletion of protein and fat, respectively, and an additional 14% were at risk for protein or fat depletion. Most of those patients were transferred from other hospitals or the wards or had chronic illness. Infants require 43% of protein as essential amino acids, and children require 36%. The American Academy of Pediatrics recommends that infants receive a minimum of 30% of calories from fat; providing 40% to 50% of energy as fat is desirable at that age. In contrast, children older than 2 y should receive a maximum of 30% of total calories from fat and no more than 10% of calories from saturated or polyunsaturated fat. During critical illness, these needs are increased, with a ratio of non-protein (kilocalories) to nitrogen of 80:1 rather than 150:1. Our patients were fed formulas specific for critical illness and age, and those formulas provided fuel that met not only their bodily requirements by age but also their increased need for protein and fat, as dictated by the stress state. These stressed children, malnourished or not, were successfully fed intragastrically with those formulas as shown by the finding that none of the anthropometric measurements correlated to the success of EEF. Further, patients with fat depletion received more energy than patients with only protein depletion, which may have been random or those children likely tolerated EEF better. However, we wanted to avoid over- and underfeeding. Hypercaloric nutrition increases the physiologic load imposed on the respiratory and cardiovascular systems and can induce dangerous metabolic side effects, whereas prolonged underfeeding promotes malnutrition and its consequences. For this reason, if indirect calorimetry is available in the PICU, direct measurement of energy expenditure is recommended in stressed children with prolonged and complicated evolution. The first day poststress, plasma concentrations of prealbumin and transferrin were low. The high protein intake, however, raised these visceral proteins to normal ranges. Thus, although neither protein nor energy intake was correlated significantly to prealbumin or transferrin, the mean energy intake of 150% of PBMR restored the nutrition indices by the end of the study. In adult patients after major abdominal trauma, traditional nutrition protein markers (albumin, transferrin, and retinol-binding protein) were restored better in those taking EEF than in those taking total parenteral nutrition.12 In this study, the difference of given recommended dietary allowance for protein was significantly correlated to prealbumin levels. Our results are in agreement with those of

Malnutrition and Nutrition in Critically Ill Children

555

a prospective, randomized, controlled study in mechanically ventilated, adult patients with head injury, which showed that patients on enhanced enteral nutrition had a significantly lower ratio of serum concentration of CRP to albumin up to day 6 compared with control patients (fed at lower rates).40 Similarly, stressed surgical patients receiving early enteral nutrition with various formulas showed increases in serum total protein, albumin, and transferrin concentrations within 7 d of feeding.41 Further, patients receiving an “immune-enhancing” diet had significantly greater increases in total lymphocytes, T lymphocytes, and T-helper cells within this short poststress period. In a recent study, however, the course of albumin and prealbumin did not differ between glutamine-enriched and non-enriched enteral nutrition.42 Nonetheless, studies using animal models have shown that manipulating the intake of a wide range of nutrients can modulate many deleterious effects of infective and inflammatory states.43 More experimental studies have shown that, by optimizing dietary regimens, it is possible to improve protein metabolism, as assessed by higher serum albumin levels and better nitrogen balance, during acute illness.44 In this study, stress mediators and nutrition indices of specific subcohorts behaved differently. By the end of EEF, stress mediators were higher among APEM patients, and nutrition indices were lower in CPEM patients. Failure to feed on some days cannot be compensated for by subsequent overfeeding and will result in progressive wasting until convalescence starts.45 Similarly, patients who developed protein depletion had lower nutrition-index levels than patients who did not. In patients with fat depletion, nutrition indices were lower on day 1 of the study. High-risk patients with comorbidity, sepsis, or MOSF or who were transferred from other hospitals or the wards had developed protein deficiency or were at risk for doing so. At high risk for developing fat depletion were patients with sepsis and burns and those transferred from the wards or other hospitals. Patients with comorbidity or MOSF also were at risk of developing fat deficiency. Glucose administration during severe disease does not adequately suppress lipolysis. Fat continues to be a significant contributor to energy production in fed, stressed, adult patients.46 One study did not report whether the severity of illness was the cause or the effect of poor nutrition status.3 As shown by the high PINI values in this study, patients with SIRS, septic shock, or MOSF had ongoing stress stimulation and suppressed metabolism. Although the gastrointestinal tract was thought to be the ongoing inflammatory stimulus and the cause of MOSF,47 recent work has suggested that susceptibility to MOSF is determined genetically, with some individuals having an inherent disposition to release massive amounts of proinflammatory cytokines in response to pathologic stimuli.48 Such a hypothesis does not preclude a favorable influence of EEF on outcome. With EEF, our patients’ metabolic status, expressed by the PINI, normalized, approaching the response of their counterparts without SIRS, septic shock, or MOSF in less than 1 wk. Similarly, early and aggressive enteral feeding after major abdominal injury has been shown to diminish the incidence of major septic complications.49 Given the importance of splanchnic ischemia and reperfusion in shock states, enteral nutrition may have a cytoprotective effect by enhancing or maintaining splanchnic blood flow. Thus, we observed a negative correlation between initial values of PINI and EF or SF. The improvement of the PINI values in the MOSF group by the end of the EEF also may have been related to the influence of EEF on the splanchnic blood flow. Although EEF did not improve splanchnic blood flow in the setting of uncorrected hypovolemia or inadequate cardiac output, nutrients within the lumen of the gastrointestinal tract might preserve blood flow, which could have important implications for the prevention of mucosal breakdown and stress ulceration. If recovery from the underlying disease is delayed, nutritional wasting and tissue losses can become severe enough to compro-

556

Briassoulis et al.

Nutrition Volume 17, Numbers 7/8, 2001

mise survival. Adult ICU patients who were malnourished (43%, based on weight:height ratio) had longer hospitals stays and greater incidence of complications than the well-nourished patients.50 In particular, reduction in heart volume, cardiac muscle mass, diaphragm muscle mass, respiratory muscle strength, and maximal voluntary ventilation have been reported in malnourished patients secondary to disease.51 Also, data exist showing that parameters of cell-mediated immune function are impaired as a consequence of disease processes and malnutrition.52 Previous studies in adults have shown that malnourished patients are 4 to 20 times more likely to die than well-nourished patients.53 Mortality has been significantly associated with APEM in critically ill children.2 Those observations are in agreement with the present findings, in which half of the non-survivors had fat or protein depletion. However, enteral-nutrition regimens were effective in preventing or reversing APEM or CPEM and preventing treatment delays in children newly diagnosed with advanced cancer.54 Further, in our study in critically ill children, survivors had higher prealbumin levels after 5 d of aggressive EEF. Thus, only repleted energy was independently associated with survival in those patients, irrespective of their nutrition status. In conclusion, our data show that critically ill children are at risk for fat or protein depletion and development of malnutrition. Malnutrition is associated with increased morbidity and mortality. Anthropometry and other clinical factors interfere with the metabolic response to stress. Early enteral nutrition contributes to the improvement of nutrition indices and outcome.

APPENDIX RELATIVE RISK CRITERIA FOR MALNUTRITION Waterlow stage*

APEM† CPEM‡

0

1

2

3

ⱖ90% ⬎95%

80–89% 90–95%

70–79% 85–89%

ⱕ69% ⬍85%

* Each stage represents approximately one standard deviation from the population median. Patients are classified by these criteria as APEM or CPEM if they are at least two standard deviations from the median (stages 2 and 3). † Weight for height ⫽ actual weight/50th percentile weight for subject’s height and age. ‡ Height for weight ⫽ subject’s height/50th percentile height for subject’s age. APEM, acute protein– energy malnutrition; CPEM, chronic protein– energy malnutrition; 0, normal; 1, at risk; 2, at greater risk; 3, malnourished (APEM) or stunted (CPEM).

NUTRITION-STATUS ASSESSMENT Midarm circumference Midarm area Somatic protein stores Midarm-muscle circumference Midarm-muscle area Fat stores Triceps skinfold thickness Midarm-fat area Percentiles* ⱖ10 (normal)

MAC MMA (mm2) ⫽ ␲/4 ⫻ (MAC/␲)2 MMC (cm) ⫽ MAC ⫺ (0.0314 ⫻ TSF) MMA (mm2) ⫽ (MAC ⫻ 10␲ TSF)2/4␲ TSF (mm) MFA (mm2) ⫽ MAA ⫺ MMA 5–10 (at risk) ⬍5 (deficient)

* From Friscancho24 and Ryan and Martinez.25

REFERENCES 1. Chandra RK. Nutrition and immunology: from the clinic to cellular biology and back again. Proc Nutr Soc 1999;58:681 2. Pollack MM, Ruttimann UE, Wiley JS. Nutritional depletions in critically ill children: associations with physiologic instability and increased quantity of care. JPEN 1985;9:309 3. Pollack MM, Wiley JS, Holbrook PR. Early nutritional depletion in critically ill children. Crit Care Med 1981;9:580 4. Koretz RL. Nutritional supplementation in the ICU. How critical is nutrition for the critically ill? Am J Respir Crit Care Med 1995;151:570 5. Allison SP. The uses and limitations of nutritional support. Clin Nutr 1992;11: 319 6. Thomas B. Enteral feeding in pediatric patients. In: Thomas B, ed. Manual of dietetic practice, 2nd ed. Oxford: Backwell Scientific Publications, 1994:76 7. Green CJ. Existence, causes and consequences of disease-related malnutrition in the hospital and the community, and clinical and financial benefits of nutritional intervention. Clin Nutr 1999;18(suppl 2):3 8. De Deyne C, De Jongh R, Merckx L, Deghislage J, Heylen R. Early enteral feeding in cranial trauma. Ann Fr Anesth Reanim 1998;17:192 9. Wise J. Patients go hungry in British hospitals. BMJ 1997;314:752 10. Ziegler TR. New developments in specialized mutrition support. In: Bion JF, Burchardi H, Dellinger RP, Dobb GJ, eds. Current topics in intensive care. London: Saunders, 1995:144 11. Joosten KF, Verhoeven JJ, Hazelzet JA. Energy expenditure and substrate utilization in mechanically ventilated children. Nutrition 1999;15:444 12. Moore FA, Moore EE, Jones TN, McCroskey BL, Peterson VM. TEN versus TPN following major abdominal trauma—reduced septic morbidity. J Trauma 1989;29:916 13. Singh G, Ram RP, Khanna SK. Early postoperative enteral feeding in patients with nontraumatic intestinal perforation and peritonitis. J Am Coll Surg 1998; 187:142 14. Members of the American College of Chest Physicians/Society of Critical Care Medicine Consensus Conference Committee. American College of Chest Physicians/Society cf Critical Care Medicine Consensus Conference: definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. Crit Care Med 1992;20:864 15. Pollack MM, Ruttimann UE, Getson PR. Pediatric risk of mortality (PRISM) score. Crit Care Med 1988;16:1110 16. Keene AR, Cullen DJ. Therapeutic intervention scoring system: update 1983. Crit Care Med 1983;11:1 17. Wilkinson JD, Pollack MM, Glass NL, et al. Mortality associated with multiple organ system failure and sepsis in pediatric intensive care unit. J Pediatr 1987; 111:324 18. Seashore JH. Nutritional support of children in the intensive care unit. Yale J Biol Med 1984;57:111 19. Subcommittee of the RDAs, Food and Nutritional Research Council. Recommended dietary allowances, 10th ed. Washington, DC: National Academy Press; 1989:25 20. Waterlow JC. Classification and definition of protein-calorie malnutrition. Br Med J 1972;3:566 21. Waterlow JC. Note on the assessment and classification of protein-energy malnutrition in children. Lancet 1973;2:87 22. Waterlow JC, Buzina R, Keller W, et al. The presentation and use of height and weight data for comparing the nutritional status of groups of children under the age of 10 years. Bull World Health Organ 1977;55:489 23. Merritt RJ, Suskind RM. Nutritional survey of hospitalized pediatric patients. Am J Clin Nutr 1979;32:1320 24. Friscancho AR. Triceps skinfold and upper arm muscle size norms for assessment of nutritional status. Am J Clinic Nutr 1974;27:1052 25. Ryan A, Martinez GA. Physical growth of infants 7 to 13 months of age: results from a national survey. Am J Phys Anthropol 1987;73:449 26. Hamill PVV, Drizd TA, Johnson CL, Reed RB, Roche AF. National Center for Health Statistics: NCHS growth charts for children birth–18 years, United States. Vital and health statistics, series 11. DHEW Publication 78-1650. Hyattsville, MD: National Center for Health Statistics, 1977 27. Gurney JM, Jelliffe DB. Arm anthropometry in nutritional assessment: Nomogram for rapid calculation of muscle circumference and cross-sectional muscle and fat areas. Am J Clin Nutr 1973;26:912 28. Ingenbleek Y, Carpentier YA. A prognostic inflammatory and nutritional index scoring critically ill patients. Int J Vitam Nutr Res. 1985;55:91 29. Hendrikse WH, Reilly JJ, Weaver LT. Malnutrition in a children’s hospital. Clin Nutr 1997;16:13 30. Pomposelli J, Flores E, Bistrian B. Role of biochemical mediators in clinical nutrition and surgical metabolism. JPEN 1988;12:212

Nutrition Volume 17, Numbers 7/8, 2001 31. Hendricks KM, Duggan C, Gallagher L, et al. Malnutrition in hospitalized pediatric patients. Arch Pediatr Adolesc Med 1995;149:1118 32. Jebb SA. Energy metabolism in cancer and human immuno-deficiency virus infection. Proc Nutr Soc 1997;56:763 33. Chang HR, Bistrian B. The role of cytokines in the catabolic consequences of infection and injury. JPEN 1998;22:156 34. Fleck A, Colley M, Myers MA. Liver export proteins and trauma. Br Med Bull 1985;41:265 35. Baue AE. Nutrition and metabolism in sepsis and multisystem organ failure. Surg Clin North Am 1991;71:549 36. Golden MHN. Transport proteins as indices of protein status. Am J Clin Nutr 1982;35:1159 37. Bernier J, Jobin N, Emptoz-Bonneton A, Pugeat MM, Garrel DR. Decreased corticosteroid-binding globulin in burn patients: relationship with interleukin-6 and fat in nutritional support. Crit Care Med 1998;26:452 38. van der Poll T, Lowry S. Tumor necrosis factor in sepsis: mediator of multiple organ failure or essential part of host defense? Shock 1995;3:1 39. Schwarz MW, Dallman MF, Wood SC. Hypothalamic response to starvation: implications for the study of wasting disorders. Am J Physiol 1996;269:R949 40. Taylor SJ, Fettes SB, Jewkes C, Nelson RJ. Prospective, randomized, controlled trial to determine the effect of early enhanced enteral nutrition on clinical outcome in mechanically ventilated patients suffering head injury. Crit Care Med 1999;27:2525 41. Moore FA, Moore EE, Kudsk KA, et al. Clinical benefits of an immuneenhancing diet for early postinjury enteral feeding J Trauma 1994;37:607 42. Houdijk AP, Nijveldt RJ, van Leeuwen PA. Glutamine-enriched enteral feeding in trauma patients: reduced infectious morbidity is not related to changes in endocrine and metabolic responses. JPEN 1999;23(suppl 5):S52 43. Alexander JW, Peck MD. Future prospects for adjunctive therapy: pharmacolog-

Malnutrition and Nutrition in Critically Ill Children

44.

45. 46. 47. 48.

49.

50.

51. 52. 53. 54.

557

ical and nutritional approaches to immune system modulation. Crit Care Med 1990;18:5159 Gollaher CJ, Fechner K, Karlstad M, Babayan VK, Bistrian BR. The effect of increasing levels of fish oil-containing structured triglycerides on protein metabolism in parenterally fed rats stressed by burn plus endotoxin. JPEN 1993;17:247 Takala J. Nutrition and body composition in multiple organ failure. Nutrition 1995;11:769 Klein S, Peters E, Shangraw R, Wolfe R. Lipolytic response to metabolic stress in critically ill patients. Crit Care Med 1991;19:776 Baue AE. The role of the gut in the development of multiple organ dysfunction in cardiothoracic patients. Ann Thorac Surg 1993;55:822 Stiber F, Petersen M, Bokelmann F, Schade U. A genomic plymorphism within the tumor necrosis factor locus influences plasma tumor necrosis factor-alpha concentrations and outcome of patients with severe sepsis. Crit Care Med 1996;24:381 Moore FA, Feliciana DV, Andrassy RJ, et al. Early enteral feeding, compared with parenteral, reduces postoperative septic complications: the results of a meta analysis. Ann Surg 1992;24:381 Giner M, Laviano A, Meguid MM, Gleason JR. In 1995 a correlation between malnutrition and poor outcome in critically ill patients still exists. Nutrition 1996;12:23 Arora NS, Rochester DF. Respiratory muscle strength and maximal voluntary ventilation in undernourished patients Chandra RK. Nutrition and the immune system. Proc Nutr Soc 1993;52:77 Seltzer MH, Fletcher HS, Slocum BA, et al. Instant nutritional assessment in the intensive care units. JPEN 1981;5:70 Rickard KA, Loghmani ES, Grosfeld JL, et al. Short- and long-term effectiveness of enteral and parenteral nutrition in reversing or preventing protein-energy malnutrition in advanced neuroblastoma. A prospective randomized study. Cancer 1985;56:2881