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Pre-operative nutritional status does not alter the metabolic response to major gastrointestinal surgery in patients with oesophageal cancer

Published online by Cambridge University Press:  01 July 2007

Peter H. Bisschop*
Affiliation:
Department of Endocrinology and Metabolism (F5-165), Academic Medical Center, PO Box 22700, 1100 DE Amsterdam, The Netherlands
Samuel Klein
Affiliation:
Center for Human Nutrition, Washington University School of Medicine, Campus Box 8031, 660 South Euclid Avenue, St Louis, MO 63110, USA
Mariëtte T. Ackermans
Affiliation:
Department of Clinical Chemistry, Laboratory of Endocrinology and Radiochemistry, Academic Medical Center, PO Box 22700, 1100 DE Amsterdam, The Netherlands
Bruce W. Patterson
Affiliation:
Center for Human Nutrition, Washington University School of Medicine, Campus Box 8031, 660 South Euclid Avenue, St Louis, MO 63110, USA
Erik Endert
Affiliation:
Department of Clinical Chemistry, Laboratory of Endocrinology and Radiochemistry, Academic Medical Center, PO Box 22700, 1100 DE Amsterdam, The Netherlands
Jan J. B. van Lanschot
Affiliation:
Department of Surgery, Academic Medical Center, PO Box 22700, 1100 DE Amsterdam, The Netherlands
Johannes A. Romijn
Affiliation:
Department of Endocrinology, Leiden University Medical Center, Building 1, C4-R, PO Box 9600, 2300 RC Leiden, The Netherlands
Hans P. Sauerwein
Affiliation:
Department of Endocrinology and Metabolism (F5-165), Academic Medical Center, PO Box 22700, 1100 DE Amsterdam, The Netherlands
*
*Corresponding author: Dr Peter H. Bisschop, fax +31 20 6917682, email p.h.bisschop@amc.uva.nl
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Abstract

Malnutrition is associated with an increased incidence of perioperative morbidity and mortality. To evaluate the effect of malnutrition on the metabolic and inflammatory response to surgery in patients with oesophageal cancer, we studied the effects of oesophagectomy in six patients with major (13·9 (se 1·3) %) weight loss and five patients with minor (0·7 (se 0·6) %) weight loss in the 6 months before to surgery. Rates of appearance (Ra) of glucose, glycerol, leucine and urea were determined by stable isotopically labelled tracer infusion before and after surgery. C-reactive protein was measured as an inflammation marker. BMI was lower in the patients with major weight loss than those with minor weight loss (20·3 (se 0·7) and 24·9 (se 1·5) kg/m2, P = 0·02). With the exception of greater glucose Ra in the major weight loss than minor weight loss subjects (11·1 (se 0·3) v. 9·5 (se 0·3) μmol/kg per min, P = 0·01), there were no differences in substrate kinetics before surgery between groups. Surgery increased glucose Ra, leucine Ra and urea Ra by 41, 24 and 58 %, respectively, in the total group. Changes in substrate kinetics in response to surgery were not different between patients with major and minor weight loss. Surgery increased C-reactive protein concentrations to a comparable extent in both groups. In conclusion, major upper gastrointestinal tract surgery in patients with oesophageal cancer elicits a catabolic response, characterized by increased inflammation, glucose production and protein breakdown. However, this catabolic response does not seem to be influenced by pre-operative nutritional status.

Type
Full Papers
Copyright
Copyright © The Authors 2007

Pre-operative malnutrition, defined by percentage body weight loss, increases the risk of post-operative medical complications (Buzby et al. Reference Buzby, Mullen, Matthews, Hobbs and Rosato1980; Warnold & Lundholm, Reference Warnold and Lundholm1984; Klein et al. Reference Klein, Hey, Yu, Klein, Coufal, Young, Marshall and Garfin1996; Studley, Reference Studley2001). The mechanism(s) responsible for the relationship between malnutrition and an adverse clinical outcome is not clear, but could be related to physiological alterations induced by the combined metabolic stress of surgery and malnutrition. In patients with cancer, weight loss is caused by a combination of malnutrition due to reduced food intake and increased demands due to systemic or local inflammation. Patients with cancer of the upper gastrointestinal tract are particularly prone to developing malnutrition because of poor food intake caused by mechanical intestinal obstruction. A percentage (10–20 %) of patients with upper gastrointestinal tract cancer also have evidence of a systemic inflammatory response (Ikeda et al. Reference Ikeda, Natsugoe, Ueno, Baba and Aikou2003; Shimada et al. Reference Shimada, Nabeya and Okazumi2003). Moreover, surgical resection of upper gastrointestinal tract cancer is a major operative procedure, and represents a considerable stress to a patient who is already compromised by weight loss and muscle wasting.

The metabolic effects of upper gastrointestinal tract resection are not known, but are likely to be similar to the effects of tissue injury in general. Patients who have experienced physical trauma have increased rates of endogenous glucose production and lipolysis, and exhibit net protein catabolism (Shaw & Wolfe, Reference Shaw and Wolfe1989). It is not known whether malnutrition modifies the metabolic response to major gastrointestinal surgery. Therefore, it is possible that malnutrition-induced alterations in the metabolic response to surgery increase the risk of post-operative complications.

The aim of the present study was to evaluate the effects of malnutrition on the metabolic response to oesophageal resection as a model of major gastrointestinal surgical intervention. Stable isotopically labelled tracer infusion was used to assess protein, glucose and lipid kinetics before and after surgery in patients with oesophageal carcinoma, who were judged to be malnourished or adequately nourished based on changes in pre-operative body weight.

Subjects and methods

Subjects

A total of eleven men and women with oesophageal cancer, who were admitted to the hospital for oesophagectomy, participated in the present study (Table 1). Patients with diabetes, severe organ disease or those taking medications that would affect substrate metabolism were excluded. All patients were deemed eligible for radical resection of the tumour and surrounding lymph nodes after radiographical evaluation of the disease state by computed tomography of the thorax and upper abdomen, ultrasound of the neck and endoesophageal ultrasonography. Subjects were divided into two groups, based on documented weight change over a period of 6 months before surgery: those who lost more than 10 % of their initial, stable body weight were considered the major weight loss group and those who lost less than 5 % body weight were considered the minor weight loss group. All subjects gave written, informed consent before their participation in the study, which was approved by the Medical Ethical Committee of the Academic Medical Center.

Table 1 Patient characteristics

Mean values were significantly different from those of the minor weight loss group: *P = 0·017; **P < 0·001.

Experimental protocol

Subjects were admitted to the surgical ward of the Academic Medical Center 3 d before surgery. All subjects ate breakfast on the day of admission, but were only allowed to drink non-caloric beverages after the breakfast meal was consumed. A standard pre-operative bowel preparation protocol was initiated, which involved having the subjects drink a non-absorbable electrolyte solution (Klean Prep; Helsinn Birex Pharmaceuticals Ltd, Dublin, Ireland), until adequate bowel cleansing was achieved, which was not later than 18.00 hours on the second day of admission.

The following morning, on the third day of admission (1 day before surgery), VO2 and CO2 production rates were determined by using a metabolic measurement cart with ventilated hood system (Sensormedics model 2900; Sensormedics, Anaheim, CA, USA), and an isotope infusion study to assess substrate kinetics was performed. At 07.00 hours subjects were transferred to the metabolic ward. Subjects were weighed, and body fat percentage was determined by bioimpedance analysis (Akern, Florence, Italy). All patients were clinically and biochemically euvolemic. A catheter for isotope tracer infusion was inserted in an antecubital vein. Another catheter was placed in a hand vein of the contralateral arm and used to sample arterialized blood by heating the hand to 60°C in a thermostatically controlled box. At 08.00 hours, after blood samples were obtained to determine background plasma substrate enrichments, primed, constant infusions of [5,5,5-2H3]l-leucine (98 % enriched; Cambridge Isotope Laboratories, Andover, MA, USA; 9 μmol/kg priming dose and 0·15 μmol/kg per min constant infusion) and [15N2]urea (>98 % enriched; Cambridge Isotope Laboratories; 67·2 μmol/kg priming dose and 0·12 μmol/kg per min constant infusion) were started and continued for 8 h. At 13.30 hours, a primed, constant infusion of [6,6-2H2]d-glucose (99 % enriched; Cambridge Isotope Laboratories; 17·6 μmol/kg priming dose and 0·22 μmol/kg per min constant infusion) was started and continued for 2·5 h. At 14.30 hours, a primed, constant infusion of [2H5]glycerol (99 % enriched; Cambridge Isotope Laboratories; 1·5 μmol/kg priming dose and 0·10 μmol/kg per min constant infusion) was started and continued for 1·5 h. Blood samples were obtained at 15.30, 15.40, 15.50 and 16.00 hours to determine plasma enrichment of urea, leucine, glucose and glycerol. After the isotope infusion protocol was completed, subjects were transferred back to the surgical ward.

The following morning (the fourth day of admission), an oesophageal resection was performed in all subjects followed by gastric tube reconstruction. The transhiatal approach was used in four subjects in each of the two groups and the transthoracic approach was used in the remaining subjects. Blood loss during surgery was 1216 (se 389) and 1517 (se 472) ml in the minor and major weight loss groups, respectively (NS). Subjects were given intravenous normal saline after surgery, but did not receive parenteral or enteral calories until completion of the second isotope infusion study.

On the second post-operative day (the sixth day of admission), the same isotope infusion protocol as performed before surgery was repeated. Therefore, the first isotope infusion protocol was performed after approximately 2 d of fasting and the second isotope infusion protocol was performed after approximately 5 d of fasting. One subject in the minor weight loss group received norepinephrine infusion during the post-operative study, because of hypotension. An infectious cause was suspected and broad-spectrum antibiotic therapy was initiated. Because all cultures remained negative the antibiotic therapy was discontinued on the fourth post-operative day. Norepinephrine dependency decreased gradually and norepinephrine administration was discontinued on the sixth postoperative day. Although all results include data from this subject, eliminating the data from this subject did not change the statistical significance of any end-points.

Analytical procedures

Plasma insulin concentration was determined by RIA (Insulin RIA 100; Pharmacia Diagnostic AB, Uppsala, Sweden): intra-assay CV 3–5 %, inter-assay CV 6–9 %, detection limit 15 pmol/l. Plasma C-peptide concentration was determined by RIA (RIA-coat c-peptide; Byk-Sangtec Diagnostica GmbH & Co. KG, Dietzenbach, Germany): intra-assay CV 4–6 %, inter-assay CV 6–8 %, detection limit 50 pmol/l. Cortisol concentration was measured by enzyme-immunoassay on an Immulite analyser (DPC, Los Angeles, CA, USA): intra-assay CV 2–4 %, inter-assay CV 3–7 %, detection limit 50 nmol/l. Glucagon concentration was determined by RIA (Linco Research, St Charles, MO, USA): intra-assay CV 3–5 %, inter-assay CV 9–13 %, detection limit 15 ng/l. Epinephrine concentrations were determined by an in-house HPLC method: intra-assay CV 6–8 %, inter-assay CV 7–12 %, detection limit 0·05 nmol/l. Serum NEFA were measured using an enzymatic method (NEFAC; Wako Chemicals GmbH, Neuss, Germany): intra-assay CV 2–4 %, inter-assay CV 3–6 %, detection limit 0·02 mmol/l. Plasma C-reactive protein was determined using a fully automated assay on a Hitachi 912 (Roche Diagnostics Netherlands BV, Almere, The Netherlands).

Plasma glucose enrichment was determined by deproteinizing plasma with methanol (Reinauer et al. Reference Reinauer, Gries, Hubinger, Knode, Severing and Susanto1990). The aldononitrile penta-acetate derivative of glucose (Knap, 1979) was injected into a Hewlett Packard 5973 GC/MS system (Hewlett Packard, Palo Alto, CA, USA). Separation was achieved on a J&W DB17 column (30 m × 0·25 mm, d f 0·25 μm). Glucose concentrations were determined by GC using xylose as an internal standard. Glucose was monitored at mass-to-charge ratio (m/z) 187, 188 and 189. The enrichment of [6,6-2H2]glucose was determined by dividing the peak area of m/z 189 by the total peak area and correcting for natural enrichments.

The enrichment of [1,1,2,3,3-2H5]glycerol in plasma was determined as described previously (Ackermans et al. Reference Ackermans, Ruiter and Endert1998).

Plasma leucine, urea and α-ketoisocaproate enrichments were determined after deproteinizing plasma with ice-cold acetone. tert-butyldimethylsilyl derivatives (Patterson et al. Reference Patterson, Carraro and Wolfe1993) were injected into a Hewlett-Packard 5973 GC/MS system equipped with a HP-5MS column (30 m × 0·25 mm). Leucine was monitored at m/z 200 and 203, α-ketoisocaproate was monitored at m/z 301 and 304, and urea was monitored at m/z 231 and 233. Enrichments were determined by comparison of instrumental peak area ratios to standards of known isotopic enrichment.

Calculations

Physiological and isotopic steady states were present during the last 30 min of isotope infusion. Therefore, Steele's equation for steady-state conditions as adapted for the use of stable isotopes (Steele, Reference Steele1959) was used to calculate whole-body leucine, urea, glucose and glycerol kinetics.

Statistical analysis

Data are presented as means and their standard errors. Student's t test was used to test for pre-operative differences and for differences in the reponse to surgery between the minor and major weight loss group. Student's t test for paired samples was used to test for differences between pre-operative and post-operative values within each group. A P value of less than 0·05 was considered to be statistically different.

Results

Post-operative complications

In the minor weight loss group three patients had post-operative medical complications: one had rectal bleeding from a colonic diverticulum; one had leakage of the proximal anastomosis and developed a pneumonia with pleural empyema; one had a severe pseudomembranous colitis with sepsis and multiorgan failure for which a subtotal colectomy had to be performed.

In the major weight loss group three patients had post-operative medical complications: one had pleural empyema; one had a high production rate of the thoracic drain without evidence of infection or chylothorax and the production decreased spontaneously after several days; one patient had a cardiac arrest 1 week after surgery and died.

Energy metabolism

Pre-operatively, basal VO2 expressed per kg lean body mass was not different between subjects with minor weight loss (4·57 (se 0·23) ml/kg lean body mass per min) and those with major weight loss (5·14 (se 0·23) ml/kg lean body mass per min). In addition, RQ were not different between the minor and major weight loss groups (0·70 (se 0·03) and 0·71 (se 0·02), respectively), indicating that endogenous fat represented the major source of fuel in both groups.

Plasma hormone, cytokine and acute phase protein concentrations

Plasma hormone and C-reactive protein concentrations before and after surgery are shown in Table 2. Surgery increased C-reactive protein levels in all subjects, but the increase was not different between the minor and major weight loss group. Pre-operative hormone concentrations were not different between the groups nor were they significantly altered by surgery.

Table 2 Pre-operative and post-operative plasma hormone and C-reactive protein concentrations in patients with minor (n 5) and major (n 6) weight loss(Mean values with their standard errors)

Mean values were significantly different from those of the pre-operative group: *P < 0·05.

Glucose metabolism

Pre-operative basal plasma glucose concentrations were not different between the minor and major weight loss groups (4·87 (se 0·30) and 4·39 (se 0·39) mmol/l, respectively), but the pre-operative rate of endogenous glucose production was greater in patients with major than minor weight loss (Table 3). Surgery increased glucose production in both the minor and major weight loss groups by approximately 40 %.

Table 3 Pre-operative and post-operative rate of appearance (R a) of glucose, glycerol, leucine and urea in patients with minor (n 5) and major (n 6) weight loss(Mean values with their standard errors)

Mean values were significantly different from those of the minor and major weight loss group (tested only for pre-operative and % change): *P < 0·05.

Mean values were significantly different from those of the pre-operative group: †P < 0·05.

Lipid metabolism

Basal plasma NEFA concentrations were not different between subjects with minor and major weight loss before (1·04 (se 0·14) and 1·15 (se 0·15) mmol/l, respectively) or after (0·65 (se 0·09) and 0·74 (se 0·04) mmol/l, respectively) surgery. In accordance with plasma NEFA concentrations, whole-body lipolytic rate, as estimated by glycerol rate of appearance (R a), was not different between groups before or after surgery (Table 3).

Protein metabolism

Leucine R a, an index of whole-body protein breakdown, was not different between patients with minor and major weight loss before surgery (Table 3). Surgery increased leucine Ra in patients with minor (~23 %, P = 0·07) and major (~25 %, P = 0·03) weight loss, but the increase was significant only in the major weight loss group. Urea R a was not different between groups before or after surgery (Table 3).

Discussion

The objective of the present study was to evaluate the effect of nutritional status on the metabolic response to major surgery. Therefore, we assessed serum markers of inflammation and substrate metabolism before and after oesophagectomy in patients with oesophageal cancer, who had either lost more than 10 % or less than 5 % of their initial body weight. Major weight loss was associated with a higher rate of glucose production before surgery, whereas fat and protein kinetics were not different between the two groups. Surgery caused a similar increase in glucose R a (~40 %) and leucine R a (~25 %) in patients with major and minor weight loss. The present data indicate that pre-operative malnutrition does not seem to affect the metabolic response to major surgery in patients with oesophageal cancer.

We specifically selected two groups of patients with oesophageal cancer, who had marked differences in their nutritional status, based on recent changes in body weight. A weight loss of 10 % or more within 6 months before surgery in patients with upper gastrointestinal tract cancers has been consistently associated with an increase in major post-operative complications (Bokhorst-de van der Schueren et al. Reference Bokhorst-de van der Schueren, van Leeuwen, Sauerwein, Kuik, Snow and Quak1997). Therefore, we specifically selected patients in whom we were able to document at least a 10 % weight loss in the 6 months before surgery, and compared these patients with those who had experienced minor ( < 5 %) weight loss. These inclusion criteria resulted in marked differences in BMI between the two groups. Power analysis indicated that the sample size was sufficient to detect a 14, 29, 40 and 68 % difference between groups for glucose, leucine, glycerol and urea R a, respectively, with a CI of 0·95 and a power of 0·8. Smaller differences may exist, but are below the detection limit of the present study. Due to a wide range in the hormonal response to surgery, the power to detect differences between groups (CI of 0·95) was low: 0·34, 0·32, 0·54 and 0·17 for insulin, glucagon, cortisol and epinephrine, respectively.

The subjects were studied during fasting conditions at the time of both metabolic studies. The protocol for oesophageal resection included bowel cleansing, which was initiated 3 d before surgery, and subjects were not fed for 2 d after surgery. As a result, the subjects had been fasting for 2 d at the time of the pre-operative study and for 5 d at the time of the post-operative study. The effects of prolonged fasting on glucose, fat and protein metabolism have been well characterized in healthy subjects. Glucose production decreases gradually between 18 and 54 h of fasting from approximately 11·0 μmol/kg per min to a stable rate of ~8·3 μmol/kg per min (Nair et al. Reference Nair, Woolf, Welle and Matthews1987; Klein et al. Reference Klein, Sakurai, Romijn and Carroll1993). Glycerol R a increases in response to fasting, but more than half of the total increase during a 72 h fast occurs between 12 and 24 h of fasting. The increase in glycerol R a between 24 and 72 h of fasting is small, and reaches a plateau at 54 h of fasting of about 4 μmol/kg per min. Changes in protein metabolism in response to starvation reach a steady state after 3 d (Goschke et al. Reference Goschke, Stahl and Tholen1975; Forbes & Drenick, Reference Forbes and Drenick1979). Therefore, most of the metabolic adaptation to starvation occurs within 48 h of fasting, with relatively small changes in glucose, protein and fatty acid metabolism thereafter. Because our subjects were studied before surgery after about 48 h of fasting, the metabolic alterations observed at the time of the second isotope infusion study, which was conducted after an additional 72 h of fasting, are likely to primarily represent the effect of surgical stress rather than prolonged starvation. However, the pronounced effect of prolonged fasting on glucose, fat and protein metabolism may have obscured a potential effect of nutritional status. Cancer is often associated with progressive weight loss and cachexia induced by a combination of insufficient energy intake due to anorexia and catabolism induced by a complex interaction of inflammatory, endocrine and neural factors (Holroyde & Reichard, Reference Holroyde and Reichard1986). Together these factors induce marked changes in glucose, protein and fat metabolism. Normally, endogenous glucose production rates decrease with energy restriction; glucose R a decreases in lean subjects who have lost weight rapidly during short-term fasting (Klein et al. Reference Klein, Sakurai, Romijn and Carroll1993) and in obese subjects who have lost weight more slowly by dieting (Vazquez & Kazi, Reference Vazquez and Kazi1994). In contrast, glucose R a was greater in the oesophageal cancer patients in the present study who had experienced major weight loss than in those who had minor weight loss. Increased glucose production rates have also been observed in patients with other types of cancer who have had weight loss (Holroyde et al. Reference Holroyde, Skutches, Boden and Reichard1984; Heber et al. Reference Heber, Byerly and Chlebowski1985; Cersosimo et al. Reference Cersosimo, Pisters, Pesola, Rogatko, Vydelingum, Bajorunas and Brennan1991). In addition, we found that surgery caused an increase in glucose production, which is a known response to trauma (Jeevanandam et al. Reference Jeevanandam, Young and Schiller1990; Mizock, Reference Mizock1995; Nygren et al. Reference Nygren, Thorell, Efendic, Nair and Ljungqvist1997), in patients who had major or minor weight loss before surgery. The clinical implications of increased glucose production in patients with weight loss and cancer are not known. Catabolic conditions in otherwise healthy subjects decrease glucose production. Therefore one might assume that weight loss in patients with oesophageal cancer is associated with increased glucose production via systemic effects of cancer, possibly by inflammatory or humoral factors. Although speculative, increased glucose production could prove to be an unfavourable prognostic factor analogous to C-reactive protein, a marker of systemic inflammation (Shimada et al. Reference Shimada, Nabeya and Okazumi2003).

In a previous study, conducted in patients with oesophageal cancer, whole-body lipolytic rate, measured after a 14 h fast, was 1·5-fold greater in patients who had more than 10 % weight loss than in patients without weight loss (Klein & Wolfe, Reference Klein and Wolfe1990). In the present study, whole-body lipolytic rate was not different between patients who had major or minor weight loss. This discrepancy between studies is probably due to differences in the duration of fasting. In the present study, whole-body lipolytic rate was measured after a much longer period of fasting (48 h) than in the previous study (14 h), which likely attenuated differences in lipolysis between the two groups. In healthy volunteers, whole-body lipolytic rate is 2-fold greater after 48 h of fasting than after an overnight (12 h) fast (Klein et al. Reference Klein, Sakurai, Romijn and Carroll1993).

Data from previous studies have shown that leucine R a is not primarily affected by cancer (Borzotta et al. Reference Borzotta, Clague and Johnston1987; Harrison et al. Reference Harrison, Lewin, Halliday and Clark1989b). In the present study, pre-operative proteolysis, measured by the R a of leucine in plasma, was not different between subjects with major and minor weight loss, which is consistent with observations obtained in subjects who have lost weight due to non-neoplastic gastrointestinal disease (Carbonnel et al. Reference Carbonnel, Messing, Darmaun, Rimbert, Rongier, Rigal, Koziet, Thuillier and Desjeux1995). Therefore, protein metabolism is relatively well maintained in (pre-operative) cancer patients, even after significant weight loss. The post-operative R a of leucine was increased irrespective of nutritional status in line with a previous report on cancer patients. The increased release of leucine was not associated with net protein loss, since urea production was constant. This implies that leucine incorporation into protein, although not measured directly, was increased as well and suggests that protein turnover is accelerated by surgical stress, which is compatible with a previous report on surgery in cancer patients (Harrison et al. Reference Harrison, Lewin, Halliday and Clark1989a).

In conclusion, major upper gastrointestinal surgery in patients with oesophageal cancer elicits a catabolic response that is characterized by increased glucose production and accelerated protein breakdown. Pre-operative malnutrition does not seem to alter the metabolic response to surgery in these patients.

Acknowledgements

This study was supported by National Institutes of Health grants DK 37 948 and DK 56 341 (Clinical Nutrition Research Unit).

References

Ackermans, MT, Ruiter, AF & Endert, E (1998) Determination of glycerol concentrations and glycerol isotopic enrichments in human plasma by gas chromatography/mass spectrometry. Anal Biochem 258, 8086.CrossRefGoogle ScholarPubMed
Bokhorst-de van der Schueren, MA, van Leeuwen, PA, Sauerwein, HP, Kuik, DJ, Snow, GB & Quak, JJ (1997) Assessment of malnutrition parameters in head and neck cancer and their relation to postoperative complications. Head Neck 19, 419425.3.0.CO;2-2>CrossRefGoogle ScholarPubMed
Borzotta, AP, Clague, MB & Johnston, ID (1987) The effects of gastrointestinal malignancy on whole body protein metabolism. J Surg Res 43, 505512.CrossRefGoogle ScholarPubMed
Buzby, GP, Mullen, JL, Matthews, DC, Hobbs, CL & Rosato, EF (1980) Prognostic nutritional index in gastrointestinal surgery. Am J Surg 139, 160167.CrossRefGoogle ScholarPubMed
Carbonnel, F, Messing, B, Darmaun, D, Rimbert, A, Rongier, M, Rigal, O, Koziet, J, Thuillier, F & Desjeux, JF (1995) Energy and protein metabolism in malnutrition due to nonneoplastic gastrointestinal diseases. Metabolism 44, 11101115.CrossRefGoogle ScholarPubMed
Cersosimo, E, Pisters, PW, Pesola, G, Rogatko, A, Vydelingum, NA, Bajorunas, D & Brennan, MF (1991) The effect of graded doses of insulin on peripheral glucose uptake and lactate release in cancer cachexia. Surgery 109, 459467.Google ScholarPubMed
Forbes, GB & Drenick, EJ (1979) Loss of body nitrogen on fasting. Am J Clin Nutr 32, 15701574.CrossRefGoogle ScholarPubMed
Goschke, H, Stahl, M & Tholen, H (1975) Nitrogen loss in normal and obese subjects during total fast. Klin Wochenschr 53, 605610.CrossRefGoogle ScholarPubMed
Harrison, RA, Lewin, MR, Halliday, D & Clark, CG (1989a) Leucine kinetics in surgical patients. I: A study of the effect of surgical ‘stress’. Br J Surg 76, 505508.CrossRefGoogle Scholar
Harrison, RA, Lewin, MR, Halliday, D & Clark, CG (1989b) Leucine kinetics in surgical patients. II: A study of the effect of malignant disease and tumour burden. Br J Surg 76, 509511.CrossRefGoogle Scholar
Heber, D, Byerly, LO & Chlebowski, RT (1985) Metabolic abnormalities in the cancer patient. Cancer 55, 225229.3.0.CO;2-7>CrossRefGoogle ScholarPubMed
Holroyde, CP & Reichard, GA Jr (1986) General metabolic abnormalities in cancer patients: anorexia and cachexia. Surg Clin North Am 66, 947956.CrossRefGoogle ScholarPubMed
Holroyde, CP, Skutches, CL, Boden, G & Reichard, GA (1984) Glucose metabolism in cachectic patients with colorectal cancer. Cancer Res 44, 59105913.Google ScholarPubMed
Ikeda, M, Natsugoe, S, Ueno, S, Baba, M & Aikou, T (2003) Significant host- and tumor-related factors for predicting prognosis in patients with esophageal carcinoma. Ann Surg 238, 197202.CrossRefGoogle ScholarPubMed
Jeevanandam, M, Young, DH & Schiller, WR (1990) Glucose turnover, oxidation, and indices of recycling in severely traumatized patients. J Trauma 30, 582589.CrossRefGoogle ScholarPubMed
Klein, JD, Hey, LA, Yu, CS, Klein, BB, Coufal, FJ, Young, EP, Marshall, LF & Garfin, SR (1996) Perioperative nutrition and postoperative complications in patients undergoing spinal surgery. Spine 21, 26762682.CrossRefGoogle ScholarPubMed
Klein, S, Sakurai, Y, Romijn, JA & Carroll, RM (1993) Progressive alterations in lipid and glucose metabolism during short-term fasting in young adult men. Am J Physiol 265, E801E806.Google ScholarPubMed
Klein, S & Wolfe, RR (1990) Whole-body lipolysis and triglyceride-fatty acid cycling in cachectic patients with esophageal cancer. J Clin Invest 86, 14031408.CrossRefGoogle ScholarPubMed
Knap DR (1979) Handbook of Analytical Derivatization Reactions. Wiley-Interscience: New York, USA..Google Scholar
Mizock, BA (1995) Alterations in carbohydrate metabolism during stress: a review of the literature. Am J Med 98, 7584.CrossRefGoogle Scholar
Nair, KS, Woolf, PD, Welle, SL & Matthews, DE (1987) Leucine, glucose, and energy metabolism after 3 days of fasting in healthy human subjects. Am J Clin Nutr 46, 557562.CrossRefGoogle ScholarPubMed
Nygren, J, Thorell, A, Efendic, S, Nair, KS & Ljungqvist, O (1997) Site of insulin resistance after surgery: the contribution of hypocaloric nutrition and bed rest. Clin Sci (Colch) 93, 137146.CrossRefGoogle ScholarPubMed
Patterson, BW, Carraro, F & Wolfe, RR (1993) Measurement of 15N enrichment in multiple amino acids and urea in a single analysis by gas chromatography/mass spectrometry. Biol Mass Spectrom 22, 518523.CrossRefGoogle Scholar
Reinauer, H, Gries, FA, Hubinger, A, Knode, O, Severing, K & Susanto, F (1990) Determination of glucose turnover and glucose oxidation rates in man with stable isotope tracers. J Clin Chem Clin Biochem 28, 505511.Google ScholarPubMed
Shaw, JH & Wolfe, RR (1989) An integrated analysis of glucose, fat, and protein metabolism in severely traumatized patients. Studies in the basal state and the response to total parenteral nutrition. Ann Surg 209, 6372.CrossRefGoogle ScholarPubMed
Shimada, H, Nabeya, Y, Okazumi, S, et al. (2003) Elevation of preoperative serum C-reactive protein level is related to poor prognosis in esophageal squamous cell carcinoma. J Surg Oncol 83, 248252.CrossRefGoogle ScholarPubMed
Steele, R (1959) Influences of glucose loading and of injected insulin on hepatic glucose output. Ann N Y Acad Sci 82, 420430.CrossRefGoogle ScholarPubMed
Studley, HO (2001) Percentage of weight loss: a basic indicator of surgical risk in patients with chronic peptic ulcer. 1936. Nutr Hosp 16, 141143.Google ScholarPubMed
Vazquez, JA & Kazi, U (1994) Lipolysis and gluconeogenesis from glycerol during weight reduction with very-low-calorie diets. Metabolism 43, 12931299.CrossRefGoogle ScholarPubMed
Warnold, I & Lundholm, K (1984) Clinical significance of preoperative nutritional status in 215 noncancer patients. Ann Surg 199, 299305.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Patient characteristics

Figure 1

Table 2 Pre-operative and post-operative plasma hormone and C-reactive protein concentrations in patients with minor (n 5) and major (n 6) weight loss(Mean values with their standard errors)

Figure 2

Table 3 Pre-operative and post-operative rate of appearance (Ra) of glucose, glycerol, leucine and urea in patients with minor (n 5) and major (n 6) weight loss(Mean values with their standard errors)