Ann Lab Med.  2012 Jul;32(4):250-256. 10.3343/alm.2012.32.4.250.

Influence of a Regular, Standardized Meal on Clinical Chemistry Analytes

Affiliations
  • 1Laboratory of Clinical Biochemistry, Department of Life and Reproduction Sciences, University of Verona, Italy. dr.g.lima.oliveira@gmail.com
  • 2Post-Graduate Program of Pharmaceutical Sciences, Department of Medical Pathology Federal University of Parana, Brazil.
  • 3MERCOSUL, Sector Committee of Clinical Analyses and In Vitro Diagnostics-CSM 20, Brazil.
  • 4Brazilian Society of Clinical Analyses on Sao Paulo State, Brazil.
  • 5Laboratory of Clinical Chemistry and Hematology, Department of Pathology and Laboratory Medicine, Academic Hospital of Parma, Italy.

Abstract

BACKGROUND
Preanalytical variability, including biological variability and patient preparation, is an important source of variability in laboratory testing. In this study, we assessed whether a regular light meal might bias the results of routine clinical chemistry testing.
METHODS
We studied 17 healthy volunteers who consumed light meals containing a standardized amount of carbohydrates, proteins, and lipids. We collected blood for routine clinical chemistry tests before the meal and 1, 2, and 4 hr thereafter.
RESULTS
One hour after the meal, triglycerides (TG), albumin (ALB), uric acid (UA), phosphatase (ALP), Ca, Fe, and Na levels significantly increased, whereas blood urea nitrogen (BUN) and P levels decreased. TG, ALB, Ca, Na, P, and total protein (TP) levels varied significantly. Two hours after the meal, TG, ALB, Ca, Fe, and Na levels remained significantly high, whereas BUN, P, UA, and total bilirubin (BT) levels decreased. Clinically significant variations were recorded for TG, ALB, ALT, Ca, Fe, Na, P, BT, and direct bilirubin (BD) levels. Four hours after the meal, TG, ALB, Ca, Fe, Na, lactate dehydrogenase (LDH), P, Mg, and K levels significantly increased, whereas UA and BT levels decreased. Clinically significant variations were observed for TG, ALB, ALT, Ca, Na, Mg, K, C-reactive protein (CRP), AST, UA, and BT levels.
CONCLUSIONS
A significant variation in the clinical chemistry parameters after a regular meal shows that fasting time needs to be carefully considered when performing tests to prevent spurious results and reduce laboratory errors, especially in an emergency setting.

Keyword

Blood specimen collection; Clinical laboratory techniques; Diagnostic errors; Eating; Fasting; Postprandial period; Reference values; Reproducibility of results; Quality control; Specimen handling

MeSH Terms

Adult
Alkaline Phosphatase/blood
*Blood Chemical Analysis
Blood Urea Nitrogen
C-Reactive Protein/analysis
Diagnostic Errors/prevention & control
Diet/*standards
Fasting
Female
Humans
Lipids/blood
Male
Metals/blood
Serum Albumin/analysis
Triglycerides/blood
Uric Acid/blood

Figure

  • Fig. 1 Percentage of postprandial variation in serum levels of several analytes after a light meal. Percentage variation (%) were the differences of analytes serum levels from baseline (time 0) to the different studied times. The analytes were TG, triglycerides; ALB, albumin; CRP, C-reactive protein; UA, uric acid; AST; ALT; BT, total bilirubin; and BD, direct bilirubin.

  • Fig. 2 Percentage of postprandial variation in serum levels of iron and electrolytes after a light meal. Percentage variation (%) were the differences of analytes serum levels from baseline (time 0) to the different studied times. The analytes were P, Ca, Mg, Fe, Na, and K.


Reference

1. Lippi G, Lima-Oliveira G, Salvagno GL, Montagnana M, Gelati M, Picheth G, et al. Influence of a light meal on routine haematological tests. Blood Transfus. 2010. 8:94–99.
2. Lima-Oliveira G, Salvagno GL, Lippi G, Montagnana M, Scartezini M, Picheth G, et al. Elimination of the venous stasis error for routine coagulation testing by transillumination. Clin Chim Acta. 2011. 412:1482–1484.
Article
3. Lima-Oliveira G, Lippi G, Salvagno GL, Montagnana M, Scartezini M, Guidi GC, et al. Transillumination: a new tool to eliminate the impact of venous stasis during the procedure for the collection of diagnostic blood specimens for routine haematological testing. Int J Lab Hematol. 2011. 33:457–462.
Article
4. Loh TP, Saw S, Chai V, Sethi SK. Impact of phlebotomy decision support application on sample collection errors and laboratory efficiency. Clin Chim Acta. 2011. 412:393–395.
Article
5. Lippi G, Lima-Oliveira G, Nazer SC, Moreira ML, Souza RF, Salvagno GL, et al. Suitability of a transport box for blood sample shipment over a long period. Clin Biochem. 2011. 44:1028–1029.
Article
6. Young DS. Effects of preanalytical variables on clinical laboratory tests. 2007. 3rd ed. Washington, DC: AACC Press.
7. Hallworth M, Hyde K, Cumming A, Peake I. The future for clinical scientists in laboratory medicine. Clin Lab Haematol. 2002. 24:197–204.
Article
8. Clinical Laboratory Standards Institute. CLSI H3-A6 document. Procedures for the collection of diagnostic blood specimens by venipuncture. 2007. 6th ed. Wayne, PA: Clinical Laboratory Standards Institute.
9. Guder WG, Narayanan S, Wisser H, Zawta B. Diagnostic samples: from the patient to the laboratory: the impact of preanalytical variables on the quality of laboratory results. 2009. 4th ed. New York: Wiley-Blackwell.
10. Clinical Laboratory Standards Institute. CLSI H18-A4 document. Procedures for the handling and processing of blood specimens for common laboratory tests. 2010. 4th ed. Wayne, PA: Clinical Laboratory Standards Institute.
11. Ricós C, Alvarez V, Cava F, García-Lario JV, Hernández A, Jiménez CV, et al. Current databases on biological variation: pros, cons and progress. Scand J Clin Lab Invest. 1999. 59:491–500.
12. Guidi GC, Lippi G. Laboratory medicine in the 2000s: programmed death or rebirth? Clin Chem Lab Med. 2006. 44:913–917.
Article
13. Pagni A, Plebani M. The laboratory and the general practitioner. Clin Chim Acta. 1999. 280:13–24.
Article
14. Johnson CD, Mole DR, Pestridge A. Postprandial alkaline tide: does it exist? Digestion. 1995. 56:100–106.
Article
15. Batterham RL, Cowley MA, Small CJ, Herzog H, Cohen MA, Dakin CL, et al. Gut hormone PYY(3-36) physiologically inhibits food intake. Nature. 2002. 418:650–654.
Article
16. Korbonits M, Blaine D, Elia M, Powell-Tuck J. Metabolic and hormonal changes during the refeeding period of prolonged fasting. Eur J Endocrinol. 2007. 157:157–166.
Article
17. Cohn JS, McNamara JR, Cohn SD, Ordovas JM, Schaefer EJ. Postprandial plasma lipoprotein changes in human subjects of different ages. J Lipid Res. 1988. 29:469–479.
Article
18. De Feo P, Horber FF, Haymond MW. Meal stimulation of albumin synthesis: a significant contributor to whole body protein synthesis in humans. Am J Physiol. 1992. 263:E794–E799.
Article
19. Caso G, Feiner J, Mileva I, Bryan LJ, Kelly P, Autio K, et al. Response of albumin synthesis to oral nutrients in young and elderly subjects. Am J Clin Nutr. 2007. 85:446–451.
Article
20. Hunter KA, Ballmer PE, Anderson SE, Broom J, Garlick PJ, McNurlan MA. Acute stimulation of albumin synthesis rate with oral meal feeding in healthy subjects measured with [ring-2H5]phenylalanine. Clin Sci (Lond). 1995. 88:235–242.
Article
21. Jefferson LS. Lilly Lecture 1979: role of insulin in the regulation of protein synthesis. Diabetes. 1980. 29:487–496.
22. Ryan MC, Abbasi F, Lamendola C, Carter S, McLaughlin TL. Serum alanine aminotransferase levels decrease further with carbohydrate than fat restriction in insulin-resistant adults. Diabetes Care. 2007. 30:1075–1080.
Article
23. Meyer BH, Scholtz HE, Schall R, Müller FO, Hundt HK, Maree JS. The effect of fasting on total serum bilirubin concentrations. Br J Clin Pharmacol. 1995. 39:169–171.
Article
24. Cowan RE, Thompson RP. Fatty acids and the control of bilirubin levels in blood. Med Hypotheses. 1983. 11:343–351.
Article
25. Al-Rubeaan K, Siddiqui K, Abu Risheh K, Hamsirani R, Alzekri A, Alaseem A, et al. Correlation between serum electrolytes and fasting glucose and Hb1Ac in Saudi diabetic patients. Biol Trace Elem Res. 2011. 144:463–468.
Article
26. Rohrscheib M, Tzamaloukas AH, Ing TS, Siamopoulos KC, Elisaf MS, Murata HG. Serum potassium concentration in hyperglycemia of chronic dialysis. Adv Perit Dial. 2005. 21:102–105.
27. Gozansky DM, Herman RH. Water and sodium retention in the fasted and refed human. Am J Clin Nutr. 1971. 24:869–871.
Article
28. Bloom WL. Inhibition of salt excretion by carbohydrate. Arch Intern Med. 1962. 109:26–32.
Article
29. Fernández-Real JM, López-Bermejo A, Ricart W. Cross-talk between iron metabolism and diabetes. Diabetes. 2002. 51:2348–2354.
30. Ricós C, Cava F, García-Lario JV, Hernández A, Iglesias N, Jiménez CV, et al. The reference change value: a proposal to interpret laboratory reports in serial testing based on biological variation. Scand J Clin Lab Invest. 2004. 64:175–184.
Article
31. Westgard J. Desirable Biological Variation Database Specifications. Updated on Jan 2012. http://www.westgard.com/biodatabase1.htm.
32. Cembrowski GS, Tran DV, Higgins TN. The use of serial patient blood gas, electrolyte and glucose results to derive biologic variation: a new tool to assess the acceptability of intensive care unit testing. Clin Chem Lab Med. 2010. 48:1447–1454.
Article
33. Plebani M, Lippi G. Biological variation and reference change values: an essential piece of the puzzle of laboratory testing. Clin Chem Lab Med. 2012. 50:189–190.
Article
34. Boldt J. Use of albumin: an update. Br J Anaesth. 2010. 104:276–284.
35. Kestenbaum B, Belozeroff V. Mineral metabolism disturbances in patients with chronic kidney disease. Eur J Clin Invest. 2007. 37:607–622.
Article
36. Locatelli F, Cannata-Andía JB, Drüeke TB, Hörl WH, Fouque D, Heimburger O, et al. Management of disturbances of calcium and phosphate metabolism in chronic renal insufficiency, with emphasis on the control of hyperphosphataemia. Nephrol Dial Transplant. 2002. 17:723–731.
Article
37. Block GA, Hulbert-Shearon TE, Levin NW, Port FK. Association of serum phosphorus and calcium x phosphate product with mortality risk in chronic hemodialysis patients: a national study. Am J Kidney Dis. 1998. 31:607–617.
Article
38. Young EW, Akiba T, Albert JM, McCarthy JT, Kerr PG, Mendelssohn DC, et al. Magnitude and impact of abnormal mineral metabolism in hemodialysis patients in the Dialysis Outcomes and Practice Patterns Study (DOPPS). Am J Kidney Dis. 2004. 44:34–38.
Article
39. National Kidney Foundation. K/DOQI clinical practice guidelines for bone metabolism and disease in chronic kidney disease. Am J Kidney Dis. 2003. 42(4 Suppl 3):S1–S201.
40. Ferrari P, Singer R, Agarwal A, Hurn A, Townsend MA, Chubb P. Serum phosphate is an important determinant of corrected serum calcium in end-stage kidney disease. Nephrology (Carlton). 2009. 14:383–388.
Article
Full Text Links
  • ALM
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr