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Blood biochemistry: overview
Overview
- Measuring serum or plasma levels of nutrients, metabolites, enzymes, etc can provide general or specific data about organ function and disease processes.
- Commonly measured parameters include:
- Alanine aminotransferase (ALT) Blood biochemistry: alanine aminotransferase (SGPT, ALT).
- Albumin Blood biochemistry: albumin.
- Alkaline phosphatase (ALP) Blood biochemistry: alkaline phosphatase.
- Ammonia Blood biochemistry: ammonia.
- Aspartate aminotransferase (AST) Blood biochemistry: aspartate aminotransferase.
- Bicarbonate Blood biochemistry: bicarbonate.
- Bile acids Blood biochemistry: bile acid.
- Bilirubin - direct Blood biochemistry: direct bilirubin and total Blood biochemistry: total bilirubin.
- Calcium Blood biochemistry: total calcium.
- Chloride Blood biochemistry: chloride.
- Cholesterol Blood biochemistry: cholesterol.
- Creatinine Blood biochemistry: creatinine.
- Creatinine kinase (CPK) Blood biochemistry: creatine phosphokinase.
- Gamma globulins Blood biochemistry: gamma globulin.
- Gamma glutamyl transferase (GGT) Blood biochemistry: gamma glutamyl transferase.
- Globulin Blood biochemistry: total globulin.
- Glucose Blood biochemistry: glucose.
- Lactate dehydrogenase (LDH) Blood biochemistry: lactate dehydrogenase.
- Phosphate Blood biochemistry: phosphate.
- Potassium Blood biochemistry: potassium.
- Sodium Blood biochemistry: sodium.
- Total protein Blood biochemistry: total protein.
- Urea Blood biochemistry: urea.
More specific tests
- Amylase Blood biochemistry: alpha amylase.
- C reactive protein.
- Folate Blood biochemistry: folate.
- Free fatty acids.
- Fructosamine Blood biochemistry: fructosamine.
- Glycerol.
- Glycosylated hemoglobin.
- Hormones: cortisol, thyroxine Thyroxine assay, parathyroid PTH assay.
- Iron Blood biochemistry: iron.
- Lead Lead toxicity.
- Lipase Blood biochemistry: lipase.
- Triglycerides.
- Trypsin-like immunoreactivity (TLI) Blood biochemistry: trypsin-like immunoreactivity.
- Vitamin B12 Blood biochemistry: vitamin B12.
Sampling
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Tests
Methodologies
- A number of different methodologies may be available for any given test.
Availability
- Many tests are routinely available. If in doubt, contact the laboratory to confirm availability of a specific test.
Validity
Sensitivity
- The ability of a test to produce a positive result in all animals that do have disease. A high sensitivity may be associated with a reduction in specificity as false positive reactions may occur.
Specificity
- The ability of a test to produce a positive result only in animals that do have disease. A high specificity may be associated with a lower sensitivity as some false negative may occur.
Predictive value
- How well the test performs in a given population of animals.
- Influenced by prevalence of the disease in the population being tested.
- Predictive value = how well the test performs in a given population of animals.
- Positive predictive value is probability of an abnormal test result indicating presence of disease.
- Negative predictive value is probability of a test result that is within normal limits corresponding to the absence of disease. Influenced by prevalence of the disease in the population being tested.
- Predictive value of positive test = p x sensitivity/p x sensitivity + (1-p) x (1-specificity).
- Predictive value of a negative test = (1-p) x specificity/(1-p) x specificity + P X (1-sensitivity).
- p = prevalence of disease.
Example
- In a study of dogs with and without x-disease (diagnosed at necropsy) the following results are obtained:
- Positive with test : x-disease present 235 (TP), x-disease absent 16 (FP) - total 251.
- Negative with test: x-disease present 15 (FN), x-disease absent 200 (TN) - total 215.
- Total: x-disease present - 250, total x-disease absent -216.
- 1. Sensitivity = TPx100/TP+FN = 235x100/235+15 = 235/250x100 = 94%.
- 2. Specificity = TN/TN+FPx100 = 200/200+16x100 = 200/216x100 = 93%.
- It is estimated that x-disease occurs in about 20% of the population that will be tested.
- 3.Predictive value of a positive test = p(sens)/p(sens)+(1-p)(1-spec) = 0.20(0.94)/20(94)+(0.80)(0.07) = 0.1880/0.1880+0.0560 = 0.1880/0.2440 = 0.77. So you would expect disease in 77 out of every 100 with a positive test.
- If prevalence is only 2%: PVPT =0 .02(0.94)/0.02(0.94)+(0.80)(0.07) = 0.0188/0.0188+.0560 = 0.0188/0.0748 = 0.25. So you would expect to have x-disease in only 25 animals out of every 100 with a positive test.
- 4. Predictive value of a negative test (PVNT) = (1-p)(spec)/(1-p)(spec)+p(1-sens).
- If prevalence is 20%: (0.80)(0.93)/(0.80)(0.93)+0.20(0.06) = 0.7444/0.744+0.012 = 0.744/0.756 = 0.98. So would expect 98 out of every 100 animals with a negative test to be truly free of x-disease.
- If prevalence is 2%: (0.98)(0.93)/(0.98)(0.93)+(0.02)(0.06) = 0.9114/0.9114+0.0012 = 0.9114/0.9126 = 0.998. So would expect 99.8 out of every 100 dogs with a negative test to be truly free of x-disease.
Technique intrinsic limitations
- In general, results of any given test are most significant when interpreted in conjunction with other laboratory and clinical findings.
Result Data
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Further Reading
Publications
Refereed papers
- Recent references from VetMedResource and PubMed.
- Levy J K, Crawford P C & Werner L L (2006) Effect of age on reference intervals of serum biochemical values in kittens. JAVMA 228 (7), 1033-1037 PubMed.
Other sources of information
- Kaneko J J, Harvey J W & Brass M L (1997) Eds. Clinical Biochemistry of Domestic Animals. 5th edn. Academic Press, USA.