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Acute phase reactants (APRs) have not been investigated in white rhinoceros (Ceratotherium simum). This study aimed to identify clinically useful APRs in this species. Reference intervals (RIs) were generated for albumin, fibrinogen, haptoglobin, iron and serum amyloid A (SAA) from 48 free-ranging animals, except for SAA (n = 23). APR concentrations between healthy animals and those with tissue injury (inflammation) (n = 30) were compared. Diagnostic performance was evaluated using receiver-operator characteristic (ROC) curve and logistic regression analyses. RIs were: albumin 18-31 g/L, fibrinogen 1.7-2.9 g/L, haptoglobin 1.0-4.3 g/L, iron 9.7-35.0 µmol/L, SAA <20 mg/L. Iron and albumin were lower and fibrinogen, haptoglobin and SAA higher in injured vs. healthy animals. Iron showed the best diagnostic accuracy followed by fibrinogen, albumin, haptoglobin and SAA. Iron ≤ 15.1 µmol/L and haptoglobin >4.7 g/L were significant predictors of inflammatory status and together correctly predicted the clinical status of 91% of cases. SAA > 20 mg/L had a specificity of 100%. In conclusion, albumin and iron are negative and fibrinogen, haptoglobin and SAA positive APRs in the white rhinoceros. The combination of iron and haptoglobin had an excellent diagnostic accuracy for detecting inflammation.

Investigation of globulin fractions by serum protein electrophoresis (SPE) is the first step towards evaluation of the proteome in the southern white rhinoceros (Ceratotherium simum simum). Furthermore, identification of changes in globulins in animals with poaching and other injuries can guide discovery of potentially useful biomarkers of inflammation. The aim of this study was to develop reference intervals for agarose gel SPE in healthy white rhinoceros and to compare these serum protein electrophoresis results to those from animals with tissue trauma. Reference intervals for total serum protein and agarose gel electrophoretic albumin and globulin fractions were generated using serum samples from 49 healthy free-ranging adult white rhinoceros. A standardised gating system together with identification of specific proteins by mass spectrometry aided in fraction identification. Six globulin fractions were identified: α1a, α1b, α2, β1, β2 and γ. Reference intervals were generated for total serum protein (76–111 g/L), albumin (10–27 g/L) and globulin fractions (α1a: 1.6–3.2 g/L; α1b: 1.7–3.6 g/L; α2: 16.1–26.6 g/L; β1: 6.6–18.2 g/L; β2: 11.8–30.4 g/L; γ: 10.4–23.1 g/L; albumin: globulin ratio: 0.12–0.39). Results were compared to those from 30 animals with various degrees and chronicities of tissue trauma. Wounded animals had lower concentrations of total serum protein, albumin, total globulin, α and β1 globulins, lower percentages of α2 and β1 globulins, and higher percentages of β2 and γ globulins. These protein changes are similar to those seen in human patients with wounds rather than classic acute phase or chronic inflammatory responses.

BackgroundA wide spectrum of laboratory tests is available to aid diagnosis and classification of equine inflammatory disease.ObjectivesTo compare diagnostic efficacy and combined predictive capability of the myeloperoxidase index (MPXI), and plasma fibrinogen, iron and serum amyloid A (SAA) concentrations for the diagnosis of inflammation.AnimalsTwenty‐six hospitalized horses with systemic inflammation (SI), 114 with local inflammation (LI) and 61 healthy horses or those with noninflammatory disease (NI) were included.MethodsA retrospective study was performed; clinicopathologic data from horses were compared between groups. Receiver‐operator characteristic (ROC) curves were used to evaluate diagnostic efficacy; classification and regression tree analysis (CART) and logistic regression analysis were used to generate diagnostic algorithms.ResultsHorses with SI had significantly higher SAA than horses with LI (P = .007) and NI (P < .001) and lower iron concentrations than horses with LI (P < .001) and NI (P < .001). Fibrinogen concentration was higher in horses with inflammation than in those without inflammation (P = .002). There was no difference between the SI and LI groups. White blood cell count, neutrophil count and MPXI were similar between groups. SAA had the highest accuracy for diagnosing inflammation (area under ROC curve [AUC], 0.83 ± 0.06) and iron and SAA concentration had the highest accuracy for differentiating SI from LI (AUC, 0.80 ± 0.09 and 0.73 ± 0.10 respectively). Predictive modeling failed to generate useful algorithms and classification of cases was moderate.Conclusions and Clinical ImportanceVery high SAA and low iron concentrations may reflect SI, but diagnostic guidelines based on quantitative results of inflammatory markers could not be formulated.

Abstract. Error recording and management is an integral part of a clinical laboratory quality management system. Analysis and review of recorded errors lead to corrective and preventive actions through modification of existing processes and, ultimately, to quality improvement. Laboratory errors can be divided into preanalytical, analytical, and postanalytical errors depending on where in the laboratory cycle the errors occur. The purpose of the current report is to introduce an error management system in use in a veterinary diagnostic laboratory as well as to examine the amount and types of error recorded during the 8-year period from 2003 to 2010. Annual error reports generated during this period by the error recording system were reviewed, and annual error rates were calculated. In addition, errors were divided into preanalytical, analytical, postanalytical, and "other" categories, and their frequency was examined. Data were further compared to that available from human diagnostic laboratories. Finally, sigma metrics were calculated for the various error categories. Annual error rates per total number of samples ranged from 1.3% in 2003 to 0.7% in 2010. Preanalytical errors ranged from 52% to 77%, analytical from 4% to 14%, postanalytical from 9% to 21%, and other error from 6% to 19% of total errors. Sigma metrics ranged from 4.1 to 4.7. All data were comparable to that reported in human clinical laboratories. The incremental annual reduction of error shows that use of an error management system led to quality improvement.Key words: Error management; laboratory error; quality management; veterinary laboratory. Special ArticleError management in a veterinary laboratory 459 laboratories. A small number of reports have been published about error management in human laboratory medicine.Most of the studies concerning human laboratory error management advocate the use of an error management system that evaluates errors within the framework of the Total Testing Process (TTP). 1,7,15,16 The TTP breaks laboratory testing down into 11 steps, starting with a clinical question that prompts a test selection and ending with the impact of the test result on patient care.2 These steps are grouped into preanalytical, analytical, and postanalytical phases, with some authors also describing pre-preanalytical and postpostanalytical phases. 15 Alternatively, errors may also be classified according to who bears responsibility for the event, preventability, or the impact on patient care.10 Such studies concerning error management in human medical laboratories are heterogeneous, and reported error rates differ according to study design, TTP steps analyzed, and whether results are reported per patient, per sample, or per test result. Results vary from errors occurring in 0.05% of patients in a clinical chemistry section to 0.61% of test results across a whole laboratory over 3 years.3 Other studies report error frequencies as 1:1,000 (0.1%), 1 error per 33-50 events (2-3%), or 1 error per 214-8,300 (0.01-0.5%) of laboratory results. ...

Introduction Acute phase reactants (APRs) have not been investigated in free‐living African elephants (Loxodonta africana), and there is little information about negative APRs albumin and serum iron in elephants. Objectives We aimed to generate reference intervals (RIs) for APRs for free‐living African elephants, and to determine the diagnostic performance of APRs in apparently healthy elephants and elephants with inflammatory lesions. Methods Stored serum samples from 49 apparently healthy and 16 injured free‐living elephants were used. The following APRs and methods were included: albumin, bromocresol green; haptoglobin, colorimetric assay; serum amyloid A (SAA), multispecies immunoturbidometric assay, and serum iron with ferrozine method. Reference intervals were generated using the nonparametric method. Indices of diagnostic accuracy were determined by receiver‐operator characteristic (ROC) curve analysis. Results Reference intervals were: albumin 41–55 g/L, haptoglobin 0.16–3.51 g/L, SAA < 10 mg/L, and serum iron 8.60–16.99 μmol/L. Serum iron and albumin concentrations were lower and haptoglobin and SAA concentrations were higher in the injured group. Serum iron had the best ability to predict health or inflammation, followed by haptoglobin, SAA, and albumin, with the area under the ROC curve ranging from 0.88–0.93. Conclusions SAA concentrations were lower in healthy African vs Asian elephants, and species‐specific RIs should be used. Serum iron was determined to be a diagnostically useful negative APR which should be added to APR panels for elephants.

The African elephant (Loxodonta africana) is listed as vulnerable, with wild populations threatened by habitat loss and poaching. Clinical pathology is used to detect and monitor disease and injury, however existing reference interval (RI) studies for this species have been performed with outdated analytical methods, small sample sizes or using only managed animals. The aim of this study was to generate hematology and clinical chemistry RIs, using samples from the free-ranging elephant population in the Kruger National Park, South Africa. Hematology RIs were derived from EDTA whole blood samples automatically analyzed (n = 23); manual PCV measured from 48 samples; and differential cell count results (n = 51) were included. Clinical chemistry RIs were generated from the results of automated analyzers on stored serum samples (n = 50). Reference intervals were generated according to American Society for Veterinary Clinical Pathology guidelines with a strict exclusion of outliers. Hematology RIs were: PCV 34–49%, RBC 2.80–3.96 × 1012/L, HGB 116–163 g/L, MCV 112–134 fL, MCH 35.5–45.2 pg, MCHC 314–364 g/L, PLT 182–386 × 109/L, WBC 7.5–15.2 × 109/L, segmented heterophils 1.5–4.0 × 109/L, band heterophils 0.0–0.2 × 109/L, total monocytes 3.6–7.6 × 109/L (means for “regular” were 35.2%, bilobed 8.6%, round 3.9% of total leukocytes), lymphocytes 1.1–5.5 × 109/L, eosinophils 0.0–0.9 × 109/L, basophils 0.0–0.1 × 109/L. Clinical chemistry RIs were: albumin 41–55 g/L, ALP 30–122 U/L, AST 9–34 U/L, calcium 2.56–3.02 mmol/L, CK 85–322 U/L, GGT 7–16 U/L, globulin 30–59 g/L, magnesium 1.15–1.70 mmol/L, phosphorus 1.28–2.31 mmol/L, total protein 77–109 g/L, urea 1.2–4.6 mmol/L. Reference intervals were narrower than those reported in other studies. These RI will be helpful in the future management of injured or diseased elephants in national parks and zoological settings.

SummaryObjective: An increased risk of mast cell tumours (MCT) in certain breeds has been described repeatedly in the literature. The incidence of MCTs for registered breeds in Austria, an estimate of the risk by means of the odds ratios based on breed as well as the anatomic localisation of MCTs were examined. Material and methods: In the first part of the study, the ranking of breeds in Austria based on 147,802 dogs with known breed (including mixed breed) was determined, based on those dogs included in the laboratory data base from 2000 to 2010. In the second part of the study, 476 dogs were identified with MCTs and analysed by age, sex, Patnaik grade of MCT and breed distribution. The odds ratios with confidence intervals were calculated for all breeds with skin tumours. Results: The age distribution showed a peak in the age group from 6.1 to 8.0 years; 70% of MCTs were localised to the head and trunk. No significant difference was found based on gender. The evaluation of the odds ratios showed that only four of the 20 of the most popular in Austria breeds (Boxer, Bernese Mountain Dog, Golden Retriever, Spaniel) had an increased risk; on the other hand, some breeds which have not been previously identified in the literature were indicated to have a significantly increased risk for MCT (e.g., Dogo Argentino, Tibetan Spaniel, Pyrenean Mountain Dog, Beauceron, and Austrian Smooth-haired Hound). Conclusion and clinical relevance: Because disease risk may influence the popularity of some currently rare breeds, consultation with breeders and owners regarding the identification of the breeds newly identified in this study as an increased risk for development of mast cell tumours is indicated. Schlüsselwörter