Background:Ventriculoperitoneal shunting (VPS) is the standard treatment for congenital internal hydrocephalus in dogs; however, obstruction of the ventricular catheter is a frequent and serious complication. In human medicine, several predictors of catheter obstruction have been identified, while corresponding risk factors in veterinary patients remain largely unknown. Objectives:This study aimed to identify potential risk factors for ventricular catheter obstruction after VPS implantation in dogs with congenital internal hydrocephalus. Methods:A retrospective cohort study was conducted involving 100 client-owned dogs diagnosed with congenital internal hydrocephalus and treated with VPS implantation between 2001 and 2022. The medical records and magnetic resonance imaging (MRI) data of these dogs were reviewed for age, sex, breed, body weight, ventricular size, ventricular catheter position, and preoperative medical treatments. Cerebrospinal fluid (CSF) samples were analyzed for cell count, red blood cell count, protein concentration, and cytology before and after surgery. Single logistic regression and chi-squared tests were performed to evaluate associations with ventricular catheter obstruction. Results:Obstruction occurred in 9 of the 100 dogs examined (9%; 95% confidence interval 3-15%), with an onset ranging from 8 to 210 days after VPS surgery (median 38 days). No significant associations were found between demographic factors, ventricle-to-brain ratio, ventricular catheter position, preoperative medical treatment, or CSF parameters and the occurrence of obstruction. Cerebrospinal fluid analysis revealed marked postoperative increases in cell counts, protein concentration, and red blood cell counts, peaking within the first week after surgery and gradually returning to reference ranges at the 3-month follow-up. Histological examination of obstructed catheters in three dogs demonstrated intraluminal blockage caused by inflammatory infiltrates, fibrin, and choroid plexus cells. Conclusion:Obstruction of the ventricular catheter remains a clinically important complication after VPS implantation in dogs with internal hydrocephalus. No definitive risk factors could be identified in this study. The observed postoperative CSF changes appear to reflect inflammatory and surgical responses rather than being predictors of obstruction. Further investigations with larger case numbers and detailed immunological analyses are required to clarify the underlying mechanisms and to improve prevention strategies.

Babesia canis is a protozoan vector-borne pathogen causing infections in dogs. Acute B. canis infections are emerging in central and eastern Europe. Clinicopathological abnormalities include fever, thrombocytopenia, and pigmenturia. This retrospective study aimed to analyse anamnesis, stays abroad, clinicopathological abnormalities, therapy, and outcome in dogs with acute B. canis infections in Germany. Three hundred and forty-two dogs with positive piroplasmid-PCR results (B. canis identified after sequencing) and negative Anaplasma phagocytophilum-PCR results between January 2018 and December 2024 were included if data on hematocrit, platelets, and leukocytes were available. Information about anamnesis, clinical findings, therapy, and outcome was collected through questionnaires. Acute B. canis infections occurred mainly in autumn (218/342; 63.7%), followed by spring (67/342; 19.6%), winter (34/342; 9.9%), and summer (23/342; 6.7%). Most dogs tested positive in northern federal states (259/342; 75.7%), with Berlin/Brandenburg, Saxony, Saxony-Anhalt, the Saarland, the Rhine-Main area and the Ruhr area classified as high-risk areas. Lethargy (147/220; 66.8%) and fever (127/228; 55.7%) were most frequently reported. Pigmenturia was detected in 53/204 dogs (26.0%). All 164 dogs with available information on treatment received imidocarb dipropionate (median dosage 3.3 mg/kg; 1.7-6.8 mg/kg body weight). An uncomplicated course of disease was reported in most dogs (169/193, 87.6%). The mortality rate was 6.7%. Acute B. canis infections are most often uncomplicated if prompt treatment is initiated and represent a differential diagnosis in case of thrombocytopenia throughout the year, even when presented without fever and pigmenturia, especially in high-risk areas.

Feline obesity is common, and in other species it has been linked to immune dysregulation; yet its immunological consequences in cats, and their modulation by age and sex, remain poorly defined. Whole blood from 78 neutered client-owned cats (37 males, 41 females; 1–16 years) was analyzed by flow cytometry using a panel characterizing T cells (including CD5+CD4+ and CD5+CD8+ subsets), B cells (CD21+) and natural killer (CD56+) cells with their activation (CD80) and proliferation (Ki67) status. Cats were grouped by body condition score into normal-weight (4–5) and overweight (6–9); lymphocyte proliferation was assessed in a subset by a carboxyfluorescein succinimidyl ester assay after concanavalin A stimulation, and serum amyloid A, triglycerides and adiponectin were measured in overweight cats. Across the cohort, overweight cats displayed higher frequencies of proliferating CD21+Ki67+ B cells than normal-weight cats, while the proliferation assay was descriptively consistent with enhanced T-cell proliferation in both sexes. Increasing age was associated with a decline in CD5+CD4+ T cells in both sexes and, in females, additionally in CD5+CD21+ cells alongside rising CD80 expression. Sex differences shifted across life, from B-cell activation in young adults to T-cell subsets in adults (higher CD5+CD8+ in males, higher Ki67+ fractions in females) and CD56+ NK cells in the oldest cats. Body-condition effects were largely age- and sex-specific and emerged only after stratification: adult overweight males showed higher proliferating CD4+Ki67+ and CD8+Ki67+ T cells, young-adult overweight females higher CD5+ and activated CD5+CD21+CD80+ cells, and aged overweight females fewer proliferating CD5+CD21+Ki67+ B cells. Among overweight cats, higher adiponectin was associated with fewer CD5+ lymphocytes, with no associations for serum amyloid A or triglycerides. Overall, feline obesity was associated with subtle changes in immune-cell composition but more pronounced effects on lymphocyte proliferative responsiveness, both strongly modulated by age and sex.

Babesia canis infections are considered an emerging tick-borne disease most often with unspecific clinical signs. Two injections of 6.6 mg/kg bodyweight (BW) imidocarb dipropionate (ID) in a timeframe of 14 days are recommended for treatment. Babesia antibody levels are protective against severe disease. This prospective study aimed to describe clinicopathological abnormalities and Babesia antibody levels in 23 dogs with acute B. canis infections, defined by positive PCR sequencing results revealing B. canis on EDTA-blood, and to follow these dogs from T0 (diagnosis, first ID) to T1 (laboratory control, second ID), and T2 (laboratory control). Complete blood counts, biochemistry, coagulation profiles, Coombs’ testing, and Babesia spp. antibody levels were determined. Thrombocytopenia, anemia, hyperbilirubinemia, and acute phase-responses were the most detected. ID dosage ranged from 1.7 to 7.0 mg/kg BW (median: 4.2 mg/kg BW). All PCR-results were negative at T1 and T2. At T1 (median 15 days after T0), laboratory abnormalities significantly improved but no further improvement was noted comparing T1 to T2 (median 32 days after T0). Initially serologically negative dogs built up Babesia antibody levels by T1, which mostly dropped by T2. All 23 dogs were PCR-negative at T1 besides the wide range in ID dosage. Laboratory abnormalities resolved quickly and all dogs had an uncomplicated course of disease. Dogs should be checked by PCR 14 days after the first imidocarb dipropionate injection. If the PCR result is negative and clinicopathological abnormalities have significantly improved, a second injection is not recommended to avoid a decrease in protective antibody levels.

Relapses of canine leishmaniasis during allopurinol treatment are common and complicate the course of disease. S-adenosylmethionine synthetase (METK) gene copy numbers (CN) < 3.0 have been demonstrated in allopurinol-resistant Leishmania infantum strains in vitro, but its clinical impact in vivo is still unclear. This study included 14 dogs divided into two cohorts (C): Cohort one (CI): nine dogs (64%) with signs of disease relapse under allopurinol treatment; Cohort two (CII): five dogs (36%) recently diagnosed with active leishmaniasis prior to treatment. Leishmania infantum infection was confirmed by positive PCR testing. METK gene CN was quantified by droplet digital PCR. Complete blood counts and biochemical profiles were performed where suitable samples were available. METK gene CN ranged from 0.7 to 3.4 [CN < 3.0 (n = 13), 93%; CN = 3.4 (n = 1), 7%; CI: CN = 1.2-3.4; CII: CN < 2.0 each]. Clinicopathological abnormalities consistent with active leishmaniasis were observed in all dogs. Allopurinol is used for long-term management of canine leishmaniasis, therefore identification of resistance to allopurinol is crucial, especially in cases of clinical relapses. Leishmaniasis poses a zoonotic risk to humans so that the spread of parasites due to resistance should be considered regarding the One Health aspect and the All Species approach. In dogs recently diagnosed with active leishmaniasis not receiving allopurinol yet, resistant L. infantum strains may most likely be transmitted by sand flies. The threshold of METK gene CN < 3.0 in vivo seems to be questionable in individual cases.

Abstract:Anemia is a frequent complication in cats with chronic kidney disease (CKD), mainly due to decreased erythropoietin (EPO) production resulting from a loss of renal erythropoietin-producing (REP) cells. Anemia affects both survival and quality of life by inducing clinical signs such as lethargy and anorexia. Early detection of anemia by monitoring hematocrit/packed cell volume (Htc/PCV) trends is essential to initiate treatment before progressive renal damage limits therapeutic effectiveness. Molidustat, a hypoxia-inducible factor prolyl hydroxylase inhibitor (HIF-PHI), is a novel oral drug stimulating endogenous erythropoietin synthesis. However, treatment has to be started when REP cells are still functional, with PCV target ranges between 30-40%. Regular monitoring following the International Renal Interest Society (IRIS) guidelines is essential to keep PCV within the target range and to determine when treatment should be started, stopped, or restarted. Moreover, monitoring the iron status is important since both functional and absolute iron deficiency might be seen in cats with CKD and can impair response to treatment.

Abstract:The knowledge regarding Babesia canis infections in puppies is limited to 3 dogs aged 43-46 days. A 45-day-old, male intact German Shepherd dog was presented due to lethargy, inappetence, and gait disorders. An acute Babesia canis infection was diagnosed by PCR. Marked thrombocytopenia, anemia, and hyperbilirubinemia were noted. A subcutaneous injection of imidocarb dipropionate (ID, 2.0 mg/kg bodyweight) was applied. The puppy's general condition significantly improved, but vomitus was noted. A negative PCR and mild hematological abnormalities were seen 14 days later. A second subcutaneous injection of ID (4.2 mg/kg bodyweight) was applied. Babesia canis infections should be considered in puppies with fever, marked thrombocytopenia, and marked anemia in the immunological gap. Next to vectorial transmission, transplacental Babesia canis infections are reported but considered unlikely in the presented puppy. The puppy responded well to a lower-ranged dose of ID, but side effects were noted (vomiting). In adult dogs, treatment of acute Babesia canis infections using ID dosed 6.6 mg/kg bodyweight is recommended. No safety regulations are published by the manufacturer regarding the use of ID in puppies, but vomitus is reported as a potential side effect after the use in adult dogs. A second ID injection (4.2 mg/kg bodyweight) was applied to avoid a potential disease relapse. The case report highlights the significance of the immunological gap in puppies with Babesia canis infections and the need for ectoparasite prophylaxis in puppies, if vector contact is possible.

BACKGROUND:Insect meals are increasingly being used as an ingredient in diets for dogs. However, little is known about their effects on the immune function of the animals. In the present investigation, mealworm meal was included in two complete diets with either a moderate or a high protein concentration (3.47% or 5.45% nitrogen in dry matter). Two diets with comparable protein levels (3.66% and 5.17% nitrogen in dry matter), but based on poultry by-product meal, served as control treatments. The diets were offered to 10 healthy adult beagle dogs, using a randomized crossover design. Each diet was fed for 4 weeks. Fasting blood samples were collected on day 24 of each feeding period for immune cell phenotyping, proliferation and phagocytosis assays, as well as for the measurement of plasma immunoglobulin (Ig) concentrations. RESULTS:All dogs remained healthy throughout the study. The percentages of CD4+ cells in the blood of the dogs were lower, and the percentages of CD8+ cells were higher, when the diets with mealworm meal and the high-protein diets were fed. An interaction effect between the dietary protein source and protein level could be detected for the phagocytic activity of blood granulocytes as well as for the plasma concentrations of IgA and IgE. CONCLUSIONS:Both the protein source and protein level had an impact on the immune system of the dogs. The observed immunological changes were, however, not linked to any adverse food reactions, suggesting that the clinical relevance of these findings is likely small. Further studies should evaluate the immunological properties of dietary mealworm meal also in diseased animals, particularly in allergic dogs.

Ziel der Studie Die Unterscheidung von Thrombozytopenie und EDTA-induzierter Pseudothrombozytopenie (EDTA-PTCP) ist von erheblicher klinischer Relevanz. Ziel der Untersuchung ist die Evaluation des Antikoagulans CTAD (Citrate-Theophyllin-Adenosin-Dipyridamole) zur Messung von equinen Thrombozyten über eine Lagerung von 24 Stunden.

AbstractBackgroundIn dogs, data on reference intervals (RIs) for cobalamin, markers of metabolism (markersB12met), age and sex effects are limited.Hypothesis/ObjectivesEstablish RI for serum cobalamin, homocysteine, and methylmalonic acid (sMMA) concentrations, urinary methylmalonic acid‐to‐creatinine ratio (uMMA:crea), and determine effects of sex and age.MethodsProspective study using healthy dogs (1‐10 years). Cobalamin and markersB12met were determined using chemiluminescence immunoassay (cobalamin) and liquid chromatography/tandem mass spectrometry (homocysteine, sMMA, uMMA:crea). In dogs with outlying data, changes in health, markersB12met, and onset of gastrointestinal signs were reevaluated after 9‐15 months.ResultsTwelve of 120 healthy dogs had abnormal uMMA:crea ratios. No other cobalamin analyte outliers were found. Outlying data re‐examination (odRE) was performed in 10/12 dogs. Chronic gastrointestinal signs occurred in 64% of odRE‐dogs, whereas 36% remained healthy. In total, 112 dogs (67 females, 45 males; median ages, 3.5 and 3.75 years, respectively) were included in RI analyses. Reference intervals were 178.5‐851 pmol/L (cobalamin), 5.8‐29.0 μmol/L (homocysteine), 45.3‐159.5 μg/L (sMMA), and ≤22.4 mg/g (uMMA:crea). Only age affected cobalamin concentrations (significant decrease). Compared by sex and neuter status, intact male dogs had significantly higher uMMA:crea ratios (median, 13.5; range, 1.9‐83.6 mg/g) than the other groups (median, 2.5; range, 0.7‐9.7 mg/g; P < .0001). Sex‐specific RI were ≤58.9 mg/g (intact male) vs ≤5.2 mg/g (females and neutered males).Conclusion and Clinical ImportanceIntact male dogs had significantly higher uMMA:crea ratios than the other groups. Thus, sex‐specific RI are recommended for uMMA:crea. Because of the wide distribution of uMMA:crea ratios, careful interpretation in intact male dogs is advised.

Babesia canis infections are of rising importance in Germany. This retrospective study aimed to correlate hematological and biochemical parameters with acute-phase proteins, levels of parasitemia and antibodies, as well as stays abroad in dogs with acute B. canis infection. Dogs in Germany tested PCR-positive for B. canis and negative for Anaplasma phagocytophilum from January 2018 to December 2024 were included if data on hematocrit, leukocytes, and platelets were available. Hematological scoring (HES) was performed by addition of points for mild (+ 1), moderate (+ 2), and marked (+ 3) anemia, thrombocytopenia, and leukopenia, as well as for the presence of pancytopenia (+ 3) and leukocytosis (+ 1). Results of biochemical and CRP analysis, Babesia antibody determination, and pathogen quantification were included, if available. P ≤ 0.05 in Spearman’s rank correlation was considered statistically significant. 342 dogs were included. History of stays abroad was known for 191/342 dogs (55.8

Einleitung Die Differenzierung bakterieller und steriler Zystitiden bei Hunden mit unterer Harnwegssymptomatik (LUTDS) ist für einen sparsamen Antibiotikaeinsatz entscheidend. Ziel war der Vergleich der in-house-Kultursysteme (IHKS) Uricult®​Vet und Flexicult®​Vet hinsichtlich Praxistauglichkeit, Sensitivität, Spezifität, Auswertbarkeit von Bakterienwachstum, korrekter Identifizierung der Bakteriengattung/-spezies und Antibiotikaresistenzen im Vergleich zur routinemäßig durchgeführten bakteriologischen Untersuchung mit Antibiogramm (Referenzkultur).

Synthesis and secretion of bile acids (BA) is a key physiological function of the liver. In pathological conditions like portosystemic shunt, hepatic insufficiency, hepatitis, or cirrhosis BA metabolism and secretion are disturbed. Quantification of total serum BA is an established diagnostic method to assess the general liver function and allows early detection of abnormalities, liver disease progression and guidance of treatment decisions. To date, data on comparative BA profiles in dogs are limited. However, BA profiles might be even better diagnostic parameters than total BA concentrations. On this background, the present study analyzed and compared individual BA profiles in serum, plasma, urine, and feces of 10 healthy pups and 40 adult healthy dogs using ultra-high performance liquid chromatography coupled to electrospray ionization mass spectrometry. Sample preparation was performed by solid-phase extraction for serum, plasma, and urine samples or by protein precipitation with methanol for the feces samples. For each dog, 22 different BA, including unconjugated BA and their glycine and taurine conjugates, were analyzed. In general, there was a great interindividual variation for the concentrations of single BA, mostly exemplified by the fact that cholic acid (CA) was by far the most prominent BA in blood and urine samples of some of the dogs (adults and pups), while in others, CA was under the detection limit. There were no significant age-related differences in the BA profiles, but pups showed generally lower absolute BA concentrations in serum, plasma, and urine. Taurine-conjugated BA were predominant in the serum and plasma of both pups (68%) and adults (74–75%), while unconjugated BA were predominant in the urine and feces of pups (64 and 95%, respectively) and adults (68 and 99%, respectively). The primary BA chenodeoxycholic acid and taurocholic acid and the secondary BA deoxycholic acid and lithocholic acid were the most robust analytes for potential diagnostic purpose. In conclusion, this study reports simultaneous BA profiling in dog serum, plasma, urine, and feces and provides valuable diagnostic data for subsequent clinical studies in dogs with different kinds of liver diseases.

The vCell 5 (scil Animal Care), a point-of-care hematology analyzer (POCA), was recently introduced to veterinary laboratories. This laser- and impedance-based analyzer is capable of providing a CBC with 5-part WBC differential count (Diff) along with WBC cytograms and flags serving as interpretation aids for numerical results. We compared the scil POCA-Diff to reference methods (i.e., manual differential count, Advia 2120 hematology analyzer [Siemens]) for canine and feline blood samples and considered WBC cytograms and flags. Total observed error (TEo), calculated from CV and bias%, was compared to total allowable error (TEa). Data were analyzed before and after a review process (exclusion of flagged and samples with invalid cytograms). For both species, correlation was good-to-excellent ( r s = 0.81–0.97) between both analyzers for all variables, except for feline monocytes ( r s = 0.21–0.63) and canine monocyte% ( r s = 0.50). Smallest biases were seen for neutrophils (dog: −5.7 to 0.8%; cat: 1.5–9.4%) with both reference methods. Quality requirements (TEo < TEa) were fulfilled for canine and feline neutrophils (TEo = 5.3–10.6%, TEa = 15%) and eosinophils (TEo = 67.1–83%, TEa = (90)–50%) considering at least one reference method. Our review process led to mildly higher r s -values for most variables. Although not completely satisfactory, the scil POCA provides reliable results in compliance with ASVCP quality goals for canine and feline neutrophils and eosinophils. Analyzer flag and cytogram analysis served as useful tools for QA, indicating the necessity for manual review of blood smears, and contributed to improvement of scil POCA performance.

BACKGROUND:Inhibition of hypoxia-inducible factor prolyl hydroxylase (HIF-PH) stimulates erythropoiesis in rats, dogs, monkeys, and humans. HYPOTHESIS/OBJECTIVE:Determine if molidustat, a novel HIF-PH inhibitor, stimulates erythropoiesis in healthy cats. ANIMALS:Seventeen healthy adult laboratory cats. METHODS:Randomized, placebo-controlled study. Cats were treated PO once daily with suspensions of 0 (Group 1; n = 6), 5 (Group 2; n = 6), or 10 (Group 3; n = 5) mg/kg of molidustat. Effects on red blood cell parameters, reticulocyte indices and plasma erythropoietin (EPO) concentrations were evaluated. Molidustat treatment was stopped when hematocrit (HCT) exceeded 60%. RESULTS:Compared to placebo, a significant increase in mean HCT was evident starting on Day 14 (Group 2:54.4% vs 40.3%, P < .001, 95% confidence interval [CI] for the difference [8.95-19.28]; Group 3:61.2% vs 40.3%, P < .001, 95% CI [15.48-26.43]) and remained significantly higher for the entire treatment period. In molidustat-treated groups, HCT exceeded 60% on Day 21 (Group 2) and Day 14 (Group 3). Mean HCT in molidustat-treated cats returned to within the reference range (29%-45%) after Day 56 and was numerically comparable to placebo from Day 70 onwards. Red blood cell count and hemoglobin concentrations followed a similar pattern as HCT. Mean EPO concentrations significantly increased after molidustat administration on all assessment days. Molidustat treatments were well tolerated. CONCLUSIONS AND CLINICAL IMPORTANCE:Marked erythropoietic effects were identified after daily administration of molidustat to healthy cats and additional studies are warranted to evaluate the effects in anemic cats.

Einleitung Die Differenzierung septischer (SE) und nicht-septischer Exsudate (NSE) ist für den empirischen Antibiotikaeinsatz entscheidend. Ziel war die Evaluation von Zellzahlbestimmung (TNCC), c-reaktivem Protein (CRP), Serum Amyloid A (SAA) und Adenosintriphosphat (ATP) zur Erkennung von SE.

Introduction Recently, the novel laser and impedance-based point-of-care hematology analyzer (POCA) scil vCell 5 was introduced providing a complete blood count including a 5-part differential count. White blood cell cytograms and flags are displayed automatically. The objective of the study was to evaluate the accuracy of the leukocyte differential count of the scil POCA for canine and feline specimens with consideration of leukocyte cytograms and flags in comparison to the corresponding reference methods, i.e., the ADVIA 2120 hematology analyzer and a manual 200-cell leukocyte differential count (MDiff).

Einleitung Störungen des Cobalaminhaushalts sind bei chronischen Hepatopathien beschrieben. Durch den Leber-Bypass ist auch bei Hunden mit congenitalem portosystemischen Shunt (PSS) eine Störung im Cobalaminhaushalt zu erwarten.

A robust quality management system for automated hematology analyzers is crucial for generating high-quality results and instilling confidence in analyzer function. A comprehensive quality management system comprises multiple aspects. Two major aspects are quality assurance (QA) and quality control (QC). QA is a framework and strategy for ensuring quality across the entire process, from blood draw through reported results. QA thus encompasses preanalytical to postanalytical variables related to result generation. QC, on the other hand, is focused exclusively on the analytical portion of quality management to ensure the function and performance of the analyzer itself. QC facilitates identification of analyzer problems so they can be addressed and fixed in a timely fashion. Recommendations for QC, including QC materials (QCMs), frequency of QC, and interpretation of QC results, are specific for the analyzer. The ideal QCM would (1) be able to assess the function and performance of all aspects of the hematology analyzer, (2) have a long shelf life, (3) be easy for the user to run and interpret, and (4) instill confidence in results for all species tested. To understand these requirements, it is imperative to understand the workflow of an automated hematology analyzer. Although the specifics vary among analyzers, the workflow follows the same general pattern (Table 1). The recommended QCM and the algorithms to interpret the QC results vary among analyzers due to differences in chemistry and detection methods. In addition to basic analyzer function, QC for veterinary analyzers should be able to detect species-specific differences in performance, including bias and drift. For analyzers in veterinary practices, ease of performing and interpreting QC is particularly important. Unlike reference or academic laboratories, staff in clinics typically do not have extensive training in quality management and may not have the same commitment to following QC recommendations and troubleshooting issues.1 Recommendations for in-clinic analyzers are often similar to those for reference laboratory instrumentation but with less frequent QC analysis and simpler rules for interpretation. For example, manufacturer-recommended QC frequency for in-clinic analyzers is often once per month versus daily. Regulations mandating QA and QC for veterinary in-clinic analyzers vary regionally. Nevertheless, one study of in-clinic analyzers in human medical settings, where stringent mandatory regulations exist,2 found that 19% of operators had not been trained to use the analyzer, 25% of operators failed to follow the manufacturer's procedures, and 32% failed to perform QC.3 The results of such a study would likely be similar or worse if done in veterinary practices. Practitioners often use in-clinic analyzers to streamline patient care with rapid results that can immediately inform patient care, and they might not understand the importance of QC for instilling confidence in those results or the risks of not performing QC. Hematology QC is often misunderstood by general practitioners, clinical pathologists, and other veterinary specialists. There are several myths surrounding QC that need clarification for better evaluation of the true benefits and shortcomings of traditional QC and QCM. In this editorial, we will address some common myths about QCM functionality and opportunities to continue to improve QC for in-clinic hematology analyzers through automation and inclusion of patient samples. Many practitioners and pathologists assume that fixed cell QCM (FC-QCM) closely mirrors patient samples and contains red blood cells (RBCs), white blood cells (WBCs), and platelets. The use of fresh cells in commercial QCM is unfortunately impractical because their shelf life is only days. Therefore, traditional FC-QCM uses cells that are mixed with a fixative (eg, glutaraldehyde) to improve stability and shelf life of the FC-QCM. The formulation and source of cells in commercial FC-QCM are proprietary, and there is limited information available to practitioners or clinical pathologists. Publicly available information about FC-QCM is often vague and includes statements like “partially derived from human sources.”a Cells in the FC-QCM can come from mammals (usually human), reptiles, birds, or a combination thereof. In some cases, FC-QCM use nucleated erythrocytes from reptiles or birds as WBC surrogates to assess WBC parameters since avian and reptile erythrocytes are easy to obtain in large numbers. Some commercial FC-QCM use small erythrocytes to assess analyzer platelet identification. When mammalian cells are used, they are usually human and may not accurately represent performance on veterinary species. Due to the lack of transparency about formulation, the true contents of a commercial FC-QCMs are not known, but they are not necessarily a close mimic of veterinary patient samples. Even with fixation, the shelf life of FC-QCM is short. FC-QCMs are often exquisitely sensitive to temperature, and improper storage further reduces their shelf life. Required FC-QCM for the Abaxis Vetscan HM5 hematology analyzer, for example, indicates that it is usable after opening for “up to 14 days if it is properly stored.”* Even when properly stored, changes in FC-QCM can occur over time due to aging. For some parameters, the expected aging changes in the QCM lead to alterations in QC targets over the lifespan of the QCM (Figure 1). Mishandling of the lot or using it beyond its expiration date causes further degradation of cells and may affect the utility of the QCM to provide accurate information about analyzer function. The exact QC targets and ranges can vary between lots of FC-QCM. It is recommended to update the analyzer with the QC targets for the new lot and to analyze both the new and old lots when switching lots to understand lot-to-lot bias. If clinics use FC-QCM every 2–4 weeks according to analyzer manufacturers' recommendations, they may only use a single lot of FC-QCM for one or two QC analyses due to the short shelf life. This makes it burdensome for clinics to compare lots and set lot-specific QC targets. However, skipping this step diminishes the ability of the FC-QCM to assess analyzer function and drift over time. The short shelf life of the FC-QCM, therefore, creates a significant financial and logistical burden on veterinary clinics and can prevent clinics from realizing the full potential value of QC. In addition to differences between FC-QCM components and patient samples, there are fundamental differences in analyzer workflow for FC-QCM and patient samples. Many of the steps and algorithms are QCM specific (Table 2), which impairs the ability of FC-QCM to fully evaluate analyzer function. The differences begin with sample handling in the clinic before analysis. FC-QCM must be stored in the refrigerator, brought to room temperature before use, and then quickly returned to the refrigerator. They are also mixed and loaded onto the analyzer differently than patient samples. Fixation of cells leads to alterations in stain uptake by cells, cell lysis, and response to other reagent chemistry. FC-QCM, therefore, may not be able to identify analyzer problems with sample loading, stains, and other reagent chemistry. Analyzers can extrapolate information from standardized materials to evaluate individual functions and do not need QCM to mimic patient samples. As we discussed before, FC-QCM can evaluate many aspects of analyzer function despite differences from fresh patient samples. QC-specific algorithms use standardized materials to compare current with expected analyzer function and extrapolate that information to analyzer performance on patient samples. For example, comparing detected events to expected events for standardized QCM concentration allows evaluation of the dilution, mixing, and fluidics functions. Moreover, evaluating changes in event size and complexity for standardized QCM provides information about sensor and laser alignment. Thus, evaluation of standardized materials is able to instill confidence that analyzer function is appropriate. Different types of analyzers (eg, impedance analyzers, flow cytometry analyzers, and fluorescence flow cytometry analyzers) function differently and have different required features for QCM. Commercial FC-QCM may be marketed specifically for one analyzer or for use with multiple analyzers. For instance, Para 12 Extend (Streck) is marketed for analyzers made by eight different companies, but analyzer-specific QC targets and reference intervals are provided to meet the needs of each analyzer. However, the applicability of one FC-QCM for different analyzers depends on if the formulation provides information that is relevant to that analyzer's technology and methodology. Analyzer algorithms and targets must be developed for the specific recommended FC-QCM since there are differences between analyzer requirements and FC-QCM components. Analyzer algorithms for identifying cells (eg, size, complexity, fluorescence) are species-specific and result in different scatterplots. Similarly, FC-QCM scatterplots do not necessarily mimic the plots for any veterinary species. Scatterplots for both patient samples and FC-QCM vary among analyzers because analyzers identify and characterize cells using different characteristics. If the recommended FC-QCM for the ADVIA 2100/120 is run through the analyzer as a sample, it looks reasonably like canine patient samples. When the same thing is done with the recommended FC-QCM on the IDEXX ProCyte Dx analyzer, plots look less like their corresponding canine patient scatterplots (Figure 2). Although these differences can be surprising or jarring for human observers, the similarities or differences between patient and FC-QCM plots are not informative about whether the FC-QCM is adequate for providing the needed information for the QC-related analyzer algorithms. As noted above, FC-QCM differs from veterinary patient samples. Most of us are familiar with the changes to staining patterns with Wright-type stains due to formalin exposure or fixation, but fixation of any type can alter fluorescence, staining characteristics, and response to chemical lysis. As a result, FC-QCM cannot reliably identify changes in analyzer chemistry that could impact patient samples from one or more veterinary species. Chemical alterations or degradation can have variable effects on different species. For example, minor osmolality changes in analyzer chemistry may not affect lysis of easily lysed canine RBCs but might reduce lysis of more lysis-resistant feline and equine RBCs.1 Changes in analyzer chemistry can also cause bias affecting one or more veterinary species but not FC-QCM. As a result, QC results from FC-QCM may indicate acceptable analyzer function even though results for some species are affected (Figure 3). Conversely, clinicians might erroneously believe that drift in the FC-QCM results indicates that patient results will be incorrect (Figure 4). QC results provide information about the performance of an analyzer on standardized QCM but should not be interpreted to always reflect whether patient results are reliable. Recognition of factors or changes that differentially affect FC-QCM results and veterinary patient results can be difficult if only one type of QC evaluation is performed. Continued improvement in QC recommendations to more quickly and accurately identify the problems that only affect patient samples is desirable and would facilitate appropriate corrective actions. There are required minimum QC requirements for reference and academic laboratories, but the actual QC frequency is often adapted to meet the risk analysis for the laboratory. This can lead to substantial differences among laboratories in the frequency of QC and in the choice of statistical rules chosen for QC interpretation. One study surveying laboratories at large, well-respected academic medical centers testing human patient samples found “no systematic approach to defining QC rules or frequency.”4 QC frequency varied from every 2 hours to every 24 hours, and selection of QC rules was often through institutional experience rather than through adoption of evidence-based rules like “Westgard Rules.”4 This variability in approaches to QC frequency and interpretation is likely similar in veterinary academic settings and amplified in veterinary clinics where there are fewer regulations and staff is less educated on QC. Risk assessment for choosing QC frequency and statistical analysis ideally includes identifying what potential problems could arise, the required result quality, risk to patient results, and what can be done to mitigate those risks.5, 6 In reference or academic laboratories, strategies like Six Sigma can be used to evaluate these risks and determine the optimal frequency of QC, the number of samples that can be analyzed between QC analysis, and the optimal rules for the interpretation of QC results7-9; however, many of these methods are impractical for use with in-clinic analyzers in the general practice setting. Although the same types of analyzer problems can occur in the reference or academic laboratory and the in-clinic laboratory setting, there may be differences in the quality goals, number of samples at risk, potential mitigating factors, and potential cost of mitigation. Manufacturers of in-clinic hematology analyzers may recommend a minimum of weekly or monthly external QC instead of daily. These are meant as minimum recommendations that would be appropriate for clinics that analyze a moderate number of samples; however, they might not be optimal for clinics at the extremes who either analyze large numbers of samples or rarely use the analyzer. In many clinics, the ratio of FC-QCM to patient sample analyses will be higher than in reference laboratories, even when minimum recommendations for QC are followed. If daily external QC is performed, this ratio would be further increased to a point that the time and financial burden could inadvertently discourage QC compliance for clinics. QC recommendations for in-clinic analyzers would ideally incorporate more specific risk assessment for different use scenarios to help clinics understand the risk-benefit analysis for their circumstances. Choice of statistical methods to interpret QC results is part of the risk analysis. A variety of statistical methods can be used for the interpretation of QC results with different degrees of rigor for identifying analyzer issues. Reference laboratories and clinics will have different ideal balances of maximizing the potential to identify analyzer issues and minimizing unnecessary troubleshooting and false rejection of results. Levey-Jennings charts are commonly used to track performance of QC over time.10, 11 These charts are often generated by the analyzer for easy viewing to assess QC performance. Different rules exist to evaluate whether the QC results are acceptable in different situations, and “Westgard Rules” are most commonly used.12 These rules vary in complexity from single rule to multi-rule methods and have different levels of stringency and different balances of risk (Figure 5). Most manufacturers recommend a single rule method, primarily the 13S rule. Under the 13S rule, results are not acceptable if they are more than 3 standard deviations (SDs) from the mean or target.13 Target ranges for this rule are fairly wide and minimize false rejection of QC results. Single rules can be tightened to be more sensitive to smaller drift and reject results with smaller deviations, for example, by incorporating both the magnitude and frequency of a deviation to determine if a QC result is acceptable. A 41S rule, for instance, would reject a 1 SD if it was the fourth such deviation in a row. A 41S rule would be more stringent and detect smaller deviations from the target but would be more likely to falsely reject QC results. Multiple rules (ie,13S and 41S) can be used to incorporate a variety of different magnitudes and durations of risk where any included rule can be used to reject a result. Similar to the frequency of QC, the choice of rule needs to reflect the particular risk management strategy appropriate for the reference laboratory or clinic, the volume of patient samples, and frequency of QC analyses. As such, complex rules are appropriate for reference laboratories with high sample volume and trained personnel but are unnecessarily complex for use in clinics. The frequent false rejection of QC results in clinics leads to unnecessary and frustrating analyzer downtime and troubleshooting that could erode the clinic's commitment to following QC recommendations. These common QC myths hide some of the true opportunities for improvement in QC, particularly QC in the in-clinic setting, where improvements in ease and compliance could lead to improved confidence in results from hematology analyzers. Although FC-QCM provides many of the answers about analyzer function and performance, FC-QCM alone does not allow us to assess all the components. Technological advances and research have resulted in new QC methodologies and materials being used in pockets across the industry without broad adoption. Many of these advances offer opportunities for continued improvement in hematology QC by combining different strategies and new QCM to provide a better overall view of analyzer function and thereby improve the potential for identification and resolution of analyzer issues. Noncellular QCMs, including manufactured beads, have many of the benefits of FC-QCM and have much longer stability and shelf life. Bead-based QCMs and calibration materials are commonly used as standards to verify fluidics, fluorescence, and optical performance in flow cytometers.14, 15 Bead-based QCM can be manufactured to individual specifications with high reproducibility. The design and manufacture of beads allow for a wide variety of bead types that can be specialized to best evaluate the analyzer function. The design of bead-based QCM can be specific to the cellular features that the analyzer evaluates, including size, refractility, and fluorescence. More complex features such as granularity or surface textures could be generated if relevant to the analyzer. The bead design can include features that allow the same beads to evaluate analyzer functions for red cells, white cells, and platelets, or for beads to specifically represent a single cell type. Some in-clinic hematology analyzers, like the IDEXX LaserCyte DX analyzer, already use bead-based QCM. Qualibeads are run with each sample to ensure that the analyzer functions properly and is standardized within and across runs on this analyzer.† Bead-based QCMs, like FC-QCMs, do not directly mimic patient sample cells and require QCM-specific algorithms and workflow steps (Table 2). As such, neither bead-based QCMs nor FC-QCMs assess all components of analyzer functionality on patient samples. However, the longer stability and easier storage of bead-based QCM make them more appealing for use on in-clinic analyzers. Many bead-based QCMs can be stored at room temperature and do not degrade with higher or lower temperatures. This makes bead-based QCM easier to ship and store in regions with temperature extremes, and it simplifies QC workflow. Improved thermal stability and shelf life also allow some bead-based QCM to be stored in the analyzer itself, thereby facilitating automation of QC analysis to reduce the clinic workflow and improve compliance with QC recommendations. Integration of patient samples into the QC strategy can help to fill some of the gaps left by FC-QCM or bead-based QCM. QC uses patient samples and can identify species-specific issues related to analyzer chemistry that are missed by other QCM. Several methods using patient samples have been described and found to be both practical and successful at evaluating the function of veterinary hematology analyzers.16-18 These strategies each have their own benefits and drawbacks. Patient-based population analysis quality control (PBA-QC) uses populations of patients previously analyzed on the instrument to identify drift, species-specific bias, or problems with analyzer chemistry. Since it uses data from actual patient samples, these data are generated with the normal patient workflow and can be used to assess all steps of the analysis, including preanalytical sample handling. Weighted moving averages from patient samples have been used to monitor analyzer performance for over 45 years for human hematology analyzers.19-22 Using averages allows both normal and abnormal patient results to be included in the QC analysis. However, clinics that analyze primarily or only abnormal samples may have averages that deviate from the normal targets. On the IDEXX ProCyte Dx, an in-clinic analyzer that uses PBA-QC, weighted average analysis evaluates groups of the most recent 10 patient sample results (Figures 3B–D and 4B–D). Since grouping and analysis can be performed automatically during analyzer downtime or in the background, PBA-QC does not require additional effort from the clinics to perform or seek out QC results. The frequency of PBA-QC analysis reflects the volume of patient samples analyzed and is, therefore, adaptive to the individual clinical setting and proportional to clinic analyzer use. Comparisons can also be made between the results from one individual clinic and the results of all clinics using the analyzer. This can provide additional information about drift for analyzers in both low-volume and high-volume clinics. Repeat patient testing (RPT-QC) uses patient samples differently and has been investigated in both human and veterinary medicine.17, 23 RPT-QC uses the expected rate of subtle changes in patient samples over time to evaluate analyzer performance.17, 24 Samples are re-processed at specific intervals after the original analysis to look for variation in samples. Algorithms are used to compare the expected results at different sample ages to the actual recorded values to identify both random and systematic error in the analyzer. However, since each sample can only be stored for approximately 24 hours, RPT-QC requires continual selection of new patient samples for QC. Given the requirement for daily identification of QC samples, careful storage, and repeat analysis at specific timepoints, RPT-QC is feasible for reference laboratories and possibly for in-clinic analyzers from some high-volume clinics, but not for most clinics where sample availability, cost, and technician training and time would provide major hurdles. Strategies for using patient samples have different strengths and drawbacks from FC-QCM and bead-based QCM. Since patient samples are used, there are no QC-specific analyzer workflows (Table 3), and species-specific drift can be detected for any species included in QC analysis. However, patient samples alone lack the standardization that FC-QCM allows and require access to normal samples. PBA-QC removes most logistical burden of FC-QCM and bead-based QC for in-clinic analyzers. Integration of traditional QCM and patient-based analyses within the clinic or analyzer QC strategy can provide the benefits of each approach while filling in the gaps from the use of any single approach (Table 4). Standardized QCM provides specific information about analyzer function and calibration, and patient-based analysis provides information about performance on chemistry function and individual species. PBA-QC can run in the background on the analyzer and identify issues in patient sample workflow missed by QCM analysis or that occur between routine scheduled QCM analysis. Traditionally, quality evaluation and maintenance of in-clinic analyzers have been entirely the responsibility of the clinic staff. However, there is wide variability in the commitment of clinics to perform QC and to understand the importance and significance of QC and quality management. There can also be logistical hurdles for clinics due to high patient volume and staff turnover. Automation of QC provides a path around these hurdles, presenting an opportunity to improve confidence in results from in-clinic analyzers across all clinics and to ensure that QC is performed at the recommended minimum frequency. Automated QC can be performed by the analyzer outside of work hours and without requiring effort or commitment from clinic staff. Additionally, automation of QC interpretation would improve and standardize recognition of analyzer problems and assist in troubleshooting for in-clinic analyzers. Centralization of QC interpretation could also more easily identify drift or other subtle issues by comparing an analyzer in one clinic to the general population of all similar analyzers. These subtle problems could be centrally identified with notifications automatically sent to clinic staff with appropriate next steps. Additionally, QC could automatically be repeated if there was a run failure, and analyzer or calibration issues could be fixed remotely. Partially transferring responsibility for performing QC analysis from the clinic to a centralized, automated system would improve overall compliance with QC recommendations and decrease strain on clinics. Automated QC could also facilitate using more stringent interpretive rules by removing resource and time barriers for more stringent analyses from the clinic. Automating both the QC and its interpretation should improve analyzer performance and instill better confidence in results from in-clinic hematology analyzers. Despite the importance of QC, it is often misunderstood or even ignored by clinicians. There are pervasive misconceptions and myths about quality control, the nature and requirements of QCM, and QC for in-clinic hematology analyzers. While FC-QCM provides valuable information about the health and performance of the analyzer system, they do not directly mimic patient samples and patient workflow, and they have a short shelf life. This short shelf life can be financially and logistically burdensome for clinics with low sample numbers and infrequent QC analysis. Direct mimicry of patient samples is not necessary for the benefits associated with QCM. Noncellular QCM can have similar benefits without the short shelf life of FC-QCM. However, both cellular and noncellular QCM fail to assess all aspects of patient sample analysis. Combining QCM and patient sample analysis (eg, PBA-QCM) can provide more ideal QC information about the analyzer function and identify species-specific issues with analyzer chemistry or drift. Risk assessment for in-clinic analyzers is different than for reference laboratory analyzers. As a result, the QC frequency and analysis recommended for the laboratory analyzer might not be appropriate for many clinics, especially ones with low sample numbers. There are unique challenges to ensuring appropriate analyzer function for in-clinic analyzers and QC compliance. Automation of QC analysis can help to improve compliance with minimum QC recommendations and to ensure accurate results for in-clinic analysis. This automation can also relieve some of the burden of QC from busy clinics. There are opportunities to continually improve the QC experience and compliance for in-clinic analyzers by extending QCM shelf life, improving thermal stability of QCM, and automating many of the QC activities. The concepts described here can be adapted and applied to different hematology analyzer technologies and are not specific to any particular manufacturer. Hematology analyzer manufacturers should strive toward improving QC in ways that increase the quality of results from in-clinic analyzers, reduce the financial and logistical burdens of QC, and improve overall patient care by minimizing analytical errors. JH, HTM, and DBD are or have been full-time employees of IDEXX Laboratories, Inc. All other authors serve as consultants for IDEXX Laboratories, Inc.

Swine inflammation and necrosis syndrome (SINS) can lead to significant clinical alterations at tail, ears, claws and other parts of the body in suckling piglets, weaners and fatteners. Clinical findings are associated with vasculitis, intima proliferation and thrombosis. The syndrome can be found in newborns, indicating a primarily endogenous aetiology. It has been hypothesized that SINS is triggered by gut-derived microbial-associated molecular patterns, causing derangements in liver metabolism and activity of peripheral white blood cells involving inflammation and blood haemostasis. In order to characterize these metabolic derangements of SINS for the first time, red and white blood counts, parameters of blood haemostasis, serum metabolites and acute phase proteins in the serum were analysed in 360 piglets, weaners and fatteners, each with significantly different SINS scores. SINS scores and haematological/clinical chemical parameters were significantly associated (P < 0.05), especially in weaners and fatteners. Higher degrees of clinical SINS were associated with increased numbers of monocytes and neutrophils. Blood coagulation was altered in weaners and a thrombocytopenia was found in fatteners. Additionally, acute phase proteins, especially C-reactive protein and fibrinogen were increased in serum. Serum metabolites and serum liver enzymes were slightly altered. Aspartate transaminase levels overall exceeded physiological limit and increased in parallel with SINS scores in fatteners. Clinical inflammation and necrosis at tail, ears, claws and other parts of the body were significantly associated with haematology and serum clinical chemistry, especially in weaners and fatteners. The involvement of inflammatory cells, blood coagulation, acute phase proteins and certain serum metabolites support the inflammatory-necrotising character of the syndrome and provide starting points for further studies to decipher its exact pathogenesis. The low to moderate variations seem less suitable for diagnostic use.