Accuracy of the IDEXX SediVue Dx analyzer for quantifying RBC and WBC indices in the urine sediments of cats and dogs compared with manual microscopic evaluations.

BACKGROUND: The IDEXX SediVue Dx (SediVue) is an automated, in-clinic urine sediment analyzer for veterinary patients. The bias between the results from manual microscopy and the SediVue is currently unknown. OBJECTIVES: To assess the diagnostic accuracy of the SediVue, we aimed to determine the bias between the SediVue (index test) and manual microscopy (reference standard) for the quantification of RBCs and WBCs in urine. METHODS: Urine remnant samples were collected from cats and dogs that contained RBCs (n = 462) and WBCs (n = 510). Retrospective analysis of results from urine sediment examinations using both manual microscopy (using a KOVA and DeciSlide system) and the SediVue (1.0.1.3) was performed. Bias was determined with Bland-Altman plots. SediVue-captured images from high-bias samples were reviewed, and biases were compared. RESULTS: The median bias for semi-quantitative RBC and WBC counts was determined for RBC and WBC counts. The cutoffs were RBC ≤ 5/HPF, 0.3; RBC 5.1-10/HPF, 10.1; RBC 10.1-20/HPF, 10.6; and RBC > 20/HPF, 28.93; WBC ≤ 5/HPF, 0.1; WBC 5.1-10/HPF, 2.2; WBC 10.1-20/HPF, 9.4; and WBC > 20/HPF, 26.6. High bias between the methods was identified in 98 samples (21.0%) with RBCs and 77 samples (15.7%) with WBCs. Reviewer-based enumeration of the SediVue-captured images decreased the percentage of samples with high bias to 17.3% for RBCs and to 11.4% for WBCs. CONCLUSIONS: Bias in the RBC and WBC counts between manual microscopy and the SediVue was unlikely to impact clinical interpretations in a majority of cases. Although reviewer enumeration of SediVue-captured images reduced observed bias, inherent differences between methodologies appeared to have a larger impact on the bias.

Comparing a Mobile Phone Automated System With a Paper and Email Data Collection System: Substudy Within a Randomized Controlled Trial.

BACKGROUND: Traditional data collection methods using paper and email are increasingly being replaced by data collection using mobile phones, although there is limited evidence evaluating the impact of mobile phone technology as part of an automated research management system on data collection and health outcomes. OBJECTIVE: The aim of this study is to compare a web-based mobile phone automated system (MPAS) with a more traditional delivery and data collection system combining paper and email data collection (PEDC) in a cohort of breastfeeding women. METHODS: We conducted a substudy of a randomized controlled trial in Sydney, Australia, which included women with uncomplicated term births who intended to breastfeed. Women were recruited within 72 hours of giving birth. A quasi-randomized number of women were recruited using the PEDC system, and the remainder were recruited using the MPAS. The outcomes assessed included the effectiveness of data collection, impact on study outcomes, response rate, acceptability, and cost analysis between the MPAS and PEDC methods. RESULTS: Women were recruited between April 2015 and December 2016. The analysis included 555 women: 471 using the MPAS and 84 using the PEDC. There were no differences in clinical outcomes between the 2 groups. At the end of the 8-week treatment phase, the MPAS group showed an increased response rate compared with the PEDC group (56% vs 37%; P<.001), which was also seen at the 2-, 6-, and 12-month follow-ups. At the 2-month follow-up, the MPAS participants also showed an increased rate of self-reported treatment compliance (70% vs 56%; P<.001) and a higher recommendation rate for future use (95% vs 64%; P<.001) as compared with the PEDC group. The cost analysis between the 2 groups was comparable. CONCLUSIONS: MPAS is an effective and acceptable method for improving the overall management, treatment compliance, and methodological quality of clinical research to ensure the validity and reliability of findings.

Comparison of the performance of the IDEXX SediVue Dx® with manual microscopy for the detection of cells and 2 crystal types in canine and feline urine.

BACKGROUND: Microscopic evaluation of urine is inconsistently performed in veterinary clinics. The IDEXX SediVue Dx® Urine Sediment Analyzer (SediVue) recently was introduced for automated analysis of canine and feline urine and may facilitate performance of urinalyses in practice. OBJECTIVE: Compare the performance of the SediVue with manual microscopy for detecting clinically relevant numbers of cells and 2 crystal types. SAMPLES: Five-hundred thirty urine samples (82% canine, 18% feline). METHODS: For SediVue analysis (software versions [SW] 1.0.0.0 and 1.0.1.3), uncentrifuged urine was pipetted into a cartridge. Images were captured and processed using a convolutional neural network algorithm. For manual microscopy, urine was centrifuged to obtain sediment. To determine sensitivity and specificity of the SediVue compared with manual microscopy, thresholds were set at ≥5/high power field (hpf) for red blood cells (RBC) and white blood cells (WBC) and ≥1/hpf for squamous epithelial cells (sqEPI), non-squamous epithelial cells (nsEPI), struvite crystals (STR), and calcium oxalate dihydrate crystals (CaOx Di). RESULTS: The sensitivity of the SediVue (SW1.0.1.3) was 85%-90% for the detection of RBC, WBC, and STR; 75% for CaOx Di; 71% for nsEPI; and 33% for sqEPI. Specificity was 99% for sqEPI and CaOx Di; 87%-90% for RBC, WBC, and nsEPI; and 84% for STR. Compared to SW1.0.0.0, SW1.0.1.3 had increased sensitivity but decreased specificity. Performance was similar for canine versus feline and fresh versus stored urine samples. CONCLUSIONS AND CLINICAL IMPORTANCE: The SediVue exhibits good agreement with manual microscopy for the detection of most formed elements evaluated, but improvement is needed for epithelial cells.

Urine sediment examination: Potential impact of red and white blood cell counts using different sediment methods.

BACKGROUND: Centrifugation is the primary method used to perform urine sediment analyses, but evaluation of other methods is required to validate centrifugation. OBJECTIVES: Non-urine materials were used to examine the repeatability (precision) and effectiveness (recovery) of four sediment methodologies on red blood cell (RBC) and white blood cell (WBC) counts. METHODS: Four urine sediment methods were compared using commercially available quality control material (QCM) and fresh canine RBCs in a diluent. Treatments included (a) 5 mL centrifugation at 390g for 5 minutes; (b) 1.5 mL centrifugation at 3900g for 45 seconds; (c) 60 µL of neat (unspun urine) in a microtiter well; and (d) 30 µL of neat on a slide with a coverslip. A within-run precision using QCM was followed by a one-run comparison test performed with a suspension of canine erythrocytes. RBC morphology was also examined. RESULTS: All results are listed in order of Methods A-D. Percent coefficients of variation (%CVs) for WBCs were 23.2%, 33.7%, 15.0%, and 27.2%. Red blood cells %CVs were 34.3%, 29.2%, 16.2%, and 24.4%. Average WBC counts in ten fields of view (FOV) ± 1 SD were 26.4 ± 6.1, 14.2 ± 4.8, 32.8 ± 4.9, and 1.6 ± 0.4. Average RBC counts in 10 fields of view (FOV) ± 1 SD were 45.3 ± 15.5, 23.9 ± 7.0, 38.4 ± 6.2, and 2.6 ± 0.6. The one-run comparison test reports average RBC counts per FOV at 55.2, 23.4, 92.8, and 13.8. The percentages of abnormal RBCs were 92.2%, 74.8%, 7.0%, and 55.1%. CONCLUSIONS: Method C had the best reproducibility, a lower frequency of cell morphology abnormalities, and similar cellular counts to those of Methods A and B.

VetCompass Australia: A National Big Data Collection System for Veterinary Science.

VetCompass Australia is veterinary medical records-based research coordinated with the global VetCompass endeavor to maximize its quality and effectiveness for Australian companion animals (cats, dogs, and horses). Bringing together all seven Australian veterinary schools, it is the first nationwide surveillance system collating clinical records on companion-animal diseases and treatments. VetCompass data service collects and aggregates real-time, clinical records for researchers to interrogate, delivering sustainable and cost-effective access to data from hundreds of veterinary practitioners nationwide. Analysis of these clinical records will reveal geographical and temporal trends in the prevalence of inherited and acquired diseases, identify frequently prescribed treatments, revolutionize clinical auditing, help the veterinary profession to rank research priorities, and assure evidence-based companion-animal curricula in veterinary schools. VetCompass Australia will progress in three phases: (1) roll-out of the VetCompass platform to harvest Australian veterinary clinical record data; (2) development and enrichment of the coding (data-presentation) platform; and (3) creation of a world-first, real-time surveillance interface with natural language processing (NLP) technology. The first of these three phases is described in the current article. Advances in the collection and sharing of records from numerous practices will enable veterinary professionals to deliver a vastly improved level of care for companion animals that will improve their quality of life.

Novel succinate dehydrogenase subunit B (SDHB) mutations in familial phaeochromocytomas and paragangliomas, but an absence of somatic SDHB mutations in sporadic phaeochromocytomas.

Phaeochromocytomas arising in adrenal or extra-adrenal sites and paragangliomas of the head and neck, in particular of the carotid bodies, occur sporadically and also in a familial setting. In addition to mutations in RET and VHL in familial disease, germline mutations in SDHD and SDHB genes that encode subunits of mitochondrial complex II have also been associated with the development of familial phaeochromocytomas. To further investigate the role of SDHD and SDHB in the development of these tumours we determined the occurrence of germline SDHD and SDHB mutations in four patients with a family history of phaeochromocytoma with associated head and neck paraganglioma, one patient with a family history of phaeochromocytoma only and two patients with apparently sporadic extra-adrenal phaeochromocytoma, one of whom had early onset disease. Secondly, we investigated whether somatic SDHB mutations correlated with loss of heterozygosity at 1p36 in a subgroup of 11 sporadic and three MEN 2-associated RET-mutation-positive phaeochromocytomas. Novel SDHB mutations were identified in the probands from four families and two apparently sporadic cases (six of seven probands studied), including two missense mutations, a single nonsense and frameshift mutation, as well as two splice site mutations, one of which was shown to have partial penetrance resulting in 'leaky' splicing. Further, five intronic polymorphisms in SDHB were found. No SDHD mutations were identified. In addition, no somatic SDHB mutations were found in the remaining allele of the 11 sporadic adrenal phaeochromocytomas with allelic loss at 1p36 or the three MEN 2-associated RET-mutation-positive phaeochromocytomas. Therefore, we conclude that SDHB has a major role in the pathogenesis of familial phaeochromocytomas, but the possible role of SDHB in sporadic tumours showing allelic loss at 1p36 has yet to be ascertained.

Patient-based feedback control for erythroid variables obtained using in-house automated hematology analyzers in veterinary medicine.

BACKGROUND: Automated in-house diagnostic analyzers, most commonly used for hematologic and biochemical analysis, are typically calibrated, and then control materials are used to confirm the quality of results. Although this approach provides indirect knowledge that the system is performing correctly, it does not provide direct knowledge of system performance between control runs. OBJECTIVES: The objectives of this study were to apply analysis of weighted moving averages to assess performance of hematology analyzers using animal patient samples from dogs, cats, and horses as they were analyzed and apply correction factors to mitigate instrument-driven biases when they developed. METHODS: A set of algorithms was developed and applied to sequential batches of 20 samples. Repeated samples within a batch and large populations of samples with similar abnormalities were excluded. Data for 6 hematologic variables were grouped into batches of weighted moving averages; data were analyzed with control chart rules, a gradient descent algorithm, and fuzzy logic to define and apply adjustments. RESULTS: A total of 102 hematology analyzers that had developed biases in RBC count, HCT, hemoglobin (HGB) concentration, MCV, MCH, and MCHC were evaluated. Following analysis, all variables except HGB concentration required adjustment, with RBC counts requiring only slight change and MCV requiring the greatest change. Adjustments were validated by comparing PCVs with the original and adjusted HCT values. CONCLUSIONS: The proposed system provides feedback control to minimize system bias for RBC count, HCT, HGB concentration, MCV, MCH, and MCHC. Fundamental assumptions must be met for the approach to assure proper functionality.