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Record W1986156841 · doi:10.1111/vcp.12004

Comparison of white and red blood cell estimates in urine sediment with hemocytometer and automated counts in dogs and cats

2012· article· en· W1986156841 on OpenAlex
Elizabeth O’Neil, Shelley Burton, Barbara S. Horney, Allan MacKenzie

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueVeterinary Clinical Pathology · 2012
Typearticle
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsUniversity of Prince Edward Island
FundersAtlantic Veterinary College
KeywordsHemocytometerUrineWhite blood cellUrinalysisHematology analyzerLeukocyte CountsHigh-power fieldMedicinePathologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Therapeutic decisions regarding urinalysis are commonly based on the presence of white and red blood cells. Traditionally, numbers per high-power field are estimated using wet-mount microscopic examination. This technique is not standardized and counts are likely prone to inaccuracy. In addition, differentiation of leukocyte types is not possible. OBJECTIVES: The aims of this study were to (1) compare WBC and RBC estimates using wet-mount examination with counts obtained using a hemocytometer, (2) assess if a hematology automated analyzer (Sysmex ST-2000iV/XT) provides reliable WBC and RBC counts in urine comparable to hemocytometer counts, and (3) evaluate air-dried Wright-Giemsa-stained urine drop sediment preparations for the determination of differential leukocyte counts. METHODS: WBC and RBC counts were obtained by performing wet-mount estimates, manual hemocytometer counts, and Sysmex automated counts on 219 canine and feline urine samples. Results were correlated using Spearman rank correlation. Air-dried Wright-Giemsa stained sediment drop preparations (n = 215) were examined for differential counts of leukocytes. RESULTS: A low but significant association was found between WBC estimates on wet-mount examination and hemocytometer counts (rho = 0.37, P < .01). There was a high and significant association when RBC counts were compared between wet-mount and hemocytometer evaluation (rho = 0.7, P < .01). There was very high and significant interassay correlation between Sysmex data from duplicate samples for what the analyzer classified as WBC (rho = 0.97, P < .01) and RBC (rho = 0.94, P < .01). Low correlations were found between the Sysmex RBC counts and both wet-mount estimates and hemocytometer RBC counts (rho = 0.43, P < .01 and rho = 0.39, P < .01, respectively). Cell preservation in the air-dried sediment preparations was so poor that differential counts could not be performed. CONCLUSION: WBC and RBC estimates on wet-mount examination agreed with hemocytometer counts and are therefore considered adequate. The Sysmex ST-2000iV/XT did not provide reliable cell counts under the conditions used.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.407
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it