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Record W6989941723

The complete blood count and caninemast cell tumor. A retrospective survey in a veterinary teaching hospital in Tuscany, Italy

2017· article· en· W6989941723 on OpenAlexaboutno aff

Bibliographic record

VenueCINECA IRIS Institutial research information system (University of Pisa) · 2017
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
FundersFondazione Cassa di Risparmio di Puglia
KeywordsComplete blood countStage (stratigraphy)Bone marrowCytopeniaBiopsyBlood countPalpationLymph nodeRetrospective cohort studyOdds ratio
DOInot available

Abstract

fetched live from OpenAlex

Complete blood count (CBC) modifications in canine mast cell tumor (cMCT) are described in dogs showing
\nbone marrow involvement. However, few data are available for dogs affected by MCT in other stages than
\nstage IV MCTs [1-2].
\nThe aims of this study were: 1- to investigate the frequency of cMCT in a Veterinary Teaching Hospital
\n(VTH) of Tuscany, Italy; 2- to assess if breed, gender and sexual status were associated with the frequency
\nof cMCT; 3- to evaluate the association between each CBC parameters and clinical variables in cMCT.
\nDogs with cyto/histological diagnosis of cutaneous MCT were enrolled. All dogs were staged with
\nabdominal ultrasound and 3-view chest X-rays. Fine-needle biopsy of the regional lymph node (LN) was
\nperformed if LN was palpable or seen at ultrasonography. Fine-needle biopsy of liver and spleen was
\nperformed in high-risk MCT (relapsing MCT, inguinal/perineal MCT, large or ulcerated MCT, Patnaik GIII or
\nKiupel high-grade MCT, presence of nodal metastasis), and if ultrasonography alterations were detected or
\nif requested by clinicians. Bone marrow cytology was performed in IV-stage MCT and if severe peripheral
\nblood cytopenia was found. To investigate frequency of cMCT, dogs with MCT have been selected from our
\nVTH database. To assess breed, gender and sexual status specific frequencies in cMCT, Odds Ratio (OR) with
\nmatched dogs without MCT (n. 13,077) in our VTH database has been performed. Dogs were divided in
\nthese subgroups: neutered (30)/intact (68), male (47)/female (51), age based on the 25th-, 50th- and 75thpercentile,
\npresence of ulceration (15/89), occurrence of LN (28/88), occurence of visceral metastasis
\n(12/88), and clinical stage (5 stage 0, 26 stage I, 8 stage II, 37 stage III, 12 stage IV). Each single parameter of
\nCBC was used as an independent variable and analyzed statistically for each subgroup of dogs (t-student or
\nif appropriate Mann-Whitney and Kruskal-Wallis tests).
\nFrequency of cMCT was 0.77% (98/13,175). Among purebreds, Boxer (OR 7.2), Pitt Bull (OR 5.4), French
\nBulldog (OR 4.4) and Labrador Retriever (OR 2.6) were considered the most predominant. Neutered dogs
\nwere also predominant compared to intact dogs (OR 2.1). Up to 67% (66/98) patients had CBC results in the
\nreference ranges. The most common CBC abnormalities were anemia (25%) and leukocytosis/penia (17%).
\nAny hematological abnormalities were not significantly different when analyzed for sex, age, presence of
\nulceration, occurrence of lymph node or visceral metastasis, and clinical stage.
\nThese findings suggest that some breeds and the neutered status could be at increased frequency for
\ncMCT. As all dogs came from a small area of Italy, a comprehensive examination of inbreeding and gene
\ncode associated with cMCT development could suggest a genetic predisposition. As reported in the
\nliterature, many dogs with MCT show CBC results in the reference ranges. Any single hematological variable
\nwas not associated with specific clinical findings or disease stage, suggesting a minimal role of CBC in the
\noverview of cMCT.
\n[1] Endicott MM, Charney SC, McKnight JA, et al. Clinicopathological findings and results of bone marrow aspiration in
\ndogs with cutaneous mast cell tumours: 157 cases (1999-2002). Vet Comp Oncol. 2007;5(1):31-37. [2] Marconato L,
\nBettini G, Giacoboni C, et al. Clinicopathological features

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.

How this classification was reachedexpand

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.088
GPT teacher head0.340
Teacher spread0.252 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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