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Record W4395019838 · doi:10.9734/ajravs/2022/v5i2204

Ehrlichia canis Infection Induced Chronic Kidney Disease in a Labrador Retriever and Its Management: A Case Report

2022· article· en· W4395019838 on OpenAlexaboutno aff
M Chandrasekar, S. Savitha, Vaidehi Pasumarthi

Bibliographic record

VenueAsian Journal of Research in Animal and Veterinary Sciences · 2022
Typearticle
Languageen
FieldMedicine
TopicXenotransplantation and immune response
Canadian institutionsnot available
Fundersnot available
KeywordsLabrador RetrieverEhrlichia canisCanisMedicineEhrlichiaKidney diseaseVirologyImmunologyBiologyInternal medicinePathologyEcologySerology

Abstract

fetched live from OpenAlex

Introduction: Chronic kidney disease is irreversible, progressive and most common form of kidney disease in dogs.Canine ehrlichiosis is caused by gram negative intracellular bacteria Ehrlichia canis.Case Presentation: A 7-year old Labrador retriever male dog weighing around 35 kg was presented to the Madras Veterinary College Teaching Hospital with a history of inappetence, vomiting, polyuria and polydipsia from fifteen days.The dog was fully vaccinated and dewormed.On general clinical examination, all vital parameters were within normal range except elevated temperature (103.8°F).The hematological findings revealed mild thrombocytopenia and hypochromasia.The serum biochemistry revealed increased creatinine level (3.68 mg/dl).The blood Case Study pressure was measured using Doppler device which revealed secondary hypertension.A blood smear examination was found to be negative.Case Discussion: The animal was treated for chronic kidney failure.Even then animal was going down and not taking feed.The blood sample was sent for Molecular PCR which confirmed presence of Ehrlichia canis.Then animal was treated for Canine Monocytic Ehrlichiosis to control Ehrlichia canis induced renal failure.Then there was little progress in condition of the animal.The animal was maintained with a renal diet.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.104
GPT teacher head0.411
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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
Published2022
Admission routes1
Has abstractyes

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