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Record W3016125274

PCR Based Diagnosis and Clinical Management of Ehrlichiosis in a Dog

2017· article· en· W3016125274 on OpenAlexaboutno aff
S. G. Sangeetha, Y. Ajith, Shilpi Dixit, K. Reena

Bibliographic record

VenueINTAS POLIVET · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsnot available
Fundersnot available
KeywordsLethargyMedicineEhrlichia canisInternal medicineGastroenterologyHypoalbuminemiaNeutropeniaAnorexiaImmunologyVomitingEhrlichiosisCanisTickVirologyBiologyChemotherapySerology
DOInot available

Abstract

fetched live from OpenAlex

The report depicts crucial diagnosis and successful clinical management of Ehrlichia canis infection in a dog. A fourteen months old Labrador retriever dog was presented with history of recurrent pyrexia, anorexia, vomiting and lethargy. Clinical examination revealed anaemia, pyrexia, tachycardia, tachypnea, hepatomegaly, lymphadenopathy and dehydration. Significant monocytopenia, microcytic hypochromic anaemia, immune mediated thrombocytopenia, elevated ALP and ALT activities, hyperglobulinemia, and hypoalbuminemia were evident in hemato-biochemical evaluation. Eventhough, blood smear examination was negative for any hemoparasites, PCR evaluation of the blood sample revealed E. canis infection. The animal was treated successfully using Doxycycline (5mg/kg BID per orally for 21 days) and supportive therapy using antacid, antihistamine, anti inflammatory steroid, antioxidant, hepato-protectant, hematinic and B-complex vitamins. The case points towards the need for high sensitivity molecular techniques like PCR in effective screening of canine ehrlichiosis and other tick-borne hemoparasitic diseases.

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)0.000
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 score0.009
Threshold uncertainty score0.430

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 head0.032
GPT teacher head0.341
Teacher spread0.308 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2017
Admission routes1
Has abstractyes

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