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Record W4289886984 · doi:10.30954/2347-9655.01.2022.10

Therapeutic Intervention of Chronic Kidney Disease Associated with Multiple Complications in a Labrador

2022· article· en· W4289886984 on OpenAlexaboutno aff
Rofique Ahmed

Bibliographic record

VenueInternational Journal of Bioresource Science · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineKidney diseaseIntervention (counseling)DiseaseInternal medicineIntensive care medicinePsychiatry

Abstract

fetched live from OpenAlex

A 9-year-old male Labrador retriever was presented with a history of weakness, lethargy, inappetence, yellowish urine, and blackish stool.The body temperature was found to be within the normal range (101.1°F) with pale mucous membrane and swelling of the forelimb showing gangrene formation.A blood biochemical test was done in which SGPT, SGOT, BUN, creatine, albumin, glucose, and total protein were significantly higher than the normal range.Abdominal ultrasonography revealed degenerative changes in both the kidneys with significant loss of cortico-medullary junction differentiation, cystitis, hepatomegaly, hepatitis, and ascites were noticed.The overall findings indicated chronic kidney disease with multiple complications.Treatment was initiated with Mannitol (20%), Lasix, Glutamax Forte, Erythropoietin Injection, Renodyl capsule, and other supportive drugs.Blood biochemical tests were done every week for monitoring which showed considerable improvement in the condition of the animal with the ongoing treatment. HIGHLIGHTSm Chronic Kidney Disease (CKD) is one of the most common kidney disorders of adult dogs, especially in male Labradors.m Proper diagnosis and therapeutic intervention are a must for prolonging the life expectancy of the dogs.m Prophylactic measures including nutritional management and care are needed to decrease the incidences of CKD in dogs.m In the present investigation, treatment was given as per standard protocol with few changes based on multiple complications.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.290
Teacher spread0.264 · 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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