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Record W4386087339 · doi:10.1016/j.cimid.2023.102041

Clinical findings and prognostic factors for mortality in hospitalized dogs with leishmaniosis: aretrospective study

2023· article· en· W4386087339 on OpenAlexaboutno aff
Carlota Carvalho Molina, Maria Joana Dias, Tiago Dias Domingues, Ryane E. Englar, Rodolfo Oliveira Leal

Bibliographic record

VenueComparative Immunology Microbiology and Infectious Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsHypoalbuminemiaLethargyAzotemiaMedicineLeukocytosisInterquartile rangeRetrospective cohort studyMedical recordInternal medicineStage (stratigraphy)EmaciationBiology

Abstract

fetched live from OpenAlex

This retrospective study evaluated factors responsible for mortality of dogs hospitalized for Canine Leishmaniosis. Medical records of 31 dogs with leishmaniosis from a Portuguese Veterinary Teaching Hospital were examined between August 2018 and January 2022. Females (n = 18) and pure breed dogs (n = 27) were overrepresented, with higher frequency of Labrador Retriever (n = 4). Median age was 7 years (interquartile range=7). Most had historical findings of lethargy (n = 26) and the commonest clinicopathological abnormality was hypoalbuminemia (n = 26). Eleven dogs were classified as LeishVet stage II, 10 stage III and 10 stage IV. Fourteen dogs (45.2%) died or were euthanized, with azotemia, leukocytosis, stage IV, absence of diagnosis before hospitalization and lack of leishmaniosis specific treatment during hospitalization contributing to mortality. Absence of hypoalbuminemia and stages II/III increased survival. Mean hospitalization length prior to discharge was 5.41days ( ± 1.84) and diarrhea prolonged hospital stay.

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)0.001
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 score0.013
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.052
GPT teacher head0.374
Teacher spread0.323 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

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