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Record W2542225398

Epidemiologia e risco anestésico de cães portadores de otohematoma

2016· article· es· W2542225398 on OpenAlexaboutno aff
Nhirneyla Marques Rodrigues, Ana Maria Quessada, Fabiane Leite da Silva, Esther Machado de Carvalho e Silva, João Moreira da Costa Neto, Wagner Costa Lima

Bibliographic record

VenueACTA SCIENTIAE VETERINARIAE · 2016
Typearticle
Languagees
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHematomaLeukocytosisSurgeryEhrlichiosisVeterinary medicine
DOInot available

Abstract

fetched live from OpenAlex

Background: Otohematoma or aural hematoma in dogs is blood pooling within the ear cartilage plate, and stems from several causes (ear infections, ectoparasites and others). The formation of hematoma is by vascular injury, causing bleeding, generated by self-injury. This disease occurs especially in dogs of pendulous ears, and the concave surface of the ear is considered as the most frequent. The therapy to correct the lesion can be a clinical procedure; however, surgical drainage is the treatment of choice. This work aims to record the epidemiological aspects related to aural hematoma in dogs, as well as classify such patients as to the physical condition and anesthetic risk. Materials, Methods & Results: Twenty five dogs with aural hematoma submitted to surgical procedure were followed. During the data collection period (seven months), surgery to correct aural hematoma represented 19% of surgeries performed in dogs (total of surgeries: 474). The percentage of canine breeds affected was: mixed breed (64%; 16/25), german shepherd (24%; 6/25), labrador (4%; 1/25), waimaraner (4%; 1/25) and daschund (4%; 1/25). Most occurrences were observed in females aged 3-12 years. Most of the animals showed only one pina affected (96%; 24/25), and 52% (13/25) had hematoma in the right and 44% (11/25) in the left ear. Some of the patients had no hematologic abnormalities (48%; 12/25), but some animals showed normocytic normochromic anemia (36%, 9/25), leukocytosis (8%; 2/25) and thrombocytopenia (8%; 2/25). Among animals, there were only dogs classified as ASA II and ASA III with similar rates (56% and 44% respectively). No deaths were observed among cases analyzed. Discussion: The high prevalence of the disease in mongrel dogs can be explained by the great number of mongrel animals in the service analyzed. Aural hematoma was more frequent in older dogs probably because animals in this age group are more affected by otitis externa, which can predispose them to aural hematoma. Otohematoma was common in animals with pendulous ears, probably because these dogs are more prone to ear diseases than animals with erect ears. Females are more affected, and these data are different to those of other studies, and may be related to changes of the clientele among males and females. Only 4% (1/25) showed bilateral aural hematoma which, actually, is less common. Haematological abnormalities observed may be related to the appearance of aural hematoma, but were unspecific and common to several diseases. Animals classified as ASA II entered in this category for being carriers of mild haematological disorders, especially anemia (36%; 9/25). Dogs classified as ASA III showed signs of moderate systemic disease, and the main suspected disease was ehrlichiosis, which may be associated with aural hematoma. Animals underwent surgical procedure even though being classified as ASA II and III. Such procedure caused no detectable adverse effects and no deaths were recorded. It is expected that mortality is higher in patients classified in a higher grade. The absence of deaths can be related to ASA classification, which was only up to Grade III (moderate systemic disease). Moreover, surgery to drain aural hematoma is considered free of contamination, minimally invasive and without the involvement of important anatomical structures that could systemically compromise patients.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.054
GPT teacher head0.384
Teacher spread0.330 · 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; both teacher heads agree on what is shown here.

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
Published2016
Admission routes1
Has abstractyes

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