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Record W7014808143

Resection of Vaginal Neoplasms by Video-vaginoscopy in Bitche

2014· other· en· W7014808143 on OpenAlexaboutno aff

Bibliographic record

VenueRedalyc (Universidad Autónoma del Estado de México) · 2014
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsResectionLaparotomyVaginaVaginal bleedingCannulaCervixDorsumAnastomosis
DOInot available

Abstract

fetched live from OpenAlex

"Background : Vaginal neoplasms usually represent a challenge for veterinary surgeons. Surgical resection often requires episiotomy or even laparotomy and pubic osteotomy, increasing the risk for intra and postoperative complications, such as severe pain, bleeding, wound infection or dehiscence and vaginal stenosis. Endoscopic treatment of neoplastic lesions is routinely used in human patients. However, the information about its use in small animals is sparse. Thus, the aim of the current study was to report two cases of successful vaginoscopic treatment of vaginal neoplasms in bitches. Case : A female Labrador weighing 26 kg (patient 1) and a mongrel bitch weighting 10 kg (patient 2) were attended due to vaginal bleeding. Physical examination revealed a pendunculated hard nodular mass in the caudal third of the vaginal dorsal fl oor in patient 1. In patient 2, two nodular, fi brous, infi ltrated masses of different dimension were touched on the mucosa of the caudal third of the vagina. The vaginal cytology revealed erythrocytes, cellular debris and anestrus in both cases. Given the clinical suspicion of vaginal neoplasia, the endoscopic approach by vaginoscopy was chosen in order for diagnostic investigation and surgical treatment. Under general anesthesia, a rigid 10-mm telescope with 6-mm working channel was employed for initial examination. A 10-mmHg CO2 pneumovagina was estabilished using an automatic in- suffl ator. A pedunculated spherical neoplastic mass of approximately 2 cm of diameter was excised from patient 1 using a simultaneous bipolar coagulation and cut forceps, inserted through the working channel of the telescope. In patient 2, the two infi ltrated masses were resected using cup type biopsy forceps, followed by cauterization of the neoplastic underlin- ing area with bipolar forceps, also through the working channel. The sampled specimen were sent for histopathological examination, which revealed leiomyosarcoma and fi broepithelial hyperplasia in patients 1 and 2, respectively. Moreover, no other therapy was prescribed and the patients convalesced uneventfully. Discussion : The surgical procedures lasted 23 and 38 min in patients 1 and 2, respectively. Patients recovered unevent- fully in the early postoperative period, with no signs of pain. The operative-telescope proved to be versatile and effective for vaginoscopic resection of neoplasms, which was effi cient for both diagnostic and therapeutic purposes. The patients presented excellent recovery with minimally invasive surgical trauma, especially compared with conventional techniques. The majority of tumors found in the vagina of dogs are benign, mostly from smooth muscle or fi brous tissue origin (leio- myoma, fi broma and leiomyosarcoma). Surgical excision of the tumor combined with ovariohysterectomy is usually effec- tive to prevent recurrence. After 3 months, patient 1 was submitted to clinical and laboratory tests, including a second look"

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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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
Published2014
Admission routes1
Has abstractyes

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