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Record W2050835886 · doi:10.1089/gyn.2009.0049

Oxidized Cellulose for Epithelialization of Neovagina in Vaginal Agenesis

2010· article· en· W2050835886 on OpenAlexaboutno aff
Vatsla Dadhwal, Bhaswati Ghosh, Bindiya Gupta, Deepika Deka, Suneeta Mittal

Bibliographic record

VenueJournal of Gynecologic Surgery · 2010
Typearticle
Languageen
FieldMedicine
TopicGynecological conditions and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVaginaSurgeryAgenesisProspective cohort studyOxidized cellulosePregnancyCellulose

Abstract

fetched live from OpenAlex

Objective: The study objective was to evaluate use of oxidized regenerated cellulose (Surgicel®) for epithelialization of neovagina in vaginal agenesis. Design: A prospective, longitudinal study (Canadian Task Force classification II-2) was conducted at a tertiary care center. Method: Ten (10) women (ages: 17–25 years) with vaginal agenesis, undergoing surgical construction of vagina over a period of 2 years, were included in the study. The surgical technique involved creation of a neovagina by modified Sheares technique, followed by use of a foam mold covered with a condom and further wrapped in oxidized cellulose to aid epithelialization. The main outcome measures evaluated were effectiveness and complications (if any) with the use of oxidized cellulose for epithelialization of neovagina. Results: There were no intraoperative complications. Adequate vaginal length (7–10 cm) was achieved in all cases on foam mold removal. On follow-up at 6 months, all vaginas were well epithelialized. One (1) patient had granulation tissue persisting for the initial 8 weeks, after which the vagina healed well. One (1) patient did not use a glass mold postsurgery and had partial stenosis; except for this patient, none had coital difficulty. Conclusions: Vaginal reconstruction using oxidized cellulose is a safe and effective procedure, with minimum complications and good success rates. Unlike amnion grafts, there is no risk of transmission of infections. (J GYNECOL SURG 26:189)

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)0.001
metaresearch head score (Gemma)0.003
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 score0.090
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.028
GPT teacher head0.295
Teacher spread0.267 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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