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Record W4399865297 · doi:10.1097/mou.0000000000001204

Management of vaginoplasty canal complications

2024· review· en· W4399865297 on OpenAlexaff
Borko Stojanović, Geneviève Horwood, Ivana Joksić, Sandeep Bafna, Miroslav L. Djordjević

Bibliographic record

VenueCurrent Opinion in Urology · 2024
Typereview
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineVaginoplastyGeneral surgerySurgeryVagina

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Increasing uptake of gender affirming surgery has allowed for a wider breadth of publication examining complications associated with vaginoplasty. This review aims to provide a comprehensive overview of complications associated with vaginoplasty procedures, focusing on intraoperative, early postoperative, and delayed postoperative complications across different surgical techniques. RECENT FINDINGS: Intraoperative complications such as bleeding, injury of the rectum, urethra and prostate, and intra-abdominal injury are discussed, with insights into their incidence rates and management strategies. Early postoperative complications, including wound dehiscence, infection, and voiding dysfunction, are highlighted alongside their respective treatment approaches. Moreover, delayed postoperative complications such as neovaginal stenosis, vaginal depth reduction, vaginal prolapse, rectovaginal fistula, and urinary tract fistulas are assessed, with a focus on their etiology, incidence rates, and management options. SUMMARY: Vaginoplasty complications range from minor wound issues to severe functional problems, necessitating a nuanced understanding of their management. Patient counseling, surgical approach, and postoperative care optimization emerge as crucial strategies in mitigating the impact of complications. Standardizing complication reporting and further research are emphasized to develop evidence-based strategies for complication prevention and management in vaginoplasty procedures.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.164
GPT teacher head0.459
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2024
Admission routes1
Has abstractyes

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