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Record W2914227863 · doi:10.3747/pdi.2018.00203

Laparoscopic Mesh Repair of Bilateral Obturator Hernias Post-Peritoneal Dialysis

2019· article· en· W2914227863 on OpenAlexaff
Jonathan Ramkumar, Daphne Lu, Tracy Scott

Bibliographic record

VenuePeritoneal Dialysis International · 2019
Typearticle
Languageen
FieldMedicine
TopicHernia repair and management
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineObturator herniaSurgeryHerniaHematomaPeritoneal dialysisObturator nerveFemoral herniaAbdominal wallInguinal hernia

Abstract

fetched live from OpenAlex

Abdominal wall hernias are prevalent in patients undergoing peritoneal dialysis (PD). Obturator hernias, first described by Arnaud de Ronsil in 1724, are an uncommon type of hernia where intra-abdominal contents protrude through the obturator foramen. The following case highlights a rare presentation of bilateral obturator hernias with right femoral and inguinal hernia in an 82-year-old woman post-PD. This patient presented with 5 months of bilateral thigh pain and swelling and was found to only have a right-sided obturator hernia on computer tomography (CT) scan. Intraoperatively, bilateral obturator hernias were found along with right inguinal and femoral hernias, which were all repaired laparoscopically with polypropylene mesh. Postoperatively, the patient developed a self-limiting port site hematoma and resumed PD 1 month post-surgery. Due to the high morbidity and mortality from obturator hernias, prompt diagnosis and treatment are imperative. Compared with open hernia repair, laparoscopic hernia repairs are associated with quicker return to usual activities and less persisting pain and numbness. This case portrays that laparoscopic approach to bilateral obturator hernias can be considered in patients post-PD.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0060.001

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 head0.008
GPT teacher head0.268
Teacher spread0.260 · 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.

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

Citations11
Published2019
Admission routes1
Has abstractyes

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