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Record W4386634847 · doi:10.1002/uog.16491

OP34.05: Interpreting the transvaginal ultrasound uterine “sliding sign” for the prediction of <scp>POD</scp> obliteration: a learning curve study

2016· article· en· W4386634847 on OpenAlexaff
S. Reid, Arianne Albert, Mohamed A. Bedaiwy, Catherine Allaire

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2016
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsB.C. Women's Hospital & Health CentreWomen's Health Research InstituteUniversity of British Columbia
Fundersnot available
KeywordsMedicineSign (mathematics)UltrasoundPouchRadiologySurgery

Abstract

fetched live from OpenAlex

How long does it take to become proficient in predicting pouch of Douglas (POD) obliteration using the transvaginal ultrasound (TVU) “sliding sign”? A learning curve study performed at a tertiary referral centre for women with chronic pelvic pain (CPP). The study included 1 trainee examiner who was a gynecology specialist with previous experience in TVU, but no prior experience with interpretation of the TVU “sliding sign” for POD obliteration. The trainee examiner underwent 20 hands-on, supervised training sessions with an expert sonologist for performing and interpreting the TVU “sliding sign” for POD obliteration. 25 women with CPP were then assessed for POD obliteration using the TVU uterine “sliding sign” at two anatomical locations: the posterior uterine fundus and the retro-cervix. The TVU examination was first performed independently by the trainee, who was blinded to the patient's history. The TVU examination was then repeated immediately by the expert sonologist. The reference standard was the expert's TVU “sliding sign” findings. The learning curve cumulative summation (LC-CUSUM) test was conducted to assess if trainee performance reached acceptable levels. Minimum competency was deemed as a failure rate of ≤ 10% to correctly predict outcome (i.e. success rate ≥ 90% to predict the outcome as predicted by the expert sonologist). TVU "sliding sign" results were available for 25 women. 6/25 (24%) women had a negative TVU “sliding sign” (i.e. POD obliteration), as per the expert sonologist's findings. The trainee reached the predefined level of proficiency for the prediction of POD obliteration after examining 15 women using the TVU uterine “sliding sign”. This study demonstrates that gynecologists with experience in TVU may become proficient with the prediction of POD obliteration using the TVU “sliding sign” after 15 scans, following hands-on training with 20 scans.

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)0.009
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.275
Teacher spread0.257 · 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 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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