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High prevalence of ovarian cysts in premenopausal women receiving sirolimus and tacrolimus after clinical islet transplantation

2009· article· en· W1987988742 on OpenAlexaffabout
Eman Alfadhli, Angela Koh, Waleed Albaker, Ravi Bhargava, Thomas Ackerman, Charlotte McDonald, Edmond A. Ryan, A. M. James Shapiro, Peter Senior

Bibliographic record

VenueTransplant International · 2009
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsMedicineTransplantationIsletUrologySirolimusTacrolimusCystGynecologySurgeryInternal medicineDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

We encountered an unexpectedly high rate of ovarian cysts in premenopausal women receiving sirolimus and tacrolimus following islet transplantation. The goal of this retrospective chart review was to determine the frequency of ovarian cysts found on pelvic ultrasound examinations of female islet transplant recipients and to look for potential causal factors. Fifty-seven women with a median age of 42.5 years underwent islet transplantation at the University of Alberta. Ovarian cysts were found in 31 out of 44 (70.5%) premenopausal and two out of 13 (15.4%) postmenopausal women (P = 0.001). No women using combined oral contraception developed ovarian cysts. Eight women required surgery; in four women undergoing cystectomy or unilateral oophorectomy, ovarian cysts recurred. Sirolimus withdrawal was associated with a reduction in cyst size and resolution of cysts in 80% of subjects. The risk of ovarian cysts should be discussed with female islet transplant candidates and pelvic ultrasounds performed routinely post-transplant.

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)0.002
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.013
GPT teacher head0.282
Teacher spread0.269 · 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

Citations36
Published2009
Admission routes2
Has abstractyes

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