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Record W2076294496 · doi:10.1016/j.ijgo.2009.11.019

Improved quality of life is partly explained by fewer symptoms after treatment of fibroids with mifepristone

2010· article· en· W2076294496 on OpenAlexaboutno aff
Changyong Feng, Sean Meldrum, Kevin Fiscella

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2010
Typearticle
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsMedicineMifepristoneUterine fibroidsQuality of life (healthcare)PlaceboGynecologyObstetricsPregnancy

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine mediators of mifepristone treatment on improvements in health-related quality of life (HRQOL) among women with symptomatic fibroids. METHODS: The study sample included women with symptomatic uterine fibroids who were treated with 5mg or 2.5mg of mifepristone or placebo. Assessments of uterine size (ultrasound), pain (McGill pain questionnaire), bleeding (diary), anemia (gm/dL), and HRQOL measured using the uterine fibroid symptom quality of life scale were done at baseline, 3 months, and 6 months. The improvements in HRQOL that could be explained by changes in these clinical factors were assessed. RESULTS: The final sample included 62 women. Treatment with mifepristone was associated with significant improvement in HRQOL, which was explained in part by reduction in pain (28%, P<0.001) and bleeding (18%, P<0.001). Reduction in uterine volume was of marginal significance (P=0.05) and was associated with a decrease in HRQOL (7%). Much of the impact of treatment on HRQOL (61%) remained unexplained in this model. CONCLUSIONS: Improvements in HRQOL after treatment with mifepristone are partly explained by improvements in pain and bleeding, but not uterine size. However, most of the improvement in HRQOL is not explained by improvements in these clinical parameters.

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)0.001
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 score0.105
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.013
GPT teacher head0.298
Teacher spread0.285 · 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

Citations40
Published2010
Admission routes1
Has abstractyes

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