DESCRIBING LYMPHEDEMA IN FEMALES WITH TURNER SYNDROME.
Bibliographic record
Abstract
Turner syndrome (TS) is a chromosomal condition affecting an estimated 1 in 2,500 girls where the second X chromosome is missing, or partially formed. This abnormality affects multiple body systems and can lead to short stature, cardiac, neural, and renal abnormalities. Due to the chronic, non-life threatening nature of lymphedema in comparison to other symptoms of TS, it is often ignored by girls and women with TS and their physicians. Consequently, little is known about how lymphedema affects girls and women with TS across the lifespan. Therefore, the objective of the study was to deliver an online survey for females with TS and caregivers in the US, UK, and Canada to provide a worldwide perspective on their current experience with lymphedema within the spectrum of TS. There were 219 participants who completed the survey, and we were able to identify incidence and characteristics of lymphedema across the lifespan. In addition, we found that females with 45,X karyotyping were more likely to report lymphedema symptoms. Lymphedema is not the most significant concern of females with TS, but education, physician evaluation, and assistance with referrals for treatment and management would improve the ease of managing lymphedema in girls and women with TS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".