Gender Differences in Bleeding Problems and Implications for the Assessment of a Bleeding Disorder.
Bibliographic record
Abstract
Abstract Introduction: The value of gender-specific questions in assessing patients referred for evaluation of bleeding problems is not well established. Moreover, the impact of having a bleeding problem on sexual health is unknown. Methods: To learn more about gender differences in bleeding problems, questions about bleeding affecting sexuality and gender-specific issues were included in a detailed bleeding history questionnaire (CHAT: clinical history assessment tool). CHAT was administered to 256 female (F) and 66 male (M) patients referred for bleeding problems, and 67 F and 32 M healthy controls. A final diagnosis for each patient was established by independent reviews of medical records by two physicians, with discrepancies resolved by consensus. Data were expressed as prevalences among patients with bleeding disorders versus gender-matched healthy controls, with significantly increased bleeding risks expressed as odds ratios (OR). Results: 62% of CHAT subjects had bleeding disorders (54 M, 205 F), most commonly affecting platelets or von Willebrand factor. Most subjects had experienced sexual intercourse. Men with bleeding disorders did not have significantly increased intercourse-related bleeding (5% vs. 13%, p=0.38) or bleeding affecting their sex life in other ways (8% vs. 4%, p=1.0) and they did not have increased gender-specific bleeding (p values>0.38). However, women with bleeding disorders had significantly increased intercourse-related bleeding (38% vs. 3%, p<0.0001; OR=20) and bleeding affecting their sex life in other ways (24% vs. 7%, p=0.006; OR=4.2). Affected women reported avoiding sexual activity (due to increased bleeding and bruising, pain and exhaustion), experiencing frustration and reduced self esteem. Women with bleeding disorders also had increased risks for: prolonged menses (50% vs. 12%, p<0.0001; OR=7.8), menses interfering with lifestyle (56% vs. 22%, p<0.0001; OR=5.2), menses requiring medical (43% vs 21%, p=0.0008; OR=3.0) or surgical therapy (26% vs 6%, p=0.0005; OR=5.5), uterine fibroids (18% vs.7%, p=0.008; OR=3.6), excessive bleeding during or after childbirth (50% vs. 13%, p<0.0001; OR=12), excessive bleeding with miscarriages (55% vs. 17%, p=0.0002; OR=17), and feeling concerned about becoming pregnant or delivering a baby because of bleeding (23% vs. 2%, p=0.0001; OR=19). They did not have increased risks for pregnancy losses or bleeding during pregnancy (p values >0.1). Although women with bleeding disorders had similar numbers of offspring as controls (means: 2.0 vs. 1.7), 38% had been told by a doctor not to become pregnant due to their bleeding problem. Conclusions: Gender has an important impact on the manifestations of common bleeding disorders. Detailed questions about bleeding affecting sexual life, menses, and reproduction are useful in assessing women with bleeding disorders who are at greater risk for experiencing excessive bleeding with intercourse, menses and childbirth, that can negatively impact on lifestyle and sexual/reproductive health. Recognition of these issues has important implications for the diagnosis and management of individuals with bleeding disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".