Gender Differences in Bleeding Problems and Implications for the Assessment of a Bleeding Disorder.
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».