Role of Gender in the Clinical Presentation of a First Deep Venous Thrombosis (DVT) in Outpatients.
Notice bibliographique
Résumé
Abstract BACKGROUND: As clinical assessment of pretest probability (PTP) is now considered the first step in the diagnostic evaluation of DVT it is important to know if the clinical features of DVT are the same in men and women. OBJECTIVES: We sought to answer the following questions: 1) Is the prevalence of DVT the same in men and women who are referred for diagnostic testing? 2) Are the clinical features of DVT the same in men and women? 3) Does the Wells’ clinical prediction model for first DVT perform similarly in men and women? METHODS: We performed a retrospective analysis of individual patient data from three studies that evaluated diagnostic testing in outpatients with a suspected first episode of DVT. Associations were assessed using univariable and multivariable analyses. RESULTS: A total of 1838 patients were eligible for final analyses, of whom 1132 (62%) were women and 706 (38%) were men. DVT was objectively diagnosed in 208 patients (11%). QUESTION 1: The prevalence of DVT was higher in men (14%) than in women (9%) (p=0.001). In a multivariable analysis that included eleven other clinical variables male gender was independently associated with a higher prevalence of DVT (OR 1.5, 95% CI 1.1–2.1). QUESTION 2: Of the confirmed episodes of DVT, “swelling of the entire leg” was observed more often in women (41%) than in men (16%) (p<0.001). This difference was partly explained by more extensive thrombosis in women than in men; the common femoral vein was involved on ultrasound in 48% of women and 22% of men (p< 0.001). The frequency of other clinical features was similar in men and women. QUESTION 3: The prevalence of DVT was higher in men than in women who were categorized by the Wells model as having a low PTP (6.9% vs 3.6%; p=0.025) or a moderate PTP (16.9% vs. 8.7%; p<0.001), but similar in the high PTP category (40% vs 44%; p=0.6). Five clinical features were more strongly associated with presence of DVT in women than in men: “swelling of the entire leg” (OR 7.7 vs. 1.6; p<0.001), “difference in calf circumference >3cm” (OR 8.2 vs. 2.9; p<0.001), “pitting edema” (OR 4.4 vs. 1.8; p=0.004), “age > 60 yrs” (OR 1.8 vs. 0.9; p=0.02) and “bedridden for greater than 3 days” (OR 3.7 vs. 1.4; p=0.05). CONCLUSIONS: Among outpatients referred with a suspected first episode of DVT, the prevalence of DVT is higher in men than in women but DVT is more extensive in women. Entire leg swelling is a more common and important sign of DVT in women than in men and the Wells prediction rule behaves differently in men than in women.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».