Predicting Deep Venous Thrombosis in Pregnancy: Out in “LEFt” Field?
Notice bibliographique
Résumé
BACKGROUND: Clinicians' assessment of pretest probability, based on subjective criteria or prediction rules, is central to the diagnosis of deep venous thrombosis (DVT). Pretest probability assessment for DVT diagnosis has never been evaluated in pregnant women. OBJECTIVE: To evaluate the accuracy of clinicians' subjective assessment of pretest probability for DVT diagnosis and identify prediction variables that could be used for pretest probability assessment in pregnant women with suspected DVT. DESIGN: A cross-sectional study conducted over 7 years (March 2000 to April 2007). SETTING: 5 university-affiliated, tertiary care centers in Canada. PATIENTS: 194 unselected pregnant women with suspected first DVT. INTERVENTION: Diagnosis of DVT was established with abnormal compression ultrasonography at presentation or on serial imaging. Pretest probability by subjective assessment was recorded by thrombosis experts for each patient before knowledge of results. MEASUREMENTS: The sensitivity, specificity, negative predictive value, and likelihood ratios of subjective pretest probability assessment and their corresponding 95% CIs were calculated on the basis of the diagnosis of DVT. Patients were DVT positive if they had diagnostic compression ultrasonography at initial or serial testing or symptomatic venous thromboembolism on follow-up. Patients were DVT negative if they had negative compression ultrasonography at presentation and no venous thromboembolism on follow-up. A prediction rule for assessing DVT was derived, and an internal validation study was done to explore its performance. RESULTS: The prevalence of DVT was 8.8%. Clinicians' subjective assessment of pretest probability categorized patients into 2 groups: low pretest probability (two thirds of patients) with a low prevalence of DVT (1.5% [95% CI, 0.4% to 5.4%]) and a negative predictive value of 98.5% (CI, 94.6% to 99.6%), and nonlow pretest probability with a higher prevalence of DVT (24.6% [CI, 15.5% to 36.7%]). Three variables (symptoms in the left leg [L], calf circumference difference > or = 2 cm [E], and first trimester presentation [Ft]) were highly predictive of DVT in pregnant patients. LIMITATIONS: Few outcomes occurred. Altogether, 17 events were diagnosed during the study. The prediction rule derived should be validated on an independent sample before applying it to clinical practice. CONCLUSION: Subjective assessment of pretest probability seems to exclude DVT when the pretest probability is low. Moreover, 3 objective variables ("LEFt") may improve the accuracy of the diagnosis of DVT in pregnancy. Prospective validation studies are needed. PRIMARY FUNDING SOURCE: Heart and Stroke Foundation of Ontario.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 ».