Deep Vein Thrombosis Diagnosis with D-Dimer Adjusted to Clinical Probability
Notice bibliographique
Résumé
Introduction Diagnostic testing for deep vein thrombosis (DVT) is a multi-step and time-consuming process. Testing starts with clinical pretest probability (C-PTP) assessment. A negative D-dimer in combination with low C-PTP is widely used to exclude DVT; otherwise ultrasound imaging is required. When proximal vein ultrasound is used, a repeat ultrasound after a week is usually required to exclude DVT in moderate or high C-PTP patients. Ultrasound imaging is costly and can introduce delays. The goal of this study was to evaluate the safety and efficiency of a diagnostic algorithm for DVT that was designed to minimize the need for ultrasound imaging by using C-PTP-based D-dimer thresholds to exclude DVT (the 4D algorithm), rather than a standard fixed D-dimer cut-off value. Methods Consenting patients were enrolled in a Canadian prospective multicentre management study. Outpatients with symptoms or signs of DVT were eligible to be included in this study. Physicians used the 9-item Wells score to categorize the patient's C-PTP as low (Wells score, -2 to 0), moderate (1 or 2), or high (≥3). Patients with low C-PTP and a D-dimer <1,000 ng/mL or with a moderate C-PTP and a D-dimer <500 ng/mL underwent no further diagnostic testing for DVT and did not receive anticoagulant therapy. All other patients underwent proximal vein ultrasound. Patients with a single negative ultrasound but very high D-dimer (low or moderate C-PTP with D-dimer ≥3000 ng/mL, high C-PTP with D-dimer ≥1500 ng/mL) had a second proximal venous ultrasound one week later. The primary outcome was symptomatic, objectively verified, venous thromboembolism (VTE), which included proximal DVT or pulmonary embolism. All patients were followed for 90 days. A sample size of 1500 was required to establish 4D algorithm safety (90-day post-test probability of VTE <2%). Results From April 2014 through March 2020, a total of 1512 patients were enrolled and analyzed. The mean age was 60 years and 58% were female. Overall, 173 (11%) had DVT on initial or serial diagnostic testing (168 had DVT on ultrasound imaging on the day of presentation and 5 had DVT on repeat ultrasound imaging at one week). Of all 1298 patients (86% of total) who did not have DVT (at either initial presentation or at scheduled repeat ultrasound imaging) and who did not receive anticoagulant therapy, 7 had VTE during follow-up (0.5%, 95% confidence interval (CI): 0.3 to 1.1%). In the 579 patients who had low (378 patients) or moderate (201 patients) C-PTP and negative D-dimer results (i.e. <1000 or <500 ng/mL respectively) and who did not receive anticoagulant therapy, 2 had VTE during follow-up (0.4%, 95% CI: 0.1 to 1.3%). In the 572 patients with a single negative ultrasound who were low or moderate C-PTP with D-dimer <3000 ng/mL (423 patients), or high C-PTP with D-dimer <1500 ng/mL (149 patients) and who did not receive anticoagulant therapy, 3 had VTE during follow-up (0.5%, 95% CI: 0.2 to 1.5%). The difference in the mean number of ultrasound examinations with the 4D algorithm (0.72) compared with the conventional algorithm (1.36) was -0.64 (95% CI, -0.68 to -0.61), corresponding to a 47% relative reduction (1083 ultrasound scans performed with the 4D algorithm compared with 2053 ultrasound scans required for the conventional algorithm). Conclusions The 4D diagnostic algorithm ruled out DVT safely while substantially reducing the requirement for ultrasound imaging. Disclosures Wu: BMS-pfizer: Honoraria, Other: advisory board; leo pharma: Other: advisory board; Pfizer: Honoraria; Servier: Other: advisory board.
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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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».