Ten-year trends in iliofemoral deep vein thrombosis treatment and referral pathways
Notice bibliographique
Résumé
Objectives Iliofemoral deep venous thrombosis is associated with an increased risk of developing post-thrombotic syndrome resulting in reduced quality of life. As there is debate about best management practices, this study aimed to examine the referral and treatment pathways for patients presenting with iliofemoral deep venous thrombosis over an 11-year period at our institution. Methods We conducted a retrospective review of patients diagnosed with lower limb deep vein thrombosis between 2010 and 2020. Ultrasound report findings were reviewed for the presence of iliofemoral deep venous thrombosis with acute, occlusive, or proximal clot. Multiple factors were extracted, including patient demographics, risk factors, diagnostic methods, interventions, referrals, and details of follow-up. The CaVenT and ATTRACT trials studied the benefit of thrombolysis in the early phase of iliofemoral deep venous thrombosis management as compared to anticoagulation alone. An analysis was conducted of patients requiring thrombolysis to determine whether these trials impacted physician practice patterns for thrombolysis. Data were organized and examined by year for trends in treatment and referral pathways. Results The review yielded 2792 patients assessed for lower limb deep venous thrombosis by ultrasound. Four hundred and sixty-seven (16.7%) patients were confirmed to have an occlusive iliofemoral deep venous thrombosis. The average age was 62.7 years (18–101 years). Half (50.4%) of the patients were male. The most common etiology for clot was malignancy-induced hypercoagulable state (39.0%). There was no difference in incidence of iliofemoral deep venous thrombosis diagnosed by ultrasound per year, with an average of 42.5 per year and a peak of 61. There was a trend towards increased rates of computed tomography imaging, ranging between 9.1% and 52.9%. The rate thrombolysis per year ranged between 1.8% and 8.9%, with a range of 4.3% ( n = 20) to 8.9% ( n = 5) in 2018. The use of pharmacomechanical thrombolysis increased, from 25% ( n = 1) in 2010–2012 to 87.5% ( n = 7) in 2018–2020. The rate of inferior vena cava filter insertion alone decreased from 18.2% in 2010 ( n = 4) to 5.9% ( n = 1) in 2020. The length of thrombolysis treatment also decreased, from 100% of patients ( n = 4) receiving treatment duration greater than 24 h in 2010–2012 to 0% ( n = 0) in 2018–2020. About 45% of patients receiving thrombolysis ( n = 9) had venous stenting. No difference in treatment outcomes were observed, with greater than 87.5% of patients reaching intermediate to full resolution of clot burden. No patients experienced intracranial hemorrhage. Conclusions The results of this analysis highlight the change in practice in our institution over time. The low rate of intervention likely reflects the current lack of consensus in published guidelines. It is important for future work to elicit the most appropriate management pathways for patients with iliofemoral deep venous thrombosis.
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 | 0,002 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,006 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».