Association Between Inherited and Acquired Thrombophilias and The Post Thrombotic Syndrome: A Systematic Review and Metaanalysis
Notice bibliographique
Résumé
Introduction The post thrombotic syndrome (PTS) is a frequent complication of deep vein thrombosis (DVT), occurring in 20-40% of DVT patients. Identifying risk factors for PTS may be useful to provide patients with reliable prognostic information and target prevention strategies. Inherited and acquired thrombophilias are well established risk factors for DVT. We hypothesized that these markers may also increase the risk of PTS. Objective To conduct a systematic review to assess: Among patients with DVT, are inherited or acquired thrombophilias associated with risk of PTS? Methods We conducted a search of the electronic databases PubMed, EMBASE, Scopus, and Web of Science for studies published from 1990-2013. Studies were considered eligible if they reported assessing any thrombophilia in adult DVT patients and its association with the development of PTS. Risk of bias was assessed using a modified Newcastle-Ottawa scale. Meta-analysis was performed by pooling odds ratios (OR) using the random effects model, when three or more studies were available. Results After removal of duplicates, 2376 records were screened and 84 full text articles were assessed for eligibility. Sixteen studies were included in our review: 13 studies assessed Factor V Leiden (FVL), 10 assessed prothrombin gene mutation, 5 studies assessed protein S and C deficiencies, 3 assessed antithrombin deficiency, 4 assessed factor VIII activity, and 6 studies assessed antiphospholipid antibodies (6 studies assessed Lupus Anticoagulant (LAC) and 1 assessed Anticardiolipin Antibody). None of the meta-analyses performed identified any inherited or acquired thrombophilia to be predictive of PTS (Figure 1). We were unable to pool studies reporting the association between Factor VIII and PTS because of clinical heterogeneity, however, descriptively, the predictive value of FVIII for PTS seems to be limited. We conducted subgroup analyses stratifying studies by patient characteristics (Table 1). Both FVL and prothrombin mutations appeared to be protective for PTS among studies including patients with both first and recurrent DVT, and studies where >50% of patients had an unprovoked DVT. Our pooled estimate for the effect of antiphospholipid antibodies is largely based on studies that measured LAC while on anticoagulant treatment, hence may be an underestimate. However, the confidence intervals for the estimates overlapped the null for all of these subgroups. A sensitivity analysis was conducted to restrict to studies that used a more rigorous definition of PTS (using only the Villalta scale). FVL was associated with an OR 0.88 (6 studies; 95% CI: 0.66, 1.18) and prothrombin mutation with an OR 0.91 (6 studies; 95% CI: 0.55, 1.49). Hence, FVL appeared protective when we restricted to higher quality studies. Conclusions Our meta-analysis did not demonstrate a significant association between any of the thrombophilias assessed and the risk of PTS in DVT patients, however, we cannot rule out a mild protective effect of FVL and prothrombin mutation in certain subgroups. As the pathophysiology of PTS involves the complex interplay of persistent venous obstruction, valvular incompetence and inflammation, other biomarkers may be more predictive of the patient’s risk of PTS. Disclosures: No relevant conflicts of interest to declare.
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 | 0,012 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,018 | 0,028 |
| Bibliométrie | 0,007 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».