Is Thrombophilia a Risk Factor for Peripheral Vein Infusion Thrombophlebitis?.
Notice bibliographique
Résumé
Abstract Background and Objectives. Peripheral vein infusion thrombophlebitis (PVIT) is a common complication in hospitalized patients receiving peripheral intravenous (IV) therapy. Although catheter-related risk factors such as catheter material have been well elucidated, patient-related factors have received little attention, despite evidence that (1) individuals vary in biologic vulnerability to developing PVIT; (2) there is biological evidence that thrombus formation may play a role in the pathogenesis of PVIT; and (3) thrombophilic disorders have been linked to central venous catheter thrombosis. We conducted a nested case-control study to determine whether patients who developed PVIT were more likely to have thrombophilia than patients without PVIT. Methods. A cohort of consecutive, hospitalized patients with peripheral IV catheters was prospectively assembled from 8 wards in 2 large tertiary care hospitals and followed until PVIT developed, the catheter was removed for reasons other than PVIT, or the patient was transferred with catheter in place to a non-study ward. Recruitment to the cohort continued until 100 patients, who developed PVIT, were eligible for case enrolment. For each case, 2 control patients who had not developed PVIT and who were matched to cases on catheter duration (days) were identified. PVIT was defined as the presence of two or more of the following at the catheter site: pain, tenderness, erythema, swelling, purulence, or a palpable cord. Factor V Leiden and prothrombin G20210A mutations and homocysteine levels were measured. Homocysteine levels ≥ 15μmol/L were considered elevated. The association between PVIT and thrombophilia was tested using multivariate conditional logistic regression analysis to account for the matched design. Results. From the cohort of 6426 patients with catheters, there were 113 PVIT episodes (PVIT incidence of 4.4 per 1000 catheter-days) of which 100 cases were eligible and matched to 200 randomly chosen controls. There were no differences between cases and controls with regard to age, sex distribution, history of previous venous thromboembolism (VTE) or presence of active cancer. Cases were less likely than controls to be taking anticoagulant medication(s) (9% vs. 16%, respectively, OR=0.46; 95% confidence interval (CI) [0.19, 1.12]). One or more prior episodes of PVIT was reported by 18% of cases vs. 6% of controls (OR=3.0; 95% CI [1.4, 6.2]). Prothrombin G20210A or Factor V Leiden was detected in 6% of cases and 6% of controls. Hyperhomocysteinemia was present in 24% of cases vs. 22% of controls (OR=1.23; 95% CI [0.69, 2.19]). Multivariable conditional regression analyses adjusted for age, sex and anticoagulant use showed that prior PVIT was an independent predictor of PVIT (OR=2.8; 95% CI [1.3, 6.0]), but thrombophilia did not predict PVIT (OR=1.02; 95% CI [0.57, 1.84]). Conclusions. We did not find an association between PVIT and Factor V Leiden, prothrombin gene mutation, or hyperhomocysteinemia, although our results suggest an unidentified patient-specific predisposition to PVIT. The pathogenesis of PVIT appears to be different than that of central venous catheter thrombosis, since thrombophilia, cancer and prior VTE, which are known risk factors for central venous catheter thrombosis, were not significantly associated with PVIT in our study.
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 | 0,005 |
| 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 | 0,001 |
| 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 ».