A clinical prediction score for upper extremity deep venous thrombosis

Author:

Salmi Louis-Rachid,Sevestre-Pietri Marie-Antoinette,Perusat Sophie,Nguon Monika,Degeilh Maryse,Labarere Jose,Gattolliat Olivier,Boulon Carine,Laroche Jean-Pierre,Roux Philippe Le,Pichot Olivier,Quéré Isabelle,Conri Claude,Bosson Jean-Luc,Constans Joel

Abstract

SummaryIt was the objective of this study to design a clinical prediction score for the diagnosis of upper extremity deep venous thrombosis (UEDVT).A score was built by multivariate logistic regression in a sample of patients hospitalized for suspicion of UEDVT (derivation sample). It was validated in a second sample in the same university hospital, then in a sample from the multicenter OPTIMEV study that included both outpatients and inpatients. In these three samples, UEDVT diagnosis was objectively confirmed by ultrasound. The derivation sample included 140 patients among whom 50 had confirmed UEDVT, the validation sample included 103 patients among whom 46 had UEDVT, and the OPTIMEV sample included 214 patients among whom 65 had UEDVT. The clinical score identified a combination of four items (venous material, localized pain, unilateral pitting edema and other diagnosis as plausible). One point was attributed to each item (positive for the first 3 and negative for the other diagnosis). A score of –1 or 0 characterized low probability patients, a score of 1 identified intermediate probability patients, and a score of 2 or 3 identified patients with high probability. Low probability score identified a prevalence of UEDVT of 12, 9 and 13%, respectively, in the derivation, validation and OPTIMEV samples. High probability score identified a prevalence of UEDVT of 70, 64 and 69% respectively. In conclusion we propose a simple score to calculate clinical probability of UEDVT. This score might be a useful test in clinical trials as well as in clinical practice.

Funder

public resources (Programme Hospitalier de Recherche Clinique)

Publisher

Georg Thieme Verlag KG

Subject

Hematology

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