Establishment of a bleeding score as a diagnostic tool for patients with rare bleeding disorders. Issue 148 (December 2016)

• Record Type: Journal Article
• Authors: Palla, Roberta; Siboni, Simona M.; Menegatti, Marzia; Musallam, Khaled M; Peyvandi, Flora
• Is Part Of: Thrombosis research. Issue 148(2016)
• Page Start: 128
• Page End: 134
• Publication Date: 2016-12
• Subjects: AUC area under the curve -- BAT bleeding assessment tool -- BS bleeding score -- BSS bleeding score system -- CI 95% confidence intervals -- CNS central nervous system -- EN-RBD European Network of Rare Bleeding Disorders -- F factor -- RBD rare bleeding disorder -- ROC receiver-operator curve -- VWD von Willebrand disease; Bleeding score -- Diagnostic tool -- Rare bleeding disorders -- Coagulation factors deficiency; Thrombosis -- Periodicals; 616.135
• DOI: 10.1016/j.thromres.2016.11.008
• Languages: English
• ISSNs: 0049-3848

Abstract

Abstract: Introduction: Bleeding manifestations among patients with rare bleeding disorders (RBDs) vary significantly between disorders and patients, even when affected with the same disorder. In response to the challenge represented by the clinical assessment of the presence and severity of bleeding symptoms, a number of bleeding score systems (BSSs) or bleeding assessment tools (BATs) were developed. The majority of these were specifically developed for patients with more common bleeding disorders than RBDs. Few RBDs patients were evaluated with these tools and without conclusive results. Methods: A new BSS was developed using data retrieved from a large group of patients with RBDs enrolled in the EN-RBD database and from healthy subjects. These data included previous bleeding symptoms, frequency, spontaneity, extent, localization, and relationship to prophylaxis and acute treatment. The predictive power of this BSS was also compared with the ISTH-BAT and examined for the severity of RBDs based on coagulant factor activity. Results: This BSS was able to differentiate patients with RBDs from healthy individuals with a bleeding score value of 1.5 having the highest sum of sensitivity (67.1%) and specificity (73.8%) in discriminating patients with RBD from those without. An easy-to-use calculation was also developed to assess the probability of having a RBD. Its comparison with the ISTH-BAT confirmed its utility. Finally, in RBDs patients, there was a significant negative correlation between BS and coagulant factor activity level, which was strongest for fibrinogen and FXIII deficiencies. Conclusion: The use of this quantitative method may represent a valuable support tool to clinicians. Highlights: Rare bleeding disorders (RBDs) are characterized by a wide variety of symptoms. The evaluation of bleeding symptoms should be objective to plan subsequent workup. Data from patients with RBDs and controls were used to develop a bleeding score. This tool was able to differentiate patients with RBDs from healthy individuals. An easy-to-use formula was developed to calculate the probability of having a RBD.