医学
四分位间距
内科学
优势比
血管性血友病因子
置信区间
胃肠病学
血管性血友病
心脏病学
风险因素
胃肠道出血
前瞻性队列研究
外科
血小板
作者
Samson Hennessy-Strahs,Jooeun Kang,Eric Krause,Robert D. Dowling,J. Eduardo Rame,Carlo Bartoli
标识
DOI:10.1016/j.jtcvs.2022.03.018
摘要
Abstract
Background
Continuous-flow left ventricular assist devices (LVADs) cause an acquired von Willebrand factor (VWF) deficiency and bleeding. Models to risk-stratify for bleeding are urgently needed. We developed a model of continuous-flow LVAD bleeding risk from patient-specific severity of VWF degradation. Methods
In a prospective, longitudinal cohort study, paired blood samples were obtained from patients (n = 67) with a continuous-flow LVAD before and during support. After 640 ± 395 days, patients were categorized as all-cause bleeders, gastrointestinal (GI) bleeders, or nonbleeders. VWF multimers and VWF clotting function were evaluated to determine bleeding risk. Results
Of 67 patients, 34 (51%) experienced bleeding, 26 (39%) experienced GI bleeding, and 33 (49%) did not bleed. In all patients, LVAD support significantly reduced high-molecular-weight VWF multimers (P < .001). Bleeders exhibited greater loss of high-molecular-weight VWF multimers (mean ± standard deviation, –10 ± 5% vs –7 ± 4%, P = .008) and reduced VWF clotting function versus nonbleeders (median [interquartile range], –12% [–31% to 4%] vs 0% [–9 to 26%], P = .01). A combined metric of VWF multimers and VWF function generated the All-Cause Bleeding Risk Score, which stratified bleeders versus nonbleeders (86 ± 56% vs 41 ± 48%, P < .001) with a positive predictive value of 86% (95% confidence interval, 66%-95%) and diagnostic odds ratio of 11 (95% confidence interval, 2.9-44). A separate GI Bleeding Risk Score stratified GI bleeders versus nonbleeders (202 ± 114 vs 120 ± 86, P = .003) with a positive predictive value of 88% (64%-97%) and diagnostic odds ratio of 18 (3.1-140). Conclusions
The severity of loss of VWF multimers and VWF clotting function generated Bleeding Risk Scores with high predictive value for LVAD-associated bleeding. This model may guide personalized antithrombotic therapy and patient surveillance.
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