Mousa Albeir Y, Broce Mike, De Wit David, Baskharoun Mina, Abu-Halimah Shadi, Yacoub Michael, Bates Mark C
Department of Surgery, Robert C. Byrd Health Sciences Center, West Virginia University & Charleston Area Medical Center, Charleston, WV.
Center for Health Services and Outcomes Research, Charleston Area Medical Center Health Education and Research Institute, Charleston, WV.
Ann Vasc Surg. 2018 Jul;50:21-29. doi: 10.1016/j.avsg.2017.12.006. Epub 2018 Mar 1.
The D-dimer (DD) level combined with the pretest Wells criteria probability (WCP) score can safely exclude deep venous thrombosis (DVT). The objective of this study was to examine the correlation between DD results alongside WCP score with findings on venous duplex ultrasound (VDU). The hypothesis is that VDU remains overutilized in low-risk patients with negative DD and that higher DD levels may correlate with thrombus burden and location.
Patients who presented to a high-volume tertiary care center with lower limb swelling with or without associated pain were retrospectively examined through June and July for 4 consecutive years (2012 to 2015). After calculating WCP, patients were divided into low-, moderate-, and high-risk categories. Electronic DD results utilizing enzyme linked immunosorbent assay, WCP data, and VDU analysis data were merged and analyzed based on receiver operator characteristic curve to determine the DD cutoff point for each WCP. Abnormal DD with an average value ≥ 0.6 mg/L fibrinogen equivalent units (FEUs) was correlated to positive DVT to differentiate proximal DVT (above popliteal vein) from distal DVT (below popliteal vein).
Data of 1,909 patients were analyzed, and 239 (12.5%) patients were excluded secondary to serial repeat visits or follow-ups, surveillance screens, and if they had a previous history of DVT. The average age was 62.1 ± 16.3 years with more women (55.7%) and the majority presented with limb pain and edema (87%). DD studies were ordered and completed in 202 patients and correlated with all positive and negative DVT patients (100% sensitivity and negative predictive value, with specificity and positive predictive value of 14.9% and 15.9%, respectively). Twenty-six of 202 patients had DD that were in the normal range 0.1-0.59 mg/L (FEU), all of which were negative for DVT (100% sensitive). Fifty one of 202 patients had DD values of 0.6-1.2 mg/L FEU, of which only 3 DVTs were recorded, and all of them were distal DVTs. In addition, 685 patients with WCP <1 and negative DD were sent for VDU. Thus, 762 patients had an unnecessary immediate VDU (Wells ≤1 and -DD) study during their initial presentation. Potential charge savings for VDU for all patients are 762 × $1,557 = $1,186,434 and DD for all patients are 762 × $182 = $138,684, with total potential savings of $1,047,750 (USD 2016).
This study suggests that DD is still underutilized, and DD in conjunction with WCP could significantly reduce the number of unnecessary immediate VDUs. Higher value of DD (>1.2 mg/L FEU) may raise concern for proximal DVT. Concern on cost-effectiveness exists and raises the demand for a proposed algorithm to be followed.
D - 二聚体(DD)水平与检测前Wells标准概率(WCP)评分相结合可安全排除深静脉血栓形成(DVT)。本研究的目的是检验DD结果及WCP评分与静脉超声(VDU)检查结果之间的相关性。研究假设是,在DD结果为阴性的低风险患者中,VDU检查仍存在过度使用的情况,且较高的DD水平可能与血栓负荷及部位相关。
连续4年(2012年至2015年)的6月和7月,对一家大型三级医疗中心出现下肢肿胀伴或不伴相关疼痛的患者进行回顾性研究。计算WCP后,将患者分为低、中、高风险类别。利用酶联免疫吸附测定法得出的电子DD结果、WCP数据和VDU分析数据,基于受试者工作特征曲线进行合并分析,以确定每个WCP对应的DD临界值。平均数值≥0.6mg/L纤维蛋白原当量单位(FEU)的异常DD与阳性DVT相关,以区分近端DVT(腘静脉以上)和远端DVT(腘静脉以下)。
分析了1909例患者的数据,239例(12.5%)患者因多次复诊或随访、监测筛查以及既往有DVT病史而被排除。平均年龄为62.1±16.3岁,女性居多(55.7%),大多数患者表现为肢体疼痛和水肿(87%)。对202例患者进行了DD检测并完成分析,其结果与所有DVT阳性和阴性患者相关(敏感性和阴性预测值均为100%,特异性和阳性预测值分别为14.9%和15.9%)。202例患者中有26例的DD在正常范围0.1 - 0.59mg/L(FEU),所有这些患者的DVT检查均为阴性(敏感性100%)。202例患者中有51例的DD值为0.6 - 1.2mg/L FEU,其中仅记录到3例DVT,且均为远端DVT。此外,685例WCP<1且DD阴性的患者接受了VDU检查。因此,762例患者在初次就诊时进行了不必要的即时VDU(Wells≤1且 -DD)检查。所有患者VDU检查潜在节省费用为762×1557美元 = 1186434美元,所有患者DD检查潜在节省费用为762×182美元 = 138684美元,总计潜在节省1047750美元(2016年美元)。
本研究表明,DD检查的利用仍不足,DD与WCP相结合可显著减少不必要的即时VDU检查数量。较高的DD值(>1.2mg/L FEU)可能提示近端DVT。存在对成本效益的担忧,因此需要遵循所提议算法的需求。