Department of Cardiology, Tokyo Women's Medical University Medical Center East, Tokyo, Japan.
Department of Cardiology, Tokyo Women's Medical University Medical Center East, Tokyo, Japan.
Thromb Res. 2022 Aug;216:90-96. doi: 10.1016/j.thromres.2022.06.007. Epub 2022 Jun 24.
Patients with COVID-19 and cardiovascular disease risk factors (CVDRF) have been reported to develop coagulation abnormalities frequently. However, there are limitations in conventional predictive models for the occurrence of thromboembolism in patients with COVID-19 and CVDRF.
Among data on 1518 hospitalized patients with COVID-19 registered with CLAVIS-COVID, a Japanese nationwide cohort study, 693 patients with CVDRF were subjected to least absolute shrinkage and selection operator (LASSO) analysis; a method of shrinking coefficients for reducing variance and minimizing bias to increase predictive accuracy. LASSO analysis was performed to identify risk factors for systemic thromboembolic events; occurrence of arterial and venous thromboembolism during the index hospitalization as the primary endpoint.
LASSO analysis identified a prior systemic thromboembolism, male sex, hypoxygenemia requiring invasive mechanical ventilation support, C-reactive protein levels and D-dimer levels at admission, and congestion on chest X-ray at admission as potential risk factors for the primary endpoint. The developed risk model consisting of these risk factors showed good discriminative performance (AUC-ROC: 0.83, 95 % confidence interval [CI]: 0.77-0.90), which was significantly better than that shown by D-dimer (AUC-ROC: 0.70, 95 % CI: 0.60-0.80) (p < 0.001). Furthermore, systemic embolic events were independently associated with in-hospital mortality (adjusted odds ratio: 3.29; 95 % CI: 1.31-8.00).
Six parameters readily available at the time of admission were identified as risk factors for thromboembolic events, and these may be capable of stratifying the risk of in-hospital thromboembolic events, which are associated with in-hospital mortality, in patients with COVID-19 and CVDRF.
有报道称，患有 COVID-19 和心血管疾病风险因素（CVDRF）的患者经常出现凝血异常。然而，对于 COVID-19 和 CVDRF 患者发生血栓栓塞的常规预测模型存在局限性。
在 CLAVIS-COVID 日本全国性队列研究中，对 1518 名住院 COVID-19 患者的数据进行了分析，其中 693 名患者患有 CVDRF，对其进行了最小绝对收缩和选择算子（LASSO）分析；这是一种缩小系数的方法，用于减少方差并最小化偏差，以提高预测准确性。LASSO 分析用于确定发生全身性血栓栓塞事件的危险因素；将住院期间发生的动脉和静脉血栓栓塞事件作为主要终点。
LASSO 分析确定了既往全身性血栓栓塞、男性、需要侵入性机械通气支持的低氧血症、入院时 C 反应蛋白水平和 D-二聚体水平、入院时胸部 X 射线显示充血等作为主要终点的潜在危险因素。由这些危险因素组成的风险模型显示出良好的区分性能（AUC-ROC：0.83，95%置信区间 [CI]：0.77-0.90），明显优于 D-二聚体（AUC-ROC：0.70，95% CI：0.60-0.80）（p<0.001）。此外，全身性栓塞事件与住院期间死亡率独立相关（调整后比值比：3.29；95%CI：1.31-8.00）。
在入院时即可获得的 6 个参数被确定为血栓栓塞事件的危险因素，这些因素可能能够对 COVID-19 和 CVDRF 患者住院期间血栓栓塞事件的风险进行分层，而这些事件与住院期间死亡率相关。
