三种临床模型预测血栓后综合征发生的性能和头对头比较：一项验证研究。
Performance and Head-to-Head Comparison of Three Clinical Models to Predict Occurrence of Postthrombotic Syndrome: A Validation Study.
机构信息
Department of Medicine (Division of Hematology) and the Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada.
Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada.
出版信息
Thromb Haemost. 2023 Jul;123(7):692-699. doi: 10.1055/a-2039-3388. Epub 2023 Feb 21.
OBJECTIVE
The SOX-PTS, Amin, and Méan models are three different clinical prediction scores stratifying the risk for postthrombotic syndrome (PTS) development in patients with acute deep vein thrombosis (DVT) of the lower limbs. Herein, we aimed to assess and compare these scores in the same cohort of patients.
METHODS
We retrospectively applied the three scores in a cohort of 181 patients (196 limbs) who participated in the SAVER pilot trial for an acute DVT. Patients were stratified into PTS risk groups using positivity thresholds for high-risk patients as proposed in the derivation studies. All patients were assessed for PTS 6 months after index DVT using the Villalta scale. We calculated the predictive accuracy for PTS and area under receiver operating characteristic (AUROC) curve for each model.
RESULTS
The Méan model was the most sensitive (sensitivity 87.7%; 95% confidence interval [CI]: 77.2-94.5) with the highest negative predictive value (87.5%; 95% CI: 76.8-94.4) for PTS. The SOX-PTS was the most specific score (specificity 97.5%; 95% CI: 92.7-99.5) with the highest positive predictive value (72.7%; 95% CI: 39.0-94.0). The SOX-PTS and Méan models performed well for PTS prediction (AUROC: 0.72; 95% CI: 0.65-0.80 and 0.74; 95% CI: 0.67-0.82), whereas the Amin model did not (AUROC: 0.58; 95% CI: 0.49-0.67).
CONCLUSION
Our data support that the SOX-PTS and Méan models have good accuracy to stratify the risk for PTS.
目的
SOX-PTS、Amin 和 Méan 模型是三种不同的临床预测评分，用于分层下肢急性深静脉血栓形成（DVT）患者发生血栓后综合征（PTS）的风险。在此，我们旨在评估和比较这三种评分在同一队列患者中的表现。
方法
我们回顾性地将这三种评分应用于参与 SAVER 急性 DVT 试验的 181 例（196 条肢体）患者的队列中。采用推导研究中提出的高危患者阳性截断值，将患者分层为 PTS 风险组。所有患者在 DVT 后 6 个月采用 Villalta 量表评估 PTS。我们计算了每个模型的 PTS 预测准确性和受试者工作特征（ROC）曲线下面积（AUROC）。
结果
Méan 模型的敏感性最高（87.7%；95%置信区间[CI]：77.2-94.5），阴性预测值最高（87.5%；95% CI：76.8-94.4），用于 PTS。SOX-PTS 是最特异的评分（特异性 97.5%；95% CI：92.7-99.5），阳性预测值最高（72.7%；95% CI：39.0-94.0）。SOX-PTS 和 Méan 模型对 PTS 预测表现良好（AUROC：0.72；95% CI：0.65-0.80 和 0.74；95% CI：0.67-0.82），而 Amin 模型则不然（AUROC：0.58；95% CI：0.49-0.67）。
结论
我们的数据支持 SOX-PTS 和 Méan 模型具有良好的 PTS 风险分层准确性。
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