Bouslama Mehdi, Bowen Meredith T, Haussen Diogo C, Dehkharghani Seena, Grossberg Jonathan A, Rebello Letícia C, Rangaraju Srikant, Frankel Michael R, Nogueira Raul G
Departments of Neurology, Radiology and Neurosurgery Grady Memorial Hospital and Emory University School of Medicine, Atlanta, GA, USA.
Cerebrovasc Dis. 2017;44(5-6):277-284. doi: 10.1159/000478537. Epub 2017 Sep 7.
Optimal patient selection methods for thrombectomy in large vessel occlusion stroke (LVOS) are yet to be established. We sought to evaluate the ability of different selection paradigms to predict favorable outcomes.
Review of a prospectively collected database of endovascular patients with anterior circulation LVOS, adequate CT perfusion (CTP), National Institutes of Health Stroke Scale (NIHSS) ≥10 from September 2010 to March 2016. Patients were retrospectively assessed for thrombectomy eligibility by 4 mismatch criteria: Perfusion-Imaging Mismatch (PIM): between CTP-derived perfusion defect and ischemic core volumes; Clinical-Core Mismatch (CCM): between age-adjusted NIHSS and CTP core; Clinical-ASPECTS Mismatch (CAM-1): between age-adjusted NIHSS and ASPECTS; Clinical-ASPECTS Mismatch (CAM-2): between NIHSS and ASPECTS. Outcome measures were inclusion rates for each paradigm and their ability to predict good outcomes (90-day modified Rankin Scale 0-2).
Three hundred eighty-four patients qualified. CAM-2 and CCM had higher inclusion (89.3 and 82.3%) vs. CAM-1 (67.7%) and PIM (63.3%). Proportions of selected patients were statistically different except for PIM and CAM-1 (p = 0.19), with PIM having the highest disagreement. There were no differences in good outcome rates between PIM(+)/PIM(-) (52.2 vs. 48.5%; p = 0.51) and CAM-2(+)/CAM-2(-) (52.4 vs. 38.5%; p = 0.12). CCM(+) and CAM-1(+) had higher rates compared to nonselected counterparts (53.4 vs. 38.7%, p = 0.03; 56.6 vs. 38.6%; p = 0.002). The abilities of PIM, CCM, CAM-1, and CAM-2 to predict outcomes were similar according to the c-statistic, Akaike and Bayesian information criterion.
For patients with NIHSS ≥10, PIM appears to disqualify more patients without improving outcomes. CCM may improve selection, combining a high inclusion rate with optimal outcome discrimination across (+) and (-) patients. Future studies are warranted.
大血管闭塞性卒中（LVOS）血栓切除术的最佳患者选择方法尚未确立。我们试图评估不同选择模式预测良好预后的能力。
回顾2010年9月至2016年3月前瞻性收集的前循环LVOS、CT灌注（CTP）充分、美国国立卫生研究院卒中量表（NIHSS）≥10的血管内治疗患者数据库。通过4种不匹配标准对患者进行回顾性评估以确定是否适合进行血栓切除术：灌注成像不匹配（PIM）：CTP衍生的灌注缺损与缺血核心体积之间；临床核心不匹配（CCM）：年龄校正后的NIHSS与CTP核心之间；临床-ASPECTS不匹配（CAM-1）：年龄校正后的NIHSS与ASPECTS之间；临床-ASPECTS不匹配（CAM-2）：NIHSS与ASPECTS之间。结局指标为每种模式的纳入率及其预测良好结局（90天改良Rankin量表0-2）的能力。
384例患者符合条件。与CAM-1（67.7%）和PIM（63.3%）相比，CAM-2和CCM的纳入率更高（分别为89.3%和82.3%）。除PIM和CAM-1外（p = 0.19），所选患者比例在统计学上存在差异，PIM的分歧最大。PIM（+）/PIM（-）（52.2%对48.5%；p = 0.51）和CAM-2（+）/CAM-2（-）（52.4%对38.5%；p = 0.12）之间的良好结局率无差异。与未被选中的患者相比，CCM（+）和CAM-1（+）的比率更高（分别为53.4%对38.7%，p = 0.03；56.6%对38.6%；p = 0.002）。根据c统计量、赤池信息准则和贝叶斯信息准则，PIM、CCM、CAM-1和CAM-2预测结局的能力相似。
对于NIHSS≥10的患者，PIM似乎使更多患者失去资格，而未改善结局。CCM可能改善选择，将高纳入率与对（+）和（-）患者的最佳结局区分能力相结合。有必要进行进一步研究。
