Department of Neurology, Yonsei University College of Medicine, Seoul, Korea.
Department of Science for Aging, Yonsei University Graduate School, Seoul, Korea.
PLoS One. 2019 Jan 2;14(1):e0208918. doi: 10.1371/journal.pone.0208918. eCollection 2019.
Etiology is unknown in approximately one-quarter of stroke patients after evaluation, which is termed cryptogenic stroke (CS). The prognosis of CS patients is largely undetermined. We created a novel index from transcranial Doppler parameters including mean flow velocity (MV) and pulsatility index (PI) and investigated whether the calculation of asymmetry in the novel parameter can predict functional outcomes in CS patients.
We made the middle cerebral artery (MCA) index (%) as a novel parameter, which was calculated as 100 X (MCA MV + MCA PI X 10) / (MCA MV-MCA PI X 10). The MCA asymmetry index (%) was also calculated as 100 X (|Rt MCA index-Lt MCA index|) / (Rt MCA index + Lt MCA index) / 2. Poor functional outcomes were defined as modified Rankin Scale score (mRS) ≥3 at 3 months after stroke onset.
A total of 377 CS patients were included. Among them, 52 (13.8%) patients had a poor outcome. The overall MCA asymmetry index was two-fold higher in CS patients with a poor outcome (10.26%) compared to those with a good outcome (5.41%, p = 0.002). In multivariable analysis, the overall MCA asymmetry index (OR, 1.054, 95% CI, 1.013-1.096, p = 0.009) and the cutoff value of the overall MCA asymmetry index >9 were associated with poor outcomes at 3 months (OR, 3.737, 95% CI, 1.530-9.128, p = 0.004).
We demonstrated that the novel asymmetric MCA index can predict short-term functional outcomes in CS patients.
在经过评估后，大约有四分之一的中风患者的病因仍不清楚，这种情况被称为隐源性中风（CS）。CS 患者的预后在很大程度上尚未确定。我们从经颅多普勒参数中创建了一个新的指数，包括平均血流速度（MV）和搏动指数（PI），并研究了计算新参数的不对称性是否可以预测 CS 患者的功能结局。
我们将大脑中动脉（MCA）指数（%）作为一个新的参数，其计算公式为 100X（MCA MV + MCA PI X 10）/（MCA MV-MCA PI X 10）。还计算了 MCA 不对称指数（%），其计算公式为 100X（|Rt MCA 指数-Lt MCA 指数|）/（Rt MCA 指数+ Lt MCA 指数）/2。功能结局不良定义为中风发病后 3 个月时改良 Rankin 量表评分（mRS）≥3。
共纳入 377 例 CS 患者。其中，52 例（13.8%）患者预后不良。预后不良的 CS 患者的总体 MCA 不对称指数（10.26%）是预后良好的 CS 患者（5.41%）的两倍（p=0.002）。多变量分析显示，总体 MCA 不对称指数（OR，1.054，95%CI，1.013-1.096，p=0.009）和总体 MCA 不对称指数>9 的截断值与 3 个月时的不良结局相关（OR，3.737，95%CI，1.530-9.128，p=0.004）。
我们证明了新的不对称 MCA 指数可以预测 CS 患者的短期功能结局。
