Prediction of functional outcome using the novel asymmetric middle cerebral artery index in cryptogenic stroke patients

Minho Han, Young Dae Kim, Hyung Jong Park, In Gun Hwang, Junghye Choi, Jimin Ha, Ji Hoe Heo, Hyo Suk Nam

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4 Citations (Scopus)


Background 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. Methods 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. Results 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). Conclusion We demonstrated that the novel asymmetric MCA index can predict short-term functional outcomes in CS patients.

Original languageEnglish
Article numbere0208918
JournalPloS one
Issue number1
Publication statusPublished - 2019 Jan

Bibliographical note

Publisher Copyright:
© 2019 Han et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

All Science Journal Classification (ASJC) codes

  • General


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