Brain and Behavior (Apr 2022)

Synthetic role of miR‐200b‐3p, ABCD2 score, and carotid ultrasound in the prediction of cerebral infarction in patients with transient ischemic attack

  • Jiwei Zheng,
  • Zhirong Wang,
  • Na Li,
  • Xiaomeng Zhang,
  • Xiaoguang Huo

DOI
https://doi.org/10.1002/brb3.2518
Journal volume & issue
Vol. 12, no. 4
pp. n/a – n/a

Abstract

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Abstract Background Transient ischemic attack (TIA) is a major risk factor for the occurrence of cerebral infarction (CI). This study aimed to evaluate the predictive value of the synthetic role of miR‐200b‐3p, ABCD2 score, and carotid ultrasound for CI onset in patients with TIA. Methods Expression of miR‐200b‐3p was detected by reverse transcription quantitative PCR and carotid stenosis degree was evaluated using carotid ultrasound examination. Association of miR‐200b‐3p with ABCD2 scores and carotid stenosis degree was assessed using t‐test and chi‐square test. Logistic regression analysis was used to judge the ability of miR‐200b‐3p, ABCD2 score, and carotid ultrasound to predict the occurrence of CI. Receiver operating characteristic curve was used to analyze the diagnostic value of miR‐200b‐3p and the accuracy of miR‐200b‐3p, ABCD2 score, and carotid ultrasound in predicting CI development. Results Expression of serum miR‐200b‐3p was significantly increased in TIA patients compared with healthy controls, and had diagnostic value in TIA patients. Serum miR‐200b‐3p was significantly associated with dyslipidemia, ABCD2 score, and carotid stenosis degree in TIA patients. ABCD2 score, carotid stenosis degree, and serum miR‐200b‐3p were independently associated with CI onset, and the synthetic role of these three indicators had the best accuracy in the prediction of CI onset in TIA patients. Conclusion Serum miR‐200b‐3p expression was increased in TIA patients with considerable diagnostic value to screen TIA cases from healthy controls. Moreover, we speculated that the combination of miR‐200b‐3p, ABCD2 score, and carotid stenosis degree by ultrasound may propose as an efficient predictive strategy for the prediction of CI in TIA patients.

Keywords