20-hydroxyeiscosatetraenoic acid may be as a predictor of malignant middle cerebral artery infarction in patients with massive middle cerebral artery infarction

Background Early identification of massive middle cerebral artery infarction (MCAI) at risk for malignant MCAI (m-MCAI) may be useful in selecting patients for aggressive therapies. The aim of this study was to determine whether CYP metabolites may help to predict impending m-MCAI. Methods This is a prospective, two-center observational study in 256 patients with acute massive MCAI. Plasma levels of 20-hydroxyeicosatetraenoic acid (20-HETE), epoxyeicosatrienoic acids, and dihydroxyeicosatrienoic acids were measured at admission. Brain computed tomography (CT) was performed at admission and repeated between day 3 and 7, or earlier if there was neurological deterioration. The primary outcome was m-MCAI. The m-MCAI was diagnosed when follow-up brain CT detected a more than two-thirds space-occupying MCAI with midline shift, compression of the basal cisterns, and neurological worsening. Results In total of 256 enrolled patients, 77 (30.1%) patients developed m-MCAI. Among the 77 patients with m-MCAI, 60 (77.9%) patients died during 3 months of stroke onset. 20-HETE level on admission was significantly higher in patients with m-MCAI than those without m-MCAI. There was an increase in the risk of m-MCAI with increase of 20-HETE levels. The third and fourth quartiles of 20-HETE levels were independent predictors of m-MCAI (OR: 2.86; 95% CI: 1.16 - 6.68; P = 0.025, and OR: 4.23; 95% CI: 1.35 - 8.26; P = 0.002, respectively). Conclusions Incidence of m-MCAI was high in patients with massive MCAI and the prognosis of m-MCAI is very poor. Elevated plasma 20-HETE may be as a predictor for m-MCAI in acute massive MCAI, and it might useful in clinical practice in therapeutic decision making.

Automated summary

The study showed that elevated plasma 20-HETE levels may serve as a predictor for malignant MCAI in acute massive MCAI, with potential implications for therapeutic decision-making in clinical practice.