• Xiaobo Yang, Jianhua Peng, Jinwei Pang, Weifeng Wan, Chuanhong Zhong, Tangming Peng, Kunyang Bao, and Yong Jiang.
• Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, No 25. Taiping Street, Jiangyang District, Luzhou, 646000, Sichuan Province, China.
• Neurotox Res. 2020 Feb 1; 37 (2): 397-405.

AbstractInflammatory processes have long been implicated in the development of delayed cerebral ischemia (DCI) following aneurysmal subarachnoid hemorrhage (aSAH). Macrophage migration inhibitory factor (MIF) has been implicated in inflammation. The aim of this study was to assess whether serum levels of MIF at admission helps to predict which patients with aSAH would subsequently develop DCI. All patients with first-ever aSAH admitted between 2016 and 2017 were considered for inclusion in this prospective study. Primary study outcome was development of DCI at discharge. Serum levels of MIF, C-reactive protein (CRP), and interleukin-6 (IL-6) were tested at admission. The relation of serum levels of MIF at admission with DCI was assessed by the logistic regression models. In this study, 201 patients were included. A correlation between Hunt and Hess score and serum levels of MIF was found (r = 0.340; P < 0.001). Fifty-two of the 201 aSAH (25.9%) were defined as DCI, and the obtained MIF level in those patients was higher than in those patients without DCI [26.4 (IQR, 22.6-32.4) ng/ml vs. 20.4 (16.4-24.6) ng/ml; P < 0.001). As a continuous variable, MIF was associated with the risk of DCI. When serum level of MIF was elevated by each 1 ng/ml, the unadjusted risk of DCI was increased by 18% (OR = 1.18 [1.12-1.25], P < 0.001), while the adjusted risk was increased by 10% (1.10 [1.03-1.19], P = 0.001). With the area under the curve (AUC) of 0.780 (95% CI, 0.710-0.849), the MIF showed a great discriminatory ability for DCI than CRP (0.665, 0.582-0.748; P < 0.001) and IL-6 (0.721, 0.642-0.799; P = 0.001). Interestingly, the combined model (MIF/IL-6/CRP) improved the MIF to predict DCI (AUC of the combined model: 0.811; 95% CI, 0.751-0.871; P = 0.024). Furthermore, inclusion of MIF in the existing risk factors for the prediction of DCI enhanced the index and net reclassification improvement (NRI) (P < 0.001) and integrated discrimination improvement (IDI) (P = 0.005) values, confirming the effective reclassification and discrimination. The data showed that elevated MIF serum level accurately identifies patients at highest risk for developing DCI following aSAH.

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