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Development and internal validation of a macrophage migration inhibitory factor-based risk assessment model for
JianBo Zhang1, ChengMing Bao2, AnKui Lu2
1Department of Neurosurgery, Nanjing Lishui People's Hospital, Nanjing, Jiangsu, China.
Background:
Delayed cerebral ischemia (DCI) is an important cause of poor outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH). Macrophage migration inhibitory factor (MIF) is involved in the regulation of inflammatory responses and may be associated with the development of DCI after aSAH. This study aimed to investigate the association between admission serum MIF levels and DCI in patients with aSAH and to develop an MIF-based risk assessment model for DCI.
Methods:
Patients with aSAH were included and divided into DCI and non-DCI groups according to the occurrence of DCI during hospitalization. Demographic characteristics, aneurysm-related features, hemorrhage burden indicators, admission laboratory parameters, and cardiac function parameters were collected. Baseline characteristics were compared between the two groups, and logistic regression analyses were performed to identify factors associated with DCI. A nomogram was constructed based on the final multivariable model, and model discrimination, calibration, and clinical utility were evaluated.
Results:
Among 100 patients with aSAH, 28 developed DCI. The DCI group had a higher proportion of patients with high modified Fisher grades, higher admission MIF levels, and lower LVEF. Several factors were associated with increased DCI risk, including elevated MIF, high modified Fisher grade, reduced LVEF, intraventricular hemorrhage, acute hydrocephalus, elevated white blood cell count, and elevated hs-cTnI. In the final model, elevated MIF, high modified Fisher grade, and reduced LVEF remained independently associated with DCI. The three-variable model demonstrated an AUC higher than that of any single predictor, acceptable calibration after bootstrap internal validation, and potential net benefit across clinically relevant thresholds.
Conclusion:
Increased admission MIF, high modified Fisher grade, and decreased LVEF were independently associated with higher DCI risk in patients with aSAH. An internally validated model incorporating these three indicators may offer a simple, interpretable tool for early DCI risk stratification. Its generalizability and clinical applicability require confirmation in larger, multicenter prospective cohorts.