Medicine (Baltimore). 2026 May 22;105(21):e48871. doi: 10.1097/MD.0000000000048871.
ABSTRACT
Cortical laminar necrosis (CLN) is a rare form of ischemic necrosis characterized by laminar damage primarily affecting the third to fifth cortical layers. CLN typically follows cerebral infarction but can also arise from various conditions. However, research on CLN is scarce, and predictive models have not yet been established, limiting clinical guidance. We aimed to analyze the risk factors for poor prognosis in patients with CLN after cerebral infarction and to construct a visual nomogram model with early predictive value. This retrospective study included 80 patients admitted to our hospital between January 2019 and December 2024. The modified Rankin Scale (mRS) was used to assess functional outcomes at 90 days after symptom onset. Clinical and imaging data were compared between patients with favorable outcomes (mRS 0-2, n = 56) and those with poor outcomes (mRS 3-6, n = 24). Independent risk factors for poor outcomes were identified through multivariable logistic regression analysis. R software was used to generate a nomogram; the model was evaluated and internally validated. Compared with the favorable outcome group, the poor outcome group had significantly higher age, admission National Institutes of Health Stroke Scale (NIHSS) score, C-reactive protein level, severity of white matter hyperintensity (WMH), and the degree of anterior cerebral artery (ACA) stenosis. Body mass index and albumin levels were significantly lower in the poor outcome than in the favorable outcome group (all P < .05). Admission NIHSS score (odds ratio [OR] = 1.317; 95% confidence interval [CI] 1.097-1.669; P = .008), WMH severity (OR = 5.273; 95% CI 1.181-28.519; P = .037), and degree of ACA stenosis (OR = 7.223; 95% CI 1.631-38.985; P = .013) were independent risk factors for poor outcome of CLN. The C-index (0.852) and calibration curve indicated that the nomogram model had high discriminative ability and accuracy. The area under the receiver operating characteristic curve was 0.867 (95% CI 0.811-0.906). Admission NIHSS score, WMH severity, and degree of ACA stenosis were independently and significantly associated with the prognosis of CLN. The nomogram model developed in this study exhibits strong predictive capability and good discriminative ability and accuracy, enhancing prognosis prediction in patients with CLN following cerebral infarction.
PMID:42175459 | DOI:10.1097/MD.0000000000048871