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Integrating clinical, laboratory, and imaging markers: a nomogram with favorable predictive performance for early neurological deterioration in minor acute ischemic stroke

Year: 2026

Type: article

Abstract: Early neurological deterioration (END) in minor acute ischemic stroke (mAIS) is strongly associated with poor functional outcomes. However, consistent risk factors for END in mAIS remain undefined. This study sought to identify independent predictors of END in mAIS and develop a predictive nomogram to enable timely clinical intervention. We conducted a retrospective analysis of 438 consecutive mAIS patients (National Institute of Health Stroke Scale [NIHSS] score of ≤ 5) admitted to the Second Xiangya Hospital of Central South University between January 2013 and December 2024. Patients were randomly divided into training and validation cohorts in 7:3 ratio. Multivariate logistic regression was used to identify independent END predictors, and a nomogram was developed. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis, Hosmer-Lemeshow test, and decision curve analysis (DCA). END occurred in 133 (30.37%) patients. Independent predictors of END included hemiplegia (OR 3.38, 95%CI: 2.38 to 4.80), sodium level (OR 0.69, 95%CI: 0.50 to 0.97), glycosylated hemoglobin (OR 1.67, 95%CI: 1.55 to 2.39), C-reactive protein (OR 1.53, 95%CI: 1.16 to 2.01), multiple cerebral infarcts (OR 2.39, 95%CI: 1.72 to 3.12), large cerebral infarcts (OR 1.67, 95%CI: 1.18 to 2.37). The nomogram achieved an AUC of 0.865 in the validation set. Internal validation was further performed using bootstrap resampling (1000 iterations), with an optimism-corrected AUC of 0.835, indicating stable model performance. The model showed good calibration (Hosmer-Lemeshow P = 0.722), and provided favorable net benefit across most threshold probabilities on DCA. The six-factor nomogram integrating clinical, laboratory, and imaging markers demonstrates good predictive performance and potential utility for identifying mAIS patients at high risk of END.

Source: BMC Neurology

DOI: 10.1186/s12883-026-05201-z