Development and Validation of a New Nomogram for Predicting Early Neurological Deterioration in Young and Middle-Aged Individuals With Stroke in the Neurocritical Care Unit.

Objective: To analyse risk factors for early neurological damage in young and middle-aged stroke cases.

Methods: Totally 405 young and middle-aged stroke patients in the neurocritical care unit (NCU) were selected and divided into the developmental (260 patients) and validation (145 patients) sets. The 405 cases were also grouped based on whether early neurological deterioration (END) occurred. The influencing factors of END were analysed by logistic regression, followed by the construction of a nomogram for predicting the risk of END. The Bootstrap method was applied to internally verify the predictive value of the model, using validation set data.

Results: Age, type of stroke, diabetes, mechanical ventilation, pulse, initial National Institute of Health stroke scale (NIHSS), Barthel index (BI), haemoglobin, hypersensitive C-reactive protein (hs-CRP), triglyceride glucose (TyG) index and CONUT showed statistically significant differences (p < 0.05). Logistic regression analysis revealed type of stroke, initial NIHSS, CONUT, TyG index and hs-CRP were risk factors for END in young and middle-aged stroke cases (OR > 1, p < 0.05). The area under the curve (AUC) for the developmental set was 0.842, and internal validation results showed a C-index of 0.843; the AUC for the validation set was 0.843.

Conclusion: The nomogram constructed in this study has good predictive efficacy and can provide reference for early clinical prediction of END in young and middle-aged stroke cases.

Relevance to clinical practice: The importance of this research lies in shedding light on the significant impact of early neurological deterioration on the health outcomes of young and middle-aged stroke patients, particularly in the short term. To guide clinical workers to identify risk factors early and improve the prognosis of stroke patients.