Analyzing the serum biochemical factors that influence early neurological deterioration in ischemic Stroke patients and developing a nomogram prediction model

Background: To investigate the risk factors associated with early neurological deterioration (END) in ischemic stroke (IS) patients and develop a predictive nomogram model. Methods: General clinical data from 220 IS patients treated between December 2022 and November 2023 were collected for observation. The study's inclusion and exclusion criteria select patients aged 18+ with a first-time diagnosis of IS who undergo lab tests within 24 hours of admission while excluding those with multiple organ dysfunction, sensory impairments, coagulation disorders, or other serious medical conditions. Based on the National Institutes of Health Stroke Scale (NIHSS) in the United States, patients were categorized into two groups: END (n=69) and non-END (n=151). Both groups' basic demographics, medical history, and biochemical test results were compared. Influencing factors were identified using the least absolute shrinkage and selection operator (LASSO) method, and these variables were included in a multivariate logistic regression analysis to construct a nomogram for predicting END in IS patients. Model performance was evaluated using internal validation with the Bootstrap method, assessing discrimination, calibration, and clinical validity. Results: Factors such as history of diabetes, fasting plasma glucose (FBG), triglyceride (TG), homocysteine (Hcy), and C-reactive protein (CRP) were identified as single factors for early functional deterioration in IS patients (P