Abstract
<title>Abstract</title> <p>Background and Purpose Significant inter-individual variability exists in response to dual antiplatelet therapy (DAPT) following acute ischemic stroke (AIS). This study aimed to develop and internally validate a simple, clinically applicable nomogram for predicting DAPT efficacy using routinely available parameters. Methods A retrospective cohort of 412 AIS patients receiving DAPT (aspirin plus clopidogrel/ticagrelor) was randomly divided into training (n = 288) and validation (n = 124) sets. Predictors were identified using a two-step logistic regression. A nomogram was constructed based on the final multivariate model. Model performance was evaluated by area under the receiver operating characteristic curve (AUC), calibration plots, Hosmer-Lemeshow test, and decision curve analysis (DCA). Internal validation was performed using bootstrap resampling (100 iterations). Results Five independent predictors were identified: body mass index (BMI; odds ratio [OR], 0.84; 95% confidence interval [CI], 0.76–0.93), platelet count (PLT; OR, 0.99; 95%CI, 0.99-1.00), fibrinogen level (FIB; OR, 1.07; 95%CI, 1.01–1.13), absolute lymphocyte count (ALC; OR, 0.67; 95%CI, 0.44-1.00), and total cholesterol (TC; OR, 1.42; 95%CI, 1.02–2.01). The model exhibited moderate discrimination, with an AUC of 0.75 (95%CI, 0.68–0.82) in the training set and 0.69 (95%CI, 0.58–0.80) in the validation set. Bootstrap validation yielded a mean AUC of 0.73 (95%CI, 0.71–0.75). Calibration was satisfactory (Hosmer-Lemeshow test, P > 0.05). DCA demonstrated a positive net clinical benefit across a wide range of threshold probabilities (0.09–0.81) in the training set. Conclusions This nomogram, based on five routinely available clinical and laboratory variables, offers a practical, cost-effective tool to assist clinicians in personalizing DAPT for AIS patients, particularly in resource-limited settings.</p>