Development and Validation of a Nomogram for Predicting Poor Outcome in Spontaneous Cervical Artery Dissection

建立和验证用于预测自发性颈动脉夹层不良预后的列线图

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Abstract

OBJECTIVE: This exploratory study aimed to develop a preliminary nomogram for risk assessment of poor prognosis in spontaneous cervical artery dissection (sCAD) and evaluate its statistical performance using internal validation. METHODS: We retrospectively analyzed 75 patients with sCAD (mean age 51.8 ± 14.0 years; 41 males [55%] and 34 females [45%]) diagnosed between November 2013 and April 2024. Poor prognosis was defined as imaging-confirmed acute cerebral infarction or hemorrhage (n=38); the remaining 37 patients comprised the good prognosis group. Due to the small sample size, variables with p<0.2 in univariate analysis (sex, extracranial CAD type, hypertension, hyperhomocysteinemia) were considered for multivariate modeling, though none were statistically significant predictors (all p>0.05). A multivariate logistic regression-based nomogram was constructed and internally validated using 1000 bootstrap resamples. RESULTS: The final model included the four variables above. Only non-intramural hematoma (other) CAD type showed statistical significance in the multivariate model (OR=13.41, 95% CI: 2.89-62.17, P<0.01), while sex, hypertension, and hyperhomocysteinemia did not, likely reflecting statistical instability from inadequate power. In bootstrap internal validation, the model demonstrated moderate discrimination (AUC=0.788, 95% CI: 0.686-0.891) with a Brier score of 0.185. Hosmer-Lemeshow test indicated acceptable calibration (χ(2)=8.11, P=0.23). Mean AUC across bootstrap samples was 0.763 (95% CI: 0.662-0.863), suggesting minimal overfitting within this dataset, though this does not imply generalizability. CONCLUSION: This pilot study generates the hypothesis that ultrasonographic CAD type, combined with clinical variables, may aid in predicting sCAD outcomes. However, due to the small sample size (9.5 events/variable), lack of external validation, and inclusion of non-significant predictors, this model is not ready for clinical application. Multi-center prospective validation in a cohort of at least 400 patients is required before any clinical utility can be claimed.

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