Background Posterior circulation ischemic stroke (PCS) accounts for up to 25% of all ischemic strokes but remains frequently under-recognized due to atypical symptoms and poor representation in conventional stroke scales. Early diagnosis is critical yet challenging. This study aimed to derive a pragmatic clinical scoring tool, the PCS-SCORE, to identify patients at high risk of PCS based solely on bedside features. Methods We retrospectively analyzed 5163 patients from a prospective stroke registry, including 1571 with -confirmed PCS. Key predictors were identified through multivariable logistic regression and lasso modeling. Variables were weighted according to regression coefficients and clinical relevance. The final PCS-SCORE (0-9 points) included: diabetes (1 point), hypertension (1), male sex (1), double/blurred vision (2), vertigo with vomiting (2), and incoordination (2). Results At a score threshold >3, the PCS-SCORE achieved an area under the curve (AUC) of 0.76, with 87.9% specificity and 43.4% sensitivity. Raising the threshold to >4 increased specificity to 94.4% (sensitivity 27.9%). Higher scores corresponded with progressively increased likelihood of PCS, enabling confident identification of high-risk patients. Conclusion The PCS-SCORE is a simple, highly specific bedside tool for early detection of posterior circulation strokes. Its rule-in strength makes it especially useful in prehospital settings, resource-limited environments, and crowded emergency departments. Prospective validation is ongoing.
Imam et al. (Thu,) studied this question.