Nomogram for predicting early neurological deterioration in patients with mild large and medium vessel occlusion stroke intended for medical management: a multicenter retrospective study.

Background: Accurately forecasting early neurological deterioration of ischemic origin (END_i) following medical management may aid in identifying candidates for thrombectomy. We aimed to develop and validate a nomogram to predict END_i in patients with mild large and medium vessel occlusion stroke intended for medical management.

Methods: Two hundred and forty-eight patients were enrolled (173 and 75 randomised into training and validation cohorts). The risk factors were identified using logistic regression analyses. A nomogram was constructed based on the risk factors identified. The discrimination, calibration, and clinical practicability of the nomogram were assessed using receiver operating characteristic curve (ROC) analysis, the Hosmer-Lemeshow test, and decision curve analysis (DCA), respectively.

Results: END_i was detected in 44 (17.7%) patients. Four predictors were identified in the training cohort and entered into the nomogram including age, symptom fluctuation characteristics, presence of core infarct, and occlusion site. ROC analysis showed that the area under the curve was 0.930 (95% CI 0.884 to 0.976) and 0.889 (95% CI 0.808 to 0.970) in the training and validation cohorts, respectively. The Hosmer-Lemeshow test yielded a mean absolute error of 0.025 and 0.038, respectively, for the two cohorts. The DCA showed that the nomogram model had superior practicality and accuracy across the majority of the threshold probabilities.

Conclusion: The proposed nomogram showed a favourable predictive performance for END_i in patients with mild large and medium vessel occlusion stroke intended for medical management. For such patients, immediate thrombectomy or at least intensive medical monitoring may be reasonable to avoid delays in rescue thrombectomy.