E-186 Assessing congruency of first pass effect on outcomes in mechanical thrombectomy for large vessel occlusions via unsupervised machine learning

This study was approved by the local institutional review board (IRB). Clustered outcomes to formulate clusters included the number of passes, the final reperfusion obtained, the discharge NIHSS, and complications. FPE was defined as TICI 2C or 3 reperfusions on the first pass. Uniform manifold approximations and projections (UMAP) and K-means unsupervised clustering were done to identify outcome clusters. Logistic regression with and without interaction coefficients was used to determine associated factors with cluster membership or FPE. P-values less than 0.05 were considered significant.Results287 consecutive patients were identified, of which 187 were used in the final analysis due to missing outcomes data. The average age was 70 years (sD = 15.14), with 81.8% of patients with MCA occlusion. Three outcome clusters were identified in the analysis. Cluster 2 had the greatest congruency with FPE (p < 0.001) and was also associated with poor outcomes. Patients in Cluster 2 were more likely to have ICA occlusions and were older (p = 0.043, 0.001, respectively). Predictors of FPE were analyzed using cluster membership and adjusted for aneurysm properties. Adjusted for other factors, cluster 2 membership was significantly associated with achieving FPE in our cohort (OR = 5.419 (95% CI: 2.349 - 13.464), p < 0.001). Next, the predictive value of FPE and cluster membership was compared against Discharge NIHSS. FPE was inversely associated with discharge NIHSS (B (SE) = -4.497...
Source: Journal of NeuroInterventional Surgery - Category: Neurosurgery Authors: Tags: SNIS 20th annual meeting electronic poster abstracts Source Type: research