Modified small vessel disease score as the top predictor of stroke outcome after thrombectomy: a CT-based machine learning study

 

Why are your predicting failure to recover RATHER THAN DELIVERING RECOVERY?

Laziness? Incompetence? Or just don't care? NO leadership? NO strategy? Not my job? Not my Problem!

You're all fired! You need to create EXACT RECOVERY PROTOCOLS! 

Prediction crapola like this does nothing to get survivors recovered! Your comeuppance when you have a stroke and don't recover will be a bitter pill for you to swallow.

Modified small vessel disease score as the top predictor of stroke outcome after thrombectomy: a CT-based machine learning study

• 

  Thiago Oscar Goulart 1† *

• 

  Rui Kleber do Vale Martins-Filho 2

• 

  Millene Rodrigues Camilo 2

• 

  Daniel Giansante Abud 2

• 

  Octávio Marques Pontes-Neto 2

• 1. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States

• 2. Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil

Abstract

Background: 

Mechanical thrombectomy (MT) improves outcomes in ischemic stroke (IS) due to large vessel occlusion (LVO), but ~50% of patients fail to achieve functional independence.

Objectives: 

We investigated whether cerebral small vessel disease (cSVD), assessed by the modified Small Vessel Disease (mSVD) score and Brain Frailty Score (BFS), outperforms individual CT markers in predicting 90-day outcomes after MT.

Design: 

Prospective cohort with retrospective analysis.

Methods: 

We included 351 patients with anterior circulation LVO treated with MT. Admission CT was used to score cSVD markers (leukoaraiosis, atrophy, lacunes) and compute mSVD and BFS. Eight logistic regression models and a Random Forest algorithm were used to predict poor outcome [modified Rankin Scale (mRS) 3–6]. Model performance was evaluated using AUC-ROC and compared via DeLong tests.

Results: 

Poor outcomes were associated with older age, higher NIHSS, systolic blood pressure, glycemia, and more severe leukoaraiosis and atrophy. Severe mSVD (score = 3) independently predicted poor outcomes (OR = 3.267; CI: 1.731–6.168; p = 0.009). mSVD outperformed BFS and individual CT markers (AUC = 0.904 vs. 0.889/0.898; DeLong p < 0.05) and ranked as the top predictor in Random Forest (importance = 42.05). Treatment efficacy declined with increasing mSVD: the probability of a favorable outcome was 15.53% and poor outcome was 84.47% for mSVD = 3, compared to 89.23% and 10.77%, respectively, for mSVD = 0. A secondary model incorporating 24h NIHSS and hemorrhagic transformation improved discrimination (AUC = 0.954), but mSVD remained a key independent predictor.

Conclusions: 

In this prospective study in a middle-income country, mSVD score was the strongest predictor of post-thrombectomy outcome, outperforming BFS and isolated imaging markers. While cSVD does not contraindicate MT, it reflects reduced cerebrovascular resilience. Integrating mSVD into baseline CT evaluation may enhance risk stratification and treatment guidance.

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