ABSTRACT
BACKGROUND: Predicting stroke recurrence for individual patients is difficult, but individualized prediction may improve stroke survivors' engagement in self-care. We developed PRERISK: a statistical and machine learning classifier to predict individual risk of stroke recurrence. METHODS: We analyzed clinical and socioeconomic data from a prospectively collected public health care-based data set of 41â 975 patients admitted with stroke diagnosis in 88 public health centers over 6 years (2014-2020) in Catalonia-Spain. A new stroke diagnosis at least 24 hours after the index event was considered as a recurrent stroke, which was considered as our outcome of interest. We trained several supervised machine learning models to provide individualized risk over time and compared them with a Cox regression model. Models were trained to predict early, late, and long-term recurrence risk, within 90, 91 to 365, and >365 days, respectively. C statistics and area under the receiver operating characteristic curve were used to assess the accuracy of the models. RESULTS: Overall, 16.21% (5932 of 36â 114) of patients had stroke recurrence during a median follow-up of 2.69 years. The most powerful predictors of stroke recurrence were time from previous stroke, Barthel Index, atrial fibrillation, dyslipidemia, age, diabetes, and sex, which were used to create a simplified model with similar performance, together with modifiable vascular risk factors (glycemia, body mass index, high blood pressure, cholesterol, tobacco dependence, and alcohol abuse). The areas under the receiver operating characteristic curve were 0.76 (95% CI, 0.74-0.77), 0.60 (95% CI, 0.58-0.61), and 0.71 (95% CI, 0.69-0.72) for early, late, and long-term recurrence risk, respectively. The areas under the receiver operating characteristic curve of the Cox risk class probability were 0.73 (95% CI, 0.72-0.75), 0.59 (95% CI, 0.57-0.61), and 0.67 (95% CI, 0.66-0.70); machine learning approaches (random forest and AdaBoost) showed statistically significant improvement (P<0.05) over the Cox model for the 3 recurrence time periods. Stroke recurrence curves can be simulated for each patient under different degrees of control of modifiable factors. CONCLUSIONS: PRERISK is a novel approach that provides a personalized and fairly accurate risk prediction of stroke recurrence over time. The model has the potential to incorporate dynamic control of risk factors.
ABSTRACT
OBJECTIVE: The optimal technique for treating tandem lesions (TLs) with endovascular therapy is debatable. The authors evaluated the functional, safety, and procedural outcomes of different approaches in a multicenter study. METHODS: Anterior circulation TL patients treated from January 2015 to December 2020 were divided on the basis of antegrade versus retrograde approach and included. The evaluated outcomes were favorable modified Rankin Scale (mRS) score (mRS score 0-2) at 3 months, ordinal shift in mRS score, successful recanalization, excellent recanalization, first-pass effect (FPE), time from groin puncture to successful recanalization, symptomatic intracranial hemorrhage (sICH), and 90-day mortality. RESULTS: Among 691 patients treated at 16 centers, 286 patients (174 antegrade and 112 retrograde approach patients) with acute stenting were included in the final analysis. There were no significant differences in mRS score 0-2 at 90 days (52.2% vs 50.0%, adjusted odds ratio [aOR] 0.83, 95% CI 0.42-1.56, p = 0.54), favorable shift in 90-day mRS score (aOR 1.03, 95% CI 0.66-1.29, p = 0.11), sICH (4.0% vs 4.5%, aOR 0.64, 95% CI 0.24-1.51, p = 0.45), successful recanalization (89.4% vs 93%, aOR 0.49, 95% CI 0.19-1.28, p = 0.19), excellent recanalization (51.4% vs 58.9%, aOR 0.59, 95% CI 0.40-1.07, p = 0.09), FPE (58.3% vs 69.7%, aOR 0.62, 95% CI 0.44-1.15, p = 0.21), and mortality at 90 days (16.6% vs 14.0%, aOR 0.94, 95% CI 0.35-2.44, p = 0.81) between the groups. The median (interquartile range) groin puncture to recanalization time was significantly longer in the antegrade group (59 [43-90] minutes vs 49 [35-73] minutes, p = 0.036). CONCLUSIONS: The retrograde approach was associated with faster recanalization times with a similar functional and safety profile when compared with the antegrade approach in patients with acute ischemic stroke with TL.
