Uncertainty-aware deep learning for trustworthy prediction of long-term outcome after endovascular thrombectomy

Abstract Acute ischemic stroke (AIS) is a leading global cause of mortality and morbidity. Improving long-term outcome predictions after thrombectomy can enhance treatment quality by supporting clinical decision-making. With the advent of interpretable deep learning methods in recent years, it is now possible to develop trustworthy, high-performing prediction models. This study introduces an uncertainty-aware, graph deep learning model that predicts endovascular thrombectomy outcomes using clinical features and imaging biomarkers. The model targets long-term functional outcomes, defined by the three-month modified Rankin Score (mRS), and mortality rates. A sample of 220 AIS patients in the anterior circulation who underwent endovascular thrombectomy (EVT) was included, with 81 (37%) demonstrating good outcomes (mRS $$\le$$ ≤ 2). The performance of the different algorithms evaluated was comparable, with the maximum validation under the curve (AUC) reaching 0.87 using graph convolutional networks (GCN) for mRS prediction and 0.86 using fully connected networks (FCN) for mortality prediction. Moderate performance was obtained at admission (AUC of 0.76 using GCN), which improved to 0.84 post-thrombectomy and to 0.89 a day after stroke. Reliable uncertainty prediction of the model could be demonstrated

Early versus late start of direct oral anticoagulants after acute ischaemic stroke linked to atrial fibrillation: an observational study and individual patient data pooled analysis

Objective The optimal timing to start direct oral anticoagulants (DOACs) after an acute ischaemic stroke (AIS) related to atrial fibrillation (AF) remains unclear. We aimed to compare early (<= 5 days of AIS) versus late (>5 days of AIS) DOAC-start. Methods This is an individual patient data pooled analysis of eight prospective European and Japanese cohort studies. We included patients with AIS related to non-valvular AF where a DOAC was started within 30 days. Primary endpoints were 30-day rates of recurrent AIS and ICH. Results A total of 2550 patients were included. DOACs were started early in 1362 (53%) patients, late in 1188 (47%). During 212 patient-years, 37 patients had a recurrent AIS (1.5%), 16 (43%) before a DOAC was started; 6 patients (0.2%) had an ICH, all after DOAC-start. In the early DOAC-start group, 23 patients (1.7%) suffered from a recurrent AIS, while 2 patients (0.1%) had an ICH. In the late DOAC-start group, 14 patients (1.2%) suffered from a recurrent AIS; 4 patients (0.3%) suffered from ICH. In the propensity score-adjusted comparison of late versus early DOAC-start groups, there was no statistically significant difference in the hazard of recurrent AIS (aHR=1.2, 95% CI 0.5 to 2.9, p=0.69), ICH (aHR=6.0, 95% CI 0.6 to 56.3, p=0.12) or any stroke. Conclusions Our results do not corroborate concerns that an early DOAC-start might excessively increase the risk of ICH. The sevenfold higher risk of recurrent AIS than ICH suggests that an early DOAC-start might be reasonable, supporting enrolment into randomised trials comparing an early versus late DOAC-start

Mechanical thrombectomy for acute ischemic stroke in COVID-19 patients: multicenter experience in 111 cases

Background Data on the frequency and outcome of mechanical thrombectomy (MT) for large vessel occlusion (LVO) in patients with COVID-19 is limited. Addressing this subject, we report our multicenter experience. Methods A retrospective cohort study was performed of consecutive acute stroke patients with COVID-19 infection treated with MT at 26 tertiary care centers between January 2020 and November 2021. Baseline demographics, angiographic outcome and clinical outcome evaluated by the modified Rankin Scale (mRS) at discharge and 90 days were noted. Results We identified 111 out of 11 365 (1%) patients with acute or subsided COVID-19 infection who underwent MT due to LVO. Cardioembolic events were the most common etiology for LVO (38.7%). Median baseline National Institutes of Health Stroke Scale score and Alberta Stroke Program Early CT Score were 16 (IQR 11.5-20) and 9 (IQR 7-10), respectively. Successful reperfusion (mTICI >= 2b) was achieved in 97/111 (87.4%) patients and 46/111 (41.4%) patients were reperfused completely. The procedure-related complication rate was 12.6% (14/111). Functional independence was achieved in 20/108 (18.5%) patients at discharge and 14/66 (21.2%) at 90 days follow-up. The in-hospital mortality rate was 30.6% (33/108). In the subgroup analysis, patients with severe acute COVID-19 infection requiring intubation had a mortality rate twice as high as patients with mild or moderate acute COVID-19 infection. Acute respiratory failure requiring ventilation and time interval from symptom onset to groin puncture were independent predictors for an unfavorable outcome in a logistic regression analysis. Conclusion Our study showed a poor clinical outcome and high mortality, especially in patients with severe acute COVID-19 infection undergoing MT due to LVO