Characteristics associated with outcome in patients with first-ever posterior fossa stroke

Predictors of devastating functional outcome despite successful basilar thrombectomy

BACKGROUND

Basilar thrombosis frequently leads to poor functional outcomes, even with good endovascular reperfusion. We studied factors associated with severe disability or death in basilar thrombectomy patients achieving revascularization.

METHODS

We retrospectively analyzed records from a health system's code stroke registry, including successful basilar thrombectomy patients from January 2017 to May 2023 who were evaluated with pretreatment computed tomography perfusion. The primary outcome was devastating functional outcome (90-day modified Rankin Scale [mRS] score 5-6). A multivariable logistic regression model was constructed to determine independent predictors of the primary outcome. The area under the receiver operator characteristics curve (AUC) was calculated for the model distinguishing good from devastating outcome.

RESULTS

Among 64 included subjects, with mean (standard deviation) age 65.6 (14.1) years and median (interquartile range) National Institutes of Health Stroke Scale (NIHSS) 18 (5.75-24.5), the primary outcome occurred in 28 of 64 (43.8%) subjects. Presenting NIHSS (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.01-1.14, p = 0.02), initial glucose (OR 0.99, 95% CI 0.97-1.00, p < 0.05), and proximal occlusion site (OR 7.38, 95% CI 1.84-29.60, p < 0.01) were independently associated with 90-day mRS 5-6. The AUC for the multivariable model distinguishing outcomes was 0.81 (95% CI 0.70-0.92).

CONCLUSION

We have identified presenting stroke severity, lower glucose, and proximal basilar occlusion as predictors of devastating neurological outcome in successful basilar thrombectomy patients. These factors may be used in medical decision making or for patient selection in future clinical trials.

Automated Final Lesion Segmentation in Posterior Circulation Acute Ischemic Stroke Using Deep Learning

Final lesion volume (FLV) is a surrogate outcome measure in anterior circulation stroke (ACS). In posterior circulation stroke (PCS), this relation is plausibly understudied due to a lack of methods that automatically quantify FLV. The applicability of deep learning approaches to PCS is limited due to its lower incidence compared to ACS. We evaluated strategies to develop a convolutional neural network (CNN) for PCS lesion segmentation by using image data from both ACS and PCS patients. We included follow-up non-contrast computed tomography scans of 1018 patients with ACS and 107 patients with PCS. To assess whether an ACS lesion segmentation generalizes to PCS, a CNN was trained on ACS data (ACS-CNN). Second, to evaluate the performance of only including PCS patients, a CNN was trained on PCS data. Third, to evaluate the performance when combining the datasets, a CNN was trained on both datasets. Finally, to evaluate the performance of transfer learning, the ACS-CNN was fine-tuned using PCS patients. The transfer learning strategy outperformed the other strategies in volume agreement with an intra-class correlation of 0.88 (95% CI: 0.83-0.92) vs. 0.55 to 0.83 and a lesion detection rate of 87% vs. 41-77 for the other strategies. Hence, transfer learning improved the FLV quantification and detection rate of PCS lesions compared to the other strategies.

Risk factors affecting the 1-year outcomes of minor ischemic stroke: results from Xi'an stroke registry study of China

BACKGROUND

The prevalence of stroke recurrence, disability, and all-cause mortality of patients with minor ischemic stroke (MIS) remains problematic. The aim of the present study was to identify risk factors associated with adverse outcomes at 1 year after MIS in the Xi'an region of China.

METHODS

This prospective cohort study included MIS patients above 18 years old with National Institutes of Health Stroke Scale (NIHSS) score ≤ 3 who were treated in any of four hospitals in Xi'an region of China between January and December 2015. The 1-year prevalence of stroke recurrence, disability, and all-cause mortality were evaluated, respectively. Multivariate logistic regression analysis was performed to assess the association between the identified risk factors and clinical outcomes.

RESULTS

In this study, 131(10.5%, 131/1252) patients were lost to follow-up at 1 year. A total of 1121 patients were included for analysis, the prevalence of stroke recurrence, disability, and all-cause mortality at 1 year after MIS were 3.4% (38/1121), 9.3% (104/1121), and 3.3% (37/1121), respectively. Multivariate logistic regression analysis identified age, current smoking, and pneumonia as independent risk factors for stroke recurrence. Age, pneumonia, and alkaline phosphatase were independent risk factors for all-cause mortality. Independent risk factors for disability were age, pneumonia, NIHSS score on admission, and leukocyte count.

CONCLUSIONS

The 1-year outcomes of MIS in Xi'an region of China were not optimistic, especially with a high prevalence of disability. The present study indicated that age and pneumonia were the common independent risk factors affecting the 1-year outcomes of MIS in Xi'an region of China.