Editorial: Post-stroke complications: mechanisms, diagnosis, and therapies

Hybrid Ensemble Deep Learning Model for Advancing Ischemic Brain Stroke Detection and Classification in Clinical Application

Ischemic brain strokes are severe medical conditions that occur due to blockages in the brain's blood flow, often caused by blood clots or artery blockages. Early detection is crucial for effective treatment. This study aims to improve the detection and classification of ischemic brain strokes in clinical settings by introducing a new approach that integrates the stroke precision enhancement, ensemble deep learning, and intelligent lesion detection and segmentation models. The proposed hybrid model was trained and tested using a dataset of 10,000 computed tomography scans. A 25-fold cross-validation technique was employed, while the model's performance was evaluated using accuracy, precision, recall, and F1 score. The findings indicate significant improvements in accuracy for different stages of stroke images when enhanced using the SPEM model with contrast-limited adaptive histogram equalization set to 4. Specifically, accuracy showed significant improvement (from 0.876 to 0.933) for hyper-acute stroke images; from 0.881 to 0.948 for acute stroke images, from 0.927 to 0.974 for sub-acute stroke images, and from 0.928 to 0.982 for chronic stroke images. Thus, the study shows significant promise for the detection and classification of ischemic brain strokes. Further research is needed to validate its performance on larger datasets and enhance its integration into clinical settings.

The impact of post-stroke fatigue on inpatient rehabilitation outcomes: An observational study

BACKGROUND

Post-stroke fatigue is a typical complication following stroke. However, existing research primarily focused on its underlying mechanisms, and its impact on rehabilitation outcomes has yet to be uncovered.

OBJECTIVE

This study aims to explore the impact of post-stroke fatigue on rehabilitation outcomes during hospitalization.

METHOD

This was a prospective multicenter observational study including 46 stroke patients receiving comprehensive rehabilitation treatment. Patients' basic information was recorded upon admission and patients' functional independence was assessed with Functional Independence Measure (FIM) both upon admission and discharge. One week after rehabilitation treatment, fatigue, positivity in daily activity, attention, and memory were assessed. Serum biochemical indicators and levels of C-reactive protein (CRP) were assessed weekly following admission. The pain scores were assessed during the first week of hospitalization to calculate the average. Correlation analysis, linear regression and propensity score matching (PSM) were used to analyze the impact of fatigue on FIM scores at discharge and length of hospital stay.

RESULT

The proportion of patients with low fatigue was 39.13% and significant improvement was revealed in FIM scores upon admissions and discharge [(50.67±18.61) vs. (75.13±21.04), P<0.05]. Positivity in daily activity, attention, and age are factors that influence post-stroke fatigue. After PSM, low-fatigue group (Fatigue score< 3) showed significant higher motor function independence at discharge [(54.39 ± 15.42) vs. (41.89 ± 14.90), P<0.05] and shorter hospital stay [(28.54±9.13)d vs. (37.32 ± 9.81)d, P<0.05] than high-fatigue group. There was a significant difference (P<0.05) in level of CRP between the first inpatient week and the third week, with declining trend.

CONCLUSION

Post-stroke fatigue can affect the rehabilitation outcomes regarding motor function independence and length of hospital stay.

The efficacy and safety of interleukin-1 receptor antagonist in stroke patients: A systematic review

Stroke is the leading cause of disability worldwide, yet there is currently no effective treatment available to mitigate its negative consequences. Pro-inflammatory cytokines, such as interleukin-1 (IL-1), are known to play a crucial role in exacerbating the aftermath of stroke. Thus, it is hypothesized that blocking inflammation and administering anti-inflammatory drugs at an optimal time and dosage may improve the long-term quality of life for stroke patients. This systematic review examines the effectiveness and safety of IL-1 receptor antagonist (IL-1Ra), commercially known as "anakinra," in clinical studies involving the treatment of stroke patients. A comprehensive literature search was conducted until October 2023 to identify relevant studies. The search yielded 1403 articles, out of which 598 were removed due to duplication. After a thorough review of 805 titles and abstracts, 797 articles were further excluded, resulting in 8 studies being included in this systematic review. The findings from all the included studies demonstrate that IL-1Ra is safe for use in acute ischemic and hemorrhagic stroke patients, with no significant adverse events reported. Additionally, biomarkers, clinical assessments, serious adverse events (AEs), and non-serious AEs consistently showed more favorable outcomes in IL-1Ra receiving patients. Stroke elevates the levels of several inflammatory cytokines, however, administration of IL-1RA directly or indirectly modulates these markers and improves some clinical outcomes, suggesting a potential therapeutic benefit of this intervention.