Hyperglycemia is a prognosis predictor of LOS and functional outcomes of patients with acute ischemic stroke measured by discharge Barthel index.

This study aimed to determine the effectiveness of gotu kola (Centella asiatica) in improving cognitive function in patients with vascular cognitive impairment (VCI). This study uses a quasi-experimental design. Subjects in this study were patients with poststroke cognitive impairment who were treated at two hospitals in Yogyakarta, Indonesia. The number of subjects was 48: 17 subjects were treated with 1000 mg/day of gotu kola extract, 17 subjects treated with 750 mg/day of gotu kola extract, and 14 subjects treated with 3 mg/day of folic acid for 6 weeks. A Montreal Cognitive Assessment-Indonesian version (MoCA-Ina) was conducted at the beginning of treatment and after 6 weeks of therapy. It was found that all trials effectively improved poststroke VCI based on MoCA-Ina scores over the course of the study. There is no significant difference in ΔMoCA-Ina (score at the 6th week of treatment − score at the beginning) mean score among the three groups, indicating that gotu kola is as effective as folic acid in improving poststroke VCI. Gotu kola was shown to be more effective than folic acid in improving memory domain. This study suggested that gotu kola extract is effective in improving cognitive function after stroke.

This study showed that the D allele in ACE I/D polymorphism is associated with worse functional outcomes. This highlights the possibility of further research to improve functional outcomes of ischaemic stroke by inhibiting the ACE system.

Objective: Patients who survive from the first stroke have risk factors to be recurrent. Based on American Heart Association/American Stroke Association and PERDOSSI (Indonesian Neurologist Association), medications which are prescribed to reduce the risk of recurrent stroke as secondary stroke prevention therapies include antiplatelet/anticoagulant as well as antihypertensive and lipid-lowering agent. Patients' adherence to the secondary stroke prevention therapies is important to reduce the recurrent stroke.Methods: This is a quantitative research and the data were collected retrospectively. The number of subjects of this study was 165 respondents. The participants were interviewed by researchers about their adherence to secondary stroke prevention by modified Morisky Adherence scale 8 (MMAS-8) questionnaire. Patients' adherence was stated as low (MMAS-8 score <6), moderate (MMAS-8 score =6-7), and high (MMAS-8 =8). This research was taken at a teaching hospital in Central Java Indonesia. Results:Of 165 participants, 48 participants (29%) were categorized to have low adherence, 43 participants (26%) had moderate adherence, and 74 participants (45%) had high adherence to secondary stroke prevention therapies. The reasons for not adhering to the medications were felt better (34.1%), forgetfulness (18.7%), boredom (16.5%), lack of family support (8.8%), lack of time (6.6%), felt worse (5.5%), concern about side effects (3.3%), preference to complementary alternative medicines (3.3%), and cost (3.3%). Conclusion:The number of patients who has high adherence to secondary stroke prevention was 45% and the most common reason why participants did not adhere to therapy was because they felt better (34.1%).

BACKGROUND: National Institutes of Health Stroke Scale (NIHSS) and Montreal Cognitive Assessment (MoCA) measure stroke severity by assessing the functional and cognitive outcome, respectively. However, they cannot be used to measure subtle evolution in clinical symptoms during the early phase. Quantitative EEG (qEEG) can detect any subtle changes in CBF and brain metabolism thus may also benefit for assessing the severity. AIM: This study aims to identify the correlation between qEEG with NIHSS and MoCA for assessing the initial stroke severity in acute ischemic stroke patients. METHODS: This was a cross-sectional study. We recruited 30 patients with first-ever acute ischemic stroke hospitalized in Dr. Sardjito General Hospital, Yogyakarta, Indonesia. We measured the NIHSS, MoCA score, and qEEG parameter during the acute phase of stroke. Correlation and regression analysis was completed to investigate the relationship between qEEG parameter with NIHSS and MoCA. RESULTS: Four acute qEEG parameter demonstrated moderate-to-high correlations with NIHSS and MoCA. DTABR had positive correlation with NIHSS (r = 0.379, p = 0.04). Meanwhile, delta-absolute power, DTABR, and DAR were negatively correlated with MoCA score (r = −0.654, p = 0.01; r = −0.397, p = 0.03; and r = −0.371, p = 0.04, respectively). After adjusted with the confounding variables, delta-absolute power was independently associated with MoCA score, but not with NIHSS (B = −2.887, 95% CI (−4.304–−1.470), p < 0.001). CONCLUSIONS: Several qEEG parameters had significant correlations with NIHSS and MoCA in acute ischemic stroke patients. The use of qEEG in acute clinical setting may provide a reliable and efficient prediction of initial stroke severity. Further cohort study with larger sample size and wide range of stroke severity is still needed.