OBJECTIVE: This study was carried out to identify important parameters in designing tasks that efficiently assess hand function of stroke patients and to quantify potential benefits of robotic assessment modules to predict the conventional assessment score with iRest.
METHODS: Twelve predictive variables were explored, relating to movement time, velocity, strategy, accuracy and smoothness from three robotic assessment modules which are Draw I, Draw Diamond and Draw Circle. Regression models using up to four predictors were developed to describe the MAS.
RESULTS: Results show that the time given should be not too long and it would affect the trajectory error. Besides, result also shows that it is possible to use iRest in predicting MAS score.
CONCLUSION: There is a potential of using iRest, a non-motorized device in predicting MAS score.
METHODS: This is a cross-sectional study of adults aged 18 and above attending a blood pressure screening program in community in conjunction with May Measurement Month 2017 in Malaysia. A structured self-administered questionnaire was given to the participants who gave verbal consent. Data analysis was done using SPSS v. 23 and multiple logistic regression was used to identify the determinants of knowledge on actions to be taken during stroke and recognition of stroke symptoms.
RESULTS: Out of 4096 respondents, 82.9-92.1% of them able to recognise the common stroke symptoms. and 74.2% of the study respondents will go to hospital within 4.5 h of stroke onset. According to binomial logistic regression analyses, adults aged 45 years old and above (OR 1.39 95%CI 1.01-1.92), being Malay (OR 1.74, 95% CI 1.27-2.40), being non-smokers (OR = 2.491, 95% CI: 1.64-3.78), hypertensives (OR: 1.57, 95% CI: 1.02-2.42)and diabetics (OR: 2.54, 95% CI:1.38-4.69) are determinants of right actions to be taken during stroke. Meanwhile, respondents aged 45 years old and older (OR = 1.68, 95% CI: 1.39-2.03), being Malay (OR = 1.49, 95% CI: 1.24-1.79), hypertensive (OR = 1.32, 95% CI: 1.04-1.66) and those who had a previous history of stroke (OR = 2.25, 95% CI: 1.01-5.00) are determinants of good recognition of stroke symptoms.
CONCLUSIONS: The overall knowledge of stroke in our study population was good. Older age, being Malay, non-smokers, hypertensives and diabetics are determinants of right actions to be taken during stroke. Meanwhile, older age, being Malay, hypertensive and those who had a previous history of stroke are determinants of good recognition of stroke symptoms.
OBJECTIVE: This study aimed to establish the interrater reliability between multiple telephone interviewers when assessing long-term stroke outcomes.
METHODS: Patients alive at discharge selected in a retrospective cohort stroke project were recruited in this study. Their contact numbers were obtained from the medical record unit. The patients and/or proxies were interviewed based on a standardized script in Malay or English. Stroke outcomes assessed were modified Rankin Scale (mRS) and Barthel Index (BI) at 1-year post discharge. Fully crossed design was applied and 3 assessors collected the data simultaneously. Data was analysed using the software R version 3.4.4.
RESULTS: Out of 207 subjects recruited, 132 stroke survivors at the time of interview were analysed. We found a significant excellent interrater reliability between telephone interviewers assessing BI, with intraclass correlation coefficient at 0.996 (95% CI 0.995-0.997). Whereas substantial agreement between the telephone interviewers was revealed in assessing mRS, with Fleiss', Conger's and Light's Kappa statistics reporting 0.719 and the Nelson's model-based κm kappa statistic reporting 0.689 (95% CI 0.667-0.711).
CONCLUSION: It is reliable to get multiple raters in assessing mRS and BI using the telephone system. It is worthwhile to make use of a telephone interview to update clinicians on their acute clinical management towards long-term stroke prognosis.