OBJECTIVE: This proposed study aims to evaluate the effectiveness of the Stroke Riskometer™ app in improving stroke awareness and stroke risk probability amongst the adult population in Malaysia.
METHODS: A non-blinded, parallel-group cluster-randomized controlled trial with a 1:1 allocation ratio will be implemented in Kelantan, Malaysia. Two groups with a sample size of 66 in each group will be recruited. The intervention group will be equipped with the Stroke Riskometer™ app and informational leaflets, while the control group will be provided with standard management, including information leaflets only. The Stroke Riskometer™ app was developed according to the self-management model of chronic diseases based on self-regulation and social cognitive theories. Data collection will be conducted at baseline and on the third week, sixth week, and sixth month follow-up via telephone interview or online questionnaire survey. The primary outcome measure is stroke risk awareness, including the domains of knowledge, perception, and intention to change. The secondary outcome measure is stroke risk probability within 5 and 10 years adjusted to each participant's socio-demographic and/or socio-economic status. An intention-to-treat approach will be used to evaluate these measures. Pearson's χ2 or independent t test will be used to examine differences between the intervention and control groups. The generalized estimating equation and the linear mixed-effects model will be employed to test the overall effectiveness of the intervention.
CONCLUSION: This study will evaluate the effect of Stroke Riskometer™ app on stroke awareness and stroke probability and briefly evaluate participant engagement to a pre-specified trial protocol. The findings from this will inform physicians and public health professionals of the benefit of mobile technology intervention and encourage more active mobile phone-based disease prevention apps.
TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT04529681.
METHODS: This study included PD patients along with their caregivers and was undertaken at the Malaysian Parkinson's Disease Association from June 2016 to November 2016. Clinical features of PD patients were assessed using the Movement Disorder Society revised Unified Parkinson Disease Rating Scale; the Hoehn and Yahr stage and the Schwab and England Activities of Daily Living Scale were used to assess the severity and the ability of PD patients respectively. QoL of PD patients was measured using the Parkinson's Disease Questionnaire-39 (PDQ-39). The revised version of the Zarit Burden Interview assessed caregiver burden.
RESULTS: At least one of the clinical features affected PD patients' QoL, and at least one of the QoL domains affected the caregivers' burden. Clinical features "saliva and drooling" and "dyskinesia" explained 29% of variance in QoL of PD patients. The QoL domains "stigma," along with "emotional well-being" explained 48.6% of variance in caregivers' burden.
CONCLUSIONS: The clinical features "saliva and drooling" and "dyskinesia" impacted the QoL of PD patients, and the QoL domains "stigma" and "emotional well-being" of PD patients impacted their caregivers' burden.
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.
AIMS: We explored if the association is explained by shared risk factors or is independent and whether there are regional or stroke subtype variations.
METHODS: INTERSTROKE is a case-control study and the largest international study of risk factors for first acute stroke, completed in 27 countries. We included individuals with available serum creatinine values and calculated estimated glomerular filtration rate (eGFR). Renal impairment was defined as eGFR <60 mL/min/1.73 m2. Multivariable conditional logistic regression was used to determine the association of renal function with stroke.
RESULTS: Of 21,127 participants, 41.0% were female, the mean age was 62.3 ± 13.4 years, and the mean eGFR was 79.9 ± 23.5 mL/min/1.73 m2. The prevalence of renal impairment was higher in cases (22.9% vs. 17.7%, p < 0.001) and differed by region (p < 0.001). After adjustment, lower eGFR was associated with increased odds of stroke. Renal impairment was associated with increased odds of all stroke (OR 1.35; 95% CI: 1.24-1.47), with higher odds for intracerebral hemorrhage (OR 1.60; 95% CI: 1.35-1.89) than ischemic stroke (OR 1.29; 95% CI: 1.17-1.42) (pinteraction 0.12). The largest magnitudes of association were seen in younger participants and those living in Africa, South Asia, or South America (pinteraction < 0.001 for all stroke). Renal impairment was also associated with poorer clinical outcome (RRR 2.97; 95% CI: 2.50-3.54 for death within 1 month).
CONCLUSION: Renal impairment is an important risk factor for stroke, particularly in younger patients, and is associated with more severe stroke and worse outcomes.
METHODS: The subjects of this study included 202 elderly (≥65 years) residents of 17 aged care homes in suburban peninsular Malaysia. Frailty was measured using the Groningen Frailty Indicator (GFI) score and independence in daily living was measured as KATZ activity of daily living score. Medication appropriateness was assessed using the Medication Appropriateness Index (MAI) and 2015 Beers' criteria for Potentially Inappropriate Medication (PIM).
RESULTS: CNS medications constituted about 16% of the total, with an average of 0.8 ± 1.1 medications per resident, which reduced to 0.5 ± 0.8 medications after 3 months. Frailty (154/202) and polypharmacy (90/202) were highly prevalent in study subjects. Subjects on CNS medications had significantly higher GFI score (7.1 vs. 5.9; p = 0.031), polypharmacy (57.8 vs. 35.3%; p = 0.002), number of PIMs (0.9 vs. 0.2; p = 0.001), and mean summed MAI score (3.6 vs. 2.6; p = 0.015) than subjects not on CNS medications. Medication number was also significantly correlated with GFI (r = 0.194; p = 0.006) and KATZ (r = 0.141; p = 0.046) scores.
CONCLUSION: Frailty and polypharmacy were highly prevalent among aged care home subjects taking CNS medications. These findings support the notion that periodic regular medication review should improve the overall use of medications in elderly patients.
METHODS: The study protocol was registered with PROSPERO (CRD42022325505). MEDLINE (PubMed), Embase, and the Cochrane Library were used as information sources. Eligible studies included original articles of cohort studies, case-control studies, cross-sectional studies, and case series with ≥5 subjects that reported the prevalence and type of neurological manifestations, with a minimum follow-up of 3 months after the acute phase of COVID-19 disease. Two independent reviewers screened studies from January 1, 2020, to June 16, 2022. The following manifestations were assessed: neuromuscular disorders, encephalopathy/altered mental status/delirium, movement disorders, dysautonomia, cerebrovascular disorders, cognitive impairment/dementia, sleep disorders, seizures, syncope/transient loss of consciousness, fatigue, gait disturbances, anosmia/hyposmia, and headache. The pooled prevalence and their 95% confidence intervals were calculated at the six pre-specified times.
RESULTS: 126 of 6,565 screened studies fulfilled the eligibility criteria, accounting for 1,542,300 subjects with COVID-19 disease. Of these, four studies only reported data on neurological conditions other than the 13 selected. The neurological disorders with the highest pooled prevalence estimates (per 100 subjects) during the acute phase of COVID-19 were anosmia/hyposmia, fatigue, headache, encephalopathy, cognitive impairment, and cerebrovascular disease. At 3-month follow-up, the pooled prevalence of fatigue, cognitive impairment, and sleep disorders was still 20% and higher. At six- and 9-month follow-up, there was a tendency for fatigue, cognitive impairment, sleep disorders, anosmia/hyposmia, and headache to further increase in prevalence. At 12-month follow-up, prevalence estimates decreased but remained high for some disorders, such as fatigue and anosmia/hyposmia. Other neurological disorders had a more fluctuating occurrence.
DISCUSSION: Neurological manifestations were prevalent during the acute phase of COVID-19 and over the 1-year follow-up period, with the highest overall prevalence estimates for fatigue, cognitive impairment, sleep disorders, anosmia/hyposmia, and headache. There was a downward trend over time, suggesting that neurological manifestations in the early post-COVID-19 phase may be long-lasting but not permanent. However, especially for the 12-month follow-up time point, more robust data are needed to confirm this trend.
METHODS: Through literature review, we obtained data on the relative risk of dementia with each condition and estimated relative risks by age using a Bayesian meta-regression tool. We then calculated population attributable fractions (PAFs), or the proportion of dementia attributable to each condition, using the estimates of relative risk and prevalence estimates for each condition from the Global Burden of Disease Study 2019. Finally, we multiplied these estimates by dementia prevalence to calculate the number of dementia cases attributable to each condition.
FINDINGS: For each clinical condition, the relative risk of dementia decreased with age. Relative risks were highest for Down syndrome, followed by Parkinson's disease, stroke, and TBI. However, due to the high prevalence of stroke, the PAF for dementia due to stroke was highest. Together, Down syndrome, Parkinson's disease, stroke, and TBI explained 10.0% (95% UI: 6.0-16.5) of the global prevalence of dementia.
INTERPRETATION: Ten percent of dementia prevalence globally could be explained by Down syndrome, Parkinson's disease, stroke, and TBI. The quantification of the proportion of dementia attributable to these 4 conditions constitutes a small contribution to our overall understanding of what causes dementia. However, epidemiological research into modifiable risk factors as well as basic science research focused on elucidating intervention approaches to prevent or delay the neuropathological changes that commonly characterize dementia will be critically important in future efforts to prevent and treat disease.