Modelling of risk factors, case-fatalities, survival and functional health status for stroke in Kelantan, Malaysia

Stroke is an important public health problem worldwide. It is a non-communicable disease of increasing importance in the ageing population. There are four major types of stroke: a) ischaemic stroke, b) primary intracerebral haemorrhage, c) subarachnoid haemorrhage and d) undetermined stroke (no computed tomography [CT], magnetic resonance imaging [MRI], autopsy or cerebral angiography). The risk factors and fatalities for stroke vary worldwide and stroke accounts for about 9.7% of all deaths worldwide. Unfortunately, most stroke deaths occur in the less developed countries, where stroke research is scanty. Patients who survive stroke will have a wide range of functional limitations that affect their daily activities. To date, only few reliable data are available for identifying the risk factors and understanding the stroke fatalities in the low- and middle-income countries. The effect of stroke on daily activities is also understudied. Measuring the effect of stroke on daily activities is important to evaluate the recovery process. Understanding the factors affecting daily activities post-stroke helps identify areas where intervention may benefit stroke survivors the most. In this thesis, I have worked on the questions that will improve my knowledge and understanding of the natural history of stroke in the state of Kelantan, Malaysia. In this study, we posed questions to subjects from the population of interest to reflect our results across the greater Kelantan population to develop a model of risk factors for stroke, models of case-fatalities and survival to compare the characteristics and outcomes of two main types of stroke, i.e. ischaemic stroke and haemorrhagic stroke, and lastly to assess the longitudinal change in functional health status using the Barthel Index post-stroke. This thesis includes four draft papers, in which several modelling data collection and data analysis strategies were applied to four datasets: one was provided by the hospitals, two were extracted by us and the final one was based on personal interviews with stroke survivors. The first draft paper is based on an observational study using data from the records offices of two major hospitals in Kelantan. In this paper, I analysed and modelled the risk factors for stroke using a case–control study design. This dataset contained individual-level variables (patient variables from hospitals) and area-level variables supplied by the Department of Statistics, Malaysia, and we utilised logistic regression to model the risk factors for stroke. In the results, we showed the non-linear relationship between age and odds for stroke and the interaction of age with sex in the model. In the second draft paper, we explored the important prognostic factors for in-hospital stroke fatalities. Using Cox proportional hazard regression, we found that the only two independent prognostic factors for stroke fatality in the hospitals were: a) stroke subtype and b) age. To further investigate the different prognostic effect of stroke subtype on admission and on fatality, we recruited consecutive in-hospital stroke patients. In the analysis, we performed Cox proportional hazard regression to quantify the odds of stroke fatality for: a) ischaemic stroke and b) haemorrhagic stroke. In this third draft paper, we showed the prognostic effect of stroke subtype on stroke fatality. In the fourth draft paper, we recruited stroke patients and interviewed them on three occasions. In this longitudinal assessment, we assessed the functional health status of stroke patients until 3 months after hospital discharge. I conducted all interviews and assessed the functional outcome using the well-known Barthel Index. Considering the longitudinal format of the data, we used the linear mixed effect model to model the rate of change of the Barthel Index at the three measurement occasions. We have identified several limitations in this PhD project and have taken several measures to minimize the biases caused by those limitations. The limitations include the need for us to do handsearching for data abstraction, potential informative censoring due to our study design and short follow-up times, limited generalizability of results, small sample sizes, missing observations, missing important variables (to be modelled as covariates), absence of residential coordinates and using data on arrival to Emergency department (no pre-arrival data). If the censoring mechanism provides significant information with time (T), numerical estimates from Kaplan-Meier and Cox proportional hazard regression are biased. The new knowledge stemming from the stroke modelling and outcome assessment developed and analysed in this thesis could help improve our understanding of stroke in Kelantan. The thesis will also improve our understanding and knowledge of the natural history of the disease, i.e. the progression from risk factors to outcome (fatality or functional residuals) after stroke. In conclusion, our data and the four draft papers written based on this PhD project have added new stroke data and knowledge on the progression of stroke, which is understated in the Malaysian and Asian population in general and in Kelantan specifically

Diagnostic accuracy of machine learning models on mammography in breast cancer classification:a meta-analysis

In this meta-analysis, we aimed to estimate the diagnostic accuracy of machine learning models on digital mammograms and tomosynthesis in breast cancer classification and to assess the factors affecting its diagnostic accuracy. We searched for related studies in Web of Science, Scopus, PubMed, Google Scholar and Embase. The studies were screened in two stages to exclude the unrelated studies and duplicates. Finally, 36 studies containing 68 machine learning models were included in this meta-analysis. The area under the curve (AUC), hierarchical summary receiver operating characteristics (HSROC) curve, pooled sensitivity and pooled specificity were estimated using a bivariate Reitsma model. Overall AUC, pooled sensitivity and pooled specificity were 0.90 (95% CI: 0.85–0.90), 0.83 (95% CI: 0.78–0.87) and 0.84 (95% CI: 0.81–0.87), respectively. Additionally, the three significant covariates identified in this study were country (p = 0.003), source (p = 0.002) and classifier (p = 0.016). The type of data covariate was not statistically significant (p = 0.121). Additionally, Deeks’ linear regression test indicated that there exists a publication bias in the included studies (p = 0.002). Thus, the results should be interpreted with caution

Validation of the Malay Version of Auditory Verbal Learning Test (MVAVLT) Among Schizophrenia Patients in Hospital Universiti Sains Malaysia (HUSM), Malaysia

Objective: Many studies have emphasized the significance of verbal memory for the functional outcome in schizophrenia. A preserved capability to encode and recall verbal information is essential for the long-term efficacy of psychoeducational programs and other psychological intervention to ensure the successful transfer of newly acquired skills or knowledge into everyday life. Aims of this study aimed to validate the MVALT among schizophrenia patients in HUSM. Methods: The subjects were 15 schizophrenia patients conveniently selected from the patients that attended follow up at the psychiatry clinic in HUSM or inpatients who have been admitted during the study period and 15 healthy control subjects as a comparison. Reliability and validity of the MVAVLT were analyzed. Results: The validation study showed that the Malay version Auditory Verbal Learning Test (MVAVLT) had a good validity (factor analysis 0.66 to 0.98) and test-retest reliability (pearson correlation ranged from 0.24 to 0.84) and has been shown to be sensitive in discriminating between normal and schizophrenia patients. In line with the previous research, the schizophrenia patients performed significantly worse than healthy control in all indexes measured in MVAVLT. Conclusion: The screening of deficits in verbal learning and memory among the schizophrenia patients is important, for early detection and treatment since it can be helpful for clinicians and psychologists in their counseling sessions. Subsequently, it helps patients to reduce such cognitive difficulties and their impact by using specific rehabilitation with the usage of newer antipsychotic agents

Prevalence of undiagnosed metabolic syndrome using three different definitions and identifying associated risk factors among apparently healthy adults in Karachi, Pakistan:a cross-sectional survey in the year 2022

Objective: To determine the prevalence and associated risk factors of undiagnosed metabolic syndrome (MetS) using three different definitions among apparently healthy adults of Karachi, Pakistan. Methods: This community-based cross-sectional survey was conducted in Karachi, Pakistan, from January 2022 to August 2022. A total of 1065 healthy individuals aged 25–80 years of any gender were consecutively included. MetS was assessed using the National Cholesterol Education Program for Adult Treatment Panel (NCEP-ATP) III guidelines, International Diabetes Federation (IDF), and modified NCEP-ATP III. Results: The prevalence of MetS was highest with the modified NCEP-ATP III definition at 33.9% (95% CI: 31–36), followed by the IDF definition at 32.2% (95% CI: 29–35). In contrast, the prevalence was lower at 22.4% (95% CI: 19–25) when using the NCEP ATP III definition. The risk of MetS significantly increases with higher BMI, as defined by the IDF criteria (adjusted OR [ORadj] 1.13, 95% CI 1.09–2.43), NCEP-ATP III criteria (ORadj 1.15, 95% CI 1.11–1.19), and modified NCEP-ATP III criteria (ORadj 1.16, 95% CI 1.12–1.20). Current smokers had significantly higher odds of MetS according to the IDF (ORadj 2.72, 95% CI 1.84–4.03), NCEP-ATP III (ORadj 3.93, 95% CI 2.55–6.06), and modified NCEP-ATP III (ORadj 0.62, 95% CI 0.43–0.88). Areca nut use was associated with higher odds of MetS according to both IDF (ORadj 1.71, 95% CI 1.19–2.47) and modified NCEP-ATP III criteria (ORadj 1.58, 95% CI 1.10–2.72). Furthermore, low physical activity had significantly higher odds of MetS according to the NCEP-ATP III (ORadj 1.36, 95% CI 1.01–1.84) and modified NCEP-ATP III criteria (ORadj 1.56, 95% CI 1.08–2.26). Conclusion: One-third of the healthy individuals were diagnosed with MetS based on IDF, NCEP-ATP III, and modified NCEP-ATP III criteria. A higher BMI, current smoking, areca nut use, and low physical activity were significant factors

Bibliometric analysis of global research activity on premature mortality

Premature mortality is defined as death that occurs before the average age of death for a particular population. Although premature mortality is a public health problem globally, the literature indicates no bibliometric studies that have made a holistic evaluation of the publications on this issue. This study aims to explore the characteristics of the publications on premature mortality in terms of the number of publications, citations, countries, collaboration, and the author’s productivity and to further identify the trending keyword and relevant research topics. All the articles related to premature mortality data were retrieved from the Web of Science (WOS) database using the search terms “premature death,” “premature mortality,” or “years of life loss.” The retrieved articles were downloaded in a BibTeX format file. A Bibliometrix package from R software was used to perform bibliometric analyses. A total of 1060 original research articles and reviews have been published since 1971, with a total of 5499 contributing authors. The number of publications has increased substantially in the past decade. The annual percentage growth rate of publications is 5.08%. The United States is the leading country in this area of research with the highest number of publications (n = 280), the highest total citation (17,378), and the most activity in collaboration. Our thematic map suggests that the cluster for cardiovascular disease became the main research domain in this field, while the cluster for air pollution is an important topic for future research. Additionally, neurodegeneration is another cluster of research that should be developed further and connected with premature mortality. These bibliometric findings hopefully will help scholars better understand the global overview of premature mortality and provide information for potential collaborators, with the information promising attractive areas for future research

A critical appraisal of Covid-19 in Malaysia and beyond

When the first report of COVID-19 appeared in December 2019 from Wuhan, China, the world unknowingly perceived this as another flu-like illness. Many were surprised at the extreme steps that China had subsequently taken to seal Wuhan from the rest of the world. However, by February 2020, the SARS-CoV-2 virus, which causes COVID-19, had spread so quickly across the globe that the World Health Organization officially declared COVID-19 a pandemic. COVID-19 is not the first pandemic the world has seen, so what makes it so unique in Malaysia, is discussed to avoid a future coronacoma