32 research outputs found

    Effects of body composition on clinical and quality of life outcomes in kidney transplant recipients

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    Sarcopenic obesity is common among kidney transplant recipients. Fluid volume status has not been well-investigated following kidney transplantation. This thesis aimed to explore the effects of body composition, including fat mass, muscle mass and fluid volume status, on post-transplantation morbidity and fatigue. These are potential contributing factors to long-term patient- and graft- survival, as well as quality of life. Firstly, the associations between adiposity with inflammation, hepcidin and haemoglobin levels were investigated. Secondly, the effects of hypervolemia on blood pressure and levels of N-terminal fragment of pro-hormone B-type natriuretic peptide (NT-proBNP) were explored. Thirdly, the role of muscle mass and fat mass on all domains of fatigue were studied. Finally, the mechanistic aetiology of physical fatigue was examined by evaluation of muscle mass, muscular and cardiovascular functions, and fatigue perception. This thesis concluded that while adiposity displays significant independent association with inflammation, its role in determining hepcidin and haemoglobin levels remains uncertain. Reduced muscle mass may be correlated with physical fatigue, but independent contribution of fat mass in fatigue remains undefined. Hypervolemia is associated with raised blood pressure and elevated levels of NT-proBNP. The findings from this thesis set the scene for future interventional research and therapeutic strategies

    Relationship between cortical thickness and neuropsychological performance in normal older adults and those with mild cognitive impairment

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    Mild cognitive impairment (MCI) has been extensively investigated in recent decades to identify groups with a high risk of dementia and to establish effective prevention methods during this period. Neuropsychological performance and cortical thickness are two important biomarkers used to predict progression from MCI to dementia. This study compares the cortical thickness and neuropsychological performance in people with MCI and cognitively healthy older adults. We further focus on the relationship between cortical thickness and neuropsychological performance in these two groups. Forty-nine participants with MCI and 40 cognitively healthy older adults were recruited. Cortical thickness was analysed with semiautomatic software, Freesurfer. The analysis reveals that the cortical thickness in the left caudal anterior cingulate (p=0.041), lateral occipital (p=0.009) and right superior temporal (p=0.047) areas were significantly thinner in the MCI group after adjustment for age and education. Almost all neuropsychological test results (with the exception of forward digit span) were significantly correlated to cortical thickness in the MCI group after adjustment for age, gender and education. In contrast, only the score on the Category Verbal Fluency Test and the forward digit span were found to have significant inverse correlations to cortical thickness in the control group of cognitively healthy older adults. The study results suggest that cortical thinning in the temporal region reflects the global change in cognition in subjects with MCI and may be useful to predict progression of MCI to Alzheimer's disease. The different pattern in the correlation of cortical thickness to the neuropsychological performance of patients with MCI from the healthy control subjects may be explained by the hypothesis of MCI as a disconnection syndrome

    The epidemiology of COVID-19 cases and the successful containment strategy in Hong Kong-January to May 2020

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    BACKGROUND: Hong Kong, a Special Administrative Region of China, recorded its first confirmed coronavirus disease 2019 (COVID-19) case on 23 January 2020. We reviewed the case epidemiology and the various public health measures implemented from January to May 2020. METHODS: The epidemiological and clinical characteristics of the cases recorded in different phases of the epidemic were described and compared, and the effectiveness of the public health measures implemented were reviewed using the changes in the daily number of confirmed cases and the interval from symptom onset to hospital admission. RESULTS: Between January and May 2020, 1084 confirmed COVID-19 cases were reported, about 70% of which had a history of travel during the incubation period. The case fatality ratio was 0.4%. The local epidemic progressed through four phases: (1) preparedness and imported infection from mainland China, (2) local transmission, (3) imported infection from overseas countries associated with local transmission, and (4) controlled imported infection with limited local transmission, with an eventual reduction of the daily case number and minimization of the onset-to-admission interval. Various public health measures, including enhanced surveillance, border control, and social distancing, were introduced in phases in response to the prevailing local and global situations. DISCUSSION: The overall containment strategy in Hong Kong led to a stabilization of the number of cases and the absence of a community-wide outbreak during the 4.5 m after the first case was reported. This strategy of containment might serve as an example for future planning of preparedness and response against novel infectious agents

    Return to work, work productivity loss and activity impairment in Chinese breast cancer survivors 12-month post-surgery: a longitudinal study

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    IntroductionExisting evidence of returning-to-work (RTW) after cancer comes predominately from Western settings, with none prospectively examined since the initial diagnostic phase. This study prospectively documents RTW-rate, time-to-RTW, work productivity loss, and activity impairment, within the first-year post-surgery among Chinese women with breast cancer (BCW) and identify potential causal co-variants.MethodsThis observational longitudinal study followed 371 Chinese BCW who were employed/self-employed at the time of diagnosis at 4-week post-surgery (baseline). RTW-status and time-to-RTW were assessed at baseline (T1), 4-month (T2), 6-month (T3), and 12-month (T4) post-baseline. WPAI work productivity loss and activity impairment were assessed at T4. Baseline covariates included demographics, medical-related factors, work satisfaction, perceived work demand, work condition, RTW self-efficacy, B-IPQ illness perception, COST financial well-being, EORTC QLQ-C30 and QLQ-BR23 physical and psychosocial functioning, and HADS psychological distress.ResultsA 68.2% RTW-rate (at 12-month post-surgery), prolonged delay in RTW (median = 183 days), and significant proportions of T4 work productivity loss (20%), and activity impairment (26%), were seen. BCW who were blue-collar workers with lower household income, poorer financial well-being, lower RTW self-efficacy, poorer job satisfaction, poorer illness perception, greater physical symptom distress, impaired physical functioning, and unfavorable work conditions were more likely to experience undesired work-related outcomes.DiscussionUsing a multifactorial approach, effective RTW interventions should focus on not only symptom management, but also to address psychosocial and work-environmental concerns. An organizational or policy level intervention involving a multidisciplinary team comprising nurses, psychologists, occupational health professionals, and relevant stakeholders in the workplace might be helpful in developing a tailored organizational policy promoting work-related outcomes in BCW

    Prognostic Model of COVID-19 Severity and Survival among Hospitalized Patients Using Machine Learning Techniques

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    We conducted a statistical study and developed a machine learning model to triage COVID-19 patients affected during the height of the COVID-19 pandemic in Hong Kong based on their medical records and test results (features) collected during their hospitalization. The correlation between the values of these features is studied against discharge status and disease severity as a preliminary step to identify those features with a more pronounced effect on the patient outcome. Once identified, they constitute the inputs of four machine learning models, Decision Tree, Random Forest, Gradient and RUSBoosting, which predict both the Mortality and Severity associated with the disease. We test the accuracy of the models when the number of input features is varied, demonstrating their stability; i.e., the models are already highly predictive when run over a core set of (6) features. We show that Random Forest and Gradient Boosting classifiers are highly accurate in predicting patients’ Mortality (average accuracy ∼99%) as well as categorize patients (average accuracy ∼91%) into four distinct risk classes (Severity of COVID-19 infection). Our methodical and broad approach combines statistical insights with various machine learning models, which paves the way forward in the AI-assisted triage and prognosis of COVID-19 cases, which is potentially generalizable to other seasonal flus

    Table_1_Return to work, work productivity loss and activity impairment in Chinese breast cancer survivors 12-month post-surgery: a longitudinal study.DOCX

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    IntroductionExisting evidence of returning-to-work (RTW) after cancer comes predominately from Western settings, with none prospectively examined since the initial diagnostic phase. This study prospectively documents RTW-rate, time-to-RTW, work productivity loss, and activity impairment, within the first-year post-surgery among Chinese women with breast cancer (BCW) and identify potential causal co-variants.MethodsThis observational longitudinal study followed 371 Chinese BCW who were employed/self-employed at the time of diagnosis at 4-week post-surgery (baseline). RTW-status and time-to-RTW were assessed at baseline (T1), 4-month (T2), 6-month (T3), and 12-month (T4) post-baseline. WPAI work productivity loss and activity impairment were assessed at T4. Baseline covariates included demographics, medical-related factors, work satisfaction, perceived work demand, work condition, RTW self-efficacy, B-IPQ illness perception, COST financial well-being, EORTC QLQ-C30 and QLQ-BR23 physical and psychosocial functioning, and HADS psychological distress.ResultsA 68.2% RTW-rate (at 12-month post-surgery), prolonged delay in RTW (median = 183 days), and significant proportions of T4 work productivity loss (20%), and activity impairment (26%), were seen. BCW who were blue-collar workers with lower household income, poorer financial well-being, lower RTW self-efficacy, poorer job satisfaction, poorer illness perception, greater physical symptom distress, impaired physical functioning, and unfavorable work conditions were more likely to experience undesired work-related outcomes.DiscussionUsing a multifactorial approach, effective RTW interventions should focus on not only symptom management, but also to address psychosocial and work-environmental concerns. An organizational or policy level intervention involving a multidisciplinary team comprising nurses, psychologists, occupational health professionals, and relevant stakeholders in the workplace might be helpful in developing a tailored organizational policy promoting work-related outcomes in BCW.</p

    Implementation of an interprofessional team-based learning program involving seven undergraduate health and social care programs from two universities, and students’ evaluation of their readiness for interprofessional learning

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    Abstract Background Interprofessional learning is gaining momentum in revolutionizing healthcare education. During the academic year 2015/16, seven undergraduate-entry health and social care programs from two universities in Hong Kong took part in an interprofessional education program. Based on considerations such as the large number of students involved and the need to incorporate adult learning principles, team-based learning was adopted as the pedagogy for the program, which was therefore called the interprofessional team-based learning program (IPTBL). The authors describe the development and implementation of the IPTBL program and evaluate the effectiveness of the program implementation. Methods Eight hundred and one students, who are predominantly Chinese, participated in the IPTBL. The quantitative design (a pretest-posttest experimental design) was utilized to examine the students’ gains on their readiness to engage in interprofessional education (IPE). Results Three instructional units (IUs) were implemented, each around a clinical area which could engage students from complementary health and social care disciplines. Each IU followed a team-based learning (TBL) process: pre-class study, individual readiness assurance test, team readiness assurance test, appeal, feedback, and application exercise. An electronic platform was developed and was progressively introduced in the three IUs. The students’ self-perceived attainment of the IPE learning outcomes was high. Across all four subscales of RIPLS, there was significant improvement in student’s readiness to engage in interprofessional learning after the IPTBL. A number of challenges were identified: significant time involvement of the teachers, difficulty in matching students from different programs, difficulty in making IPTBL count towards a summative assessment score, difficulty in developing the LAMS platform, logistics difficulty in managing paper TBL, and inappropriateness of the venue. Conclusions Despite some challenges in developing and implementing the IPTBL program, our experience showed that TBL is a viable pedagogy to be used in interprofessional education involving hundreds of students. The significant improvement in all four subscales of RIPLS showed the effects of the IPTBL program in preparing students for collaborative practice. Factors that contributed to the success of the use of TBL for IPE are discussed
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