Flexible Bayesian semiparametric mixed-effects model for skewed longitudinal data.

BACKGROUND: In clinical trials and epidemiological research, mixed-effects models are commonly used to examine population-level and subject-specific trajectories of biomarkers over time. Despite their increasing popularity and application, the specification of these models necessitates a great deal of care when analysing longitudinal data with non-linear patterns and asymmetry. Parametric (linear) mixed-effect models may not capture these complexities flexibly and adequately. Additionally, assuming a Gaussian distribution for random effects and/or model errors may be overly restrictive, as it lacks robustness against deviations from symmetry. METHODS: This paper presents a semiparametric mixed-effects model with flexible distributions for complex longitudinal data in the Bayesian paradigm. The non-linear time effect on the longitudinal response was modelled using a spline approach. The multivariate skew-t distribution, which is a more flexible distribution, is utilized to relax the normality assumptions associated with both random-effects and model errors. RESULTS: To assess the effectiveness of the proposed methods in various model settings, simulation studies were conducted. We then applied these models on chronic kidney disease (CKD) data and assessed the relationship between covariates and estimated glomerular filtration rate (eGFR). First, we compared the proposed semiparametric partially linear mixed-effect (SPPLM) model with the fully parametric one (FPLM), and the results indicated that the SPPLM model outperformed the FPLM model. We then further compared four different SPPLM models, each assuming different distributions for the random effects and model errors. The model with a skew-t distribution exhibited a superior fit to the CKD data compared to the Gaussian model. The findings from the application revealed that hypertension, diabetes, and follow-up time had a substantial association with kidney function, specifically leading to a decrease in GFR estimates. CONCLUSIONS: The application and simulation studies have demonstrated that our work has made a significant contribution towards a more robust and adaptable methodology for modeling intricate longitudinal data. We achieved this by proposing a semiparametric Bayesian modeling approach with a spline smoothing function and a skew-t distribution.

Prevalence of musculoskeletal disorders amongst flower farm workers in Kenya.

BACKGROUND: Work-related musculoskeletal disorders (WMSDs) are a global public concern for health and social-care systems, as well as individuals. They are the second-most prevalent cause of disability globally. OBJECTIVES: The primary objective was to determine the prevalence of WMSDs amongst flower farm workers. The secondary objective was to determine the association between the socio-demographic characteristics and the presence of WMSDs in the previous 12-month period. METHOD: A cross-sectional descriptive study was conducted. A sample of 270 participants was drawn from 897 farm workers. Quantitative data related to musculoskeletal disorders were collected using the Nordic Musculoskeletal Questionnaire (NMQ). Descriptive statistics were undertaken using frequencies and percentages. Inferential statistics were analysed using a chi-squared test (X2) based on an alpha level of p < 0.05. RESULTS: A total of 184 (68.1%) respondents reported musculoskeletal discomfort. Amongst the 184 respondents, 178 were performing general farm work. Most 103 (38.1%) of the WMSDs were reported in the lower back. There was a strong association between job designation as a general worker (p = 0.016), an older age (p = 0.027) and having worked for a long time as a farm worker (p = 0.041) and WMSDs. CONCLUSION: Flower farm workers in Kenya were found to be heavily burdened by WMSDs. Furthermore, the job designation, older age, as well as having worked for a long time, predisposes workers to the risk of developing WMSDs. CLINICAL IMPLICATIONS: The high prevalence of WMSDs necessitates policy reform in the flower farm industry.

IgM, lgG and IL-6 profiles in the Trypanosoma brucei brucei monkey model of human African trypanosomiasis.

Human African trypanosomiasis (HAT) patients manifest immunological profiles, whose variations over time can be used to indicate disease progression. However, monitoring of these biomarkers in human patients is beset by several limitations which can be offset by using chronic animal models. A recent improved monkey model of HAT using a Trypanosoma brucei brucei isolate has been developed but the immunological profile has not been elucidated. The objectives of the current study was to determine the IgM, IgG and IL-6 profiles in blood and cerebrospinal fluid (CSF) in vervet monkeys infected with T. b. brucei. Three vervet monkeys were infected intravenously with 105T. b. brucei, monitored for disease development and subsequently treated 28days post infection (dpi) sub-curatively using diminazene aceturate (DA) to induce late stage disease and curatively treated with melarsoprol (Mel B) at 119 dpi, respectively. Matched serum and cerebrospinal fluid (CSF) samples were obtained at regular intervals and immunospecific IgM, immunoglobulin G (IgG) were quantified by ELISA while IL-6 was assayed using a cytometric bead array (CBA) kit. Results showed that following infection, CSF IgM, IgG, IL-6 and serum IL-6 were significantly (p<0.05) elevated with peak levels coinciding with relapse parasitaemia. The IgG levels increased to reach OD peak levels of 0.442±0.5 at 126 dpi. After curative treatment with MelB, the serum IgM and Ig G levels fell rapidly to attain pre-infection levels within 35 and 49days, respectively. This shows that the profile of these immunoglobulins can be used as an indicator of curative treatment. CSF IL-6 concentrations of infected vervet monkeys showed no significant change (P>0.05) between infection and 35 dpi but levels increased significantly (P<0.05) with the highest level of 55.53pg/ml recorded at112 dpi. IL-6 elevation from 35 dpi may be indicative of parasite neuroinvasion hence can be used as possible candidate marker for late stage disease in the monkey model. Further, the marker can also be used in conjunction with IgG and IgM as markers for development of test of cure for HAT.