Preeclampsia(PE)is a pregnancy-specific syndrome,complicating 2%-8% of pregnancies.PE is a major cause of maternal mortality throughout the world with 60000 maternal deaths attributed to hypertensive disorders of preg...Preeclampsia(PE)is a pregnancy-specific syndrome,complicating 2%-8% of pregnancies.PE is a major cause of maternal mortality throughout the world with 60000 maternal deaths attributed to hypertensive disorders of pregnancy.PE also results in fetal morbidity due to prematurity and fetal growth restriction.The precise aetiology of PE remains an enigma with multiple theories including a combination of environmental,immunological and genetic factors.The conventional and leading hypotheses for the initial insult in PE is inadequate trophoblast invasion which is thought to result in incomplete remodelling of uterine spiral arteries leading to placental ischaemia,hypoxia and thus oxidative stress.The significant heterogeneity observed in pre-eclampsia cannot be solely explained by the placental model alone.Herein we critically evaluate the clinical(risk factors,placental blood flow and biomarkers)and pathological(genetic,molecular,histological)correlates for PE.Furthermore,we discuss the role played by the(dysfunctional)maternal cardiovascular system in the aetiology of PE.We review the evidence that demonstrates a role for both the placenta and the cardiovascular system in early-and late-onset PE and highlight some of the key differences between these two distinct disease entities.展开更多
Spatio-temporal models are valuable tools for disease mapping and understanding the geographical distribution of diseases and temporal dynamics. Spatio-temporal models have been proven empirically to be very complex a...Spatio-temporal models are valuable tools for disease mapping and understanding the geographical distribution of diseases and temporal dynamics. Spatio-temporal models have been proven empirically to be very complex and this complexity has led many to oversimply and model the spatial and temporal dependencies independently. Unlike common practice, this study formulated a new spatio-temporal model in a Bayesian hierarchical framework that accounts for spatial and temporal dependencies jointly. The spatial and temporal dependencies were dynamically modelled via the matern exponential covariance function. The temporal aspect was captured by the parameters of the exponential with a first-order autoregressive structure. Inferences about the parameters were obtained via Markov Chain Monte Carlo (MCMC) techniques and the spatio-temporal maps were obtained by mapping stable posterior means from the specific location and time from the best model that includes the significant risk factors. The model formulated was fitted to both simulation data and Kenya meningitis incidence data from 2013 to 2019 along with two covariates;Gross County Product (GCP) and average rainfall. The study found that both average rainfall and GCP had a significant positive association with meningitis occurrence. Also, regarding geographical distribution, the spatio-temporal maps showed that meningitis is not evenly distributed across the country as some counties reported a high number of cases compared with other counties.展开更多
文摘Preeclampsia(PE)is a pregnancy-specific syndrome,complicating 2%-8% of pregnancies.PE is a major cause of maternal mortality throughout the world with 60000 maternal deaths attributed to hypertensive disorders of pregnancy.PE also results in fetal morbidity due to prematurity and fetal growth restriction.The precise aetiology of PE remains an enigma with multiple theories including a combination of environmental,immunological and genetic factors.The conventional and leading hypotheses for the initial insult in PE is inadequate trophoblast invasion which is thought to result in incomplete remodelling of uterine spiral arteries leading to placental ischaemia,hypoxia and thus oxidative stress.The significant heterogeneity observed in pre-eclampsia cannot be solely explained by the placental model alone.Herein we critically evaluate the clinical(risk factors,placental blood flow and biomarkers)and pathological(genetic,molecular,histological)correlates for PE.Furthermore,we discuss the role played by the(dysfunctional)maternal cardiovascular system in the aetiology of PE.We review the evidence that demonstrates a role for both the placenta and the cardiovascular system in early-and late-onset PE and highlight some of the key differences between these two distinct disease entities.
文摘Spatio-temporal models are valuable tools for disease mapping and understanding the geographical distribution of diseases and temporal dynamics. Spatio-temporal models have been proven empirically to be very complex and this complexity has led many to oversimply and model the spatial and temporal dependencies independently. Unlike common practice, this study formulated a new spatio-temporal model in a Bayesian hierarchical framework that accounts for spatial and temporal dependencies jointly. The spatial and temporal dependencies were dynamically modelled via the matern exponential covariance function. The temporal aspect was captured by the parameters of the exponential with a first-order autoregressive structure. Inferences about the parameters were obtained via Markov Chain Monte Carlo (MCMC) techniques and the spatio-temporal maps were obtained by mapping stable posterior means from the specific location and time from the best model that includes the significant risk factors. The model formulated was fitted to both simulation data and Kenya meningitis incidence data from 2013 to 2019 along with two covariates;Gross County Product (GCP) and average rainfall. The study found that both average rainfall and GCP had a significant positive association with meningitis occurrence. Also, regarding geographical distribution, the spatio-temporal maps showed that meningitis is not evenly distributed across the country as some counties reported a high number of cases compared with other counties.
