Mortality rates and proximal causes of death in patients with Lewy body dementia versus Alzheimer's disease: A longitudinal study using secondary care mental health records.

BACKGROUND: Previous studies have shown reduced survival in Lewy body dementia (LBD) compared to Alzheimer's disease (AD), but the reasons for this are not known. We identified cause of death categories accounting for the reduced survival in LBD. METHODS: We linked cohorts of patients with dementia with Lewy bodies (DLB), Parkinson's disease dementia (PDD) and AD, with proximal cause of death data. We examined mortality by dementia group and hazard ratios for each death category by dementia group in males and females separately. In a specific focus on the dementia group with the highest mortality rate versus reference, we examined cumulative incidence to identify the main causes of death accounting for the excess deaths. RESULTS: Hazard ratios for death were higher in PDD and DLB compared to AD, for both males and females. PDD males had the highest hazard ratio for death across the dementia comparison groups (HR 2.7, 95% CI 2.2-3.3). Compared with AD, hazard ratios for "nervous system" causes of death were significantly elevated in all LBD groups. Additional significant cause-of-death categories included aspiration pneumonia, genitourinary causes, other respiratory causes, circulatory and a "symptoms and signs" category in PDD males; other respiratory causes in DLB males; mental disorders in PDD females; and aspiration pneumonia, genitourinary and other respiratory causes in DLB females. CONCLUSION: Further research and cohort development is required to investigate differences by age group, to extend cohort follow-up to the whole population and to investigate the risk-balance of interventions which may differ by dementia group.

Association between antidementia medication use and mortality in people diagnosed with dementia with Lewy bodies in the UK: A retrospective cohort study.

BACKGROUND: Dementia with Lewy bodies (DLBs) is a common cause of dementia but has higher mortality than Alzheimer's disease (AD). The reasons for this are unclear, but antidementia drugs (including acetylcholinesterase inhibitors [AChEIs] and memantine) symptomatically benefit people with DLB and might improve outcomes. We investigated whether AChEIs and/or memantine were associated with reduced hospital admissions and mortality. METHODS AND FINDINGS: We performed a retrospective cohort study of those diagnosed with DLB between 1 January 2005 and 31 December 2019, using data from electronic clinical records of secondary care mental health services in Cambridgeshire and Peterborough NHS Foundation Trust (CPFT), United Kingdom (catchment area population approximately 0.86 million), as well as linked records from national Hospital Episode Statistics (HES) data. Eligible patients were those who started AChEIs or memantine within 3 months of their diagnosis (cases) and those who never used AChEIs or memantine (controls). Outcomes included admission, length of stay, and mortality. Cox proportional hazard and linear regression models were used. Of 592 patients with DLB, 219 never took AChEIs or memantine, 100 took AChEIs only, and 273 took both AChEIs and memantine. The cohorts were followed up for an average of 896 days, 981 days, and 1,004 days, respectively. There were no significant differences in the cohorts' baseline characteristics, except for socioeconomic status that was lower in patients who never took AChEIs or memantine (χ2 = 23.34, P = 0.003). After controlling for confounding by sociodemographic factors (age, sex, marital status, ethnicity, socioeconomic status), antipsychotic use, antidepressant use, cognitive status, physical comorbidity, anticholinergic burden, and global health performance, compared with patients who never took AChEIs or memantine, patients taking AChEIs only or taking both had a significantly lower risk of death (adjusted hazard ratio (HR) = 0.67, 95% CI = 0.48 to 0.93, p = 0.02; adjusted HR = 0.64, 95% CI = 0.50 to 0.83, P = 0.001, respectively). Those taking AChEIs or both AChEIs and memantine had significantly shorter periods of unplanned hospital admission for physical disorders (adjusted coefficient -13.48, 95% CI = [-26.87, -0.09], P = 0.049; adjusted coefficient -14.21, 95% CI = [-24.58, -3.85], P = 0.007, respectively), but no difference in length of stay for planned admissions for physical disorders, or for admissions for mental health disorders. No significant additional associations of memantine on admission, length of stay, and mortality were found (all P > 0.05). The main limitation was that this was a naturalistic study and possible confounds cannot be fully controlled, and there may be selection bias resulting from nonrandom prescription behaviour in clinical practice. However, we mimicked the intention-to-treat design of clinical trials, and the majority of baseline characters were balanced between cohorts. In addition, our series of sensitivity analyses confirmed the consistency of our results. CONCLUSION: In this study, we observed that use of AChEIs with or without memantine in DLB was associated with shorter duration of hospital admissions and decreased risk of mortality. Although our study was naturalistic, it supports further the use of AChEIs in DLB.

Exploration of preterm birth rates using the public health exposome database and computational analysis methods.

Recent advances in informatics technology has made it possible to integrate, manipulate, and analyze variables from a wide range of scientific disciplines allowing for the examination of complex social problems such as health disparities. This study used 589 county-level variables to identify and compare geographical variation of high and low preterm birth rates. Data were collected from a number of publically available sources, bringing together natality outcomes with attributes of the natural, built, social, and policy environments. Singleton early premature county birth rate, in counties with population size over 100,000 persons provided the dependent variable. Graph theoretical techniques were used to identify a wide range of predictor variables from various domains, including black proportion, obesity and diabetes, sexually transmitted infection rates, mother's age, income, marriage rates, pollution and temperature among others. Dense subgraphs (paracliques) representing groups of highly correlated variables were resolved into latent factors, which were then used to build a regression model explaining prematurity (R-squared = 76.7%). Two lists of counties with large positive and large negative residuals, indicating unusual prematurity rates given their circumstances, may serve as a starting point for ways to intervene and reduce health disparities for preterm births.

Scalable combinatorial tools for health disparities research.

Despite staggering investments made in unraveling the human genome, current estimates suggest that as much as 90% of the variance in cancer and chronic diseases can be attributed to factors outside an individual's genetic endowment, particularly to environmental exposures experienced across his or her life course. New analytical approaches are clearly required as investigators turn to complicated systems theory and ecological, place-based and life-history perspectives in order to understand more clearly the relationships between social determinants, environmental exposures and health disparities. While traditional data analysis techniques remain foundational to health disparities research, they are easily overwhelmed by the ever-increasing size and heterogeneity of available data needed to illuminate latent gene x environment interactions. This has prompted the adaptation and application of scalable combinatorial methods, many from genome science research, to the study of population health. Most of these powerful tools are algorithmically sophisticated, highly automated and mathematically abstract. Their utility motivates the main theme of this paper, which is to describe real applications of innovative transdisciplinary models and analyses in an effort to help move the research community closer toward identifying the causal mechanisms and associated environmental contexts underlying health disparities. The public health exposome is used as a contemporary focus for addressing the complex nature of this subject.