Palliative care in dementia: does it work?

The topic of palliative care in dementia has attracted increasing interest in recent years. Entering palliative+care+dementia into PubMed yields only 10 papers before 1990, the first from 1982. In contrast, there have been 100 or so papers in each of the last three years. The question we have set in this editorial is deliberately ambiguous. ‘Does it work?’ can be either a question about effectiveness in practice or a question about the concept of palliative care as applied to dementia and, in this regard, it’s a question as to how palliative care fits in with the journey of dementia and the other models of care that may be relevant. Conceptual In relation to dementia, palliative care could cover a huge range from the whole course of dementia from diagnosis onwards to a much narrower focus on end-of-life care. And maybe there are points in between, e.g. as a person passes from ‘living well with dementia’ to the next stage, which might be regarded as that of inexorable decline. Van der Steen et al [1] have attempted to create clearer boundaries for what we mean by ‘palliative care’ in dementia. They used a Delphi process to generate a set of core domains and then tested these on a wider international panel of experts. Most of these domains achieved consensus: the two which did not were about the importance of palliative care in relation to the stage of dementia and to provision of artificial nutrition and hydration. The first of these concerns reflected disagreement as to whether all dementia care should be relabelled as palliative care [2]. Another issue for palliative dementia care is that it has to compete with other terms that belong to other frameworks. Palliative care has a fairly simple conceptual basis (we allege) in that in the absence of a cure, health professionals should concentrate on relieving troublesome symptoms and avoiding unnecessary, potentially harmful, interventions. It has noble Classical roots – primum non nocere – that probably go back to Hippocrates. It is closely associated with ‘end of life care’ or ‘care of the dying’ which has similar sentiments but is perhaps more closely associated with the relief of pain and bringing comfort and solace. End of life care implies a clinical milieu, even if this happens to be the person’s own home. The prevailing paradigm in dementia, however, is person-centred care, which derives from the work of Kitwood and the Bradford group. By contrast to palliative care, this arises from a reaction to the medicalisation of dementia and uses social psychology to draw attention to the perspective of the person with dementia and how the actions of those around them can shape behaviour. This model has been highly attractive for the public, the voluntary sector, and workers and academics with a psychosocial bent. It is clear how person-centred care is applicable across the whole pathway of dementia. It has enabled the voice of people with dementia to be heard, so that we now have the remarkable growth of a disability movement within dementia, with bloggers, activists, and groups such as Dementia Alliance International (http://www.dementiaallianceinternational.org/). Expect further changes in the future as people living with dementia demand their rights, equality and full citizenship. Empirical Universal acceptance of palliative care in dementia would be easier if there was good research evidence that it delivers better outcomes than other forms of care. This is more difficult to test than it appears at first sight, for at least two good reasons. The first of these is that, if we take the view that all dementia care is palliative care, any trial of palliative care might need to be across the whole pathway of dementia. This is unfeasible given the length of time that such a trial would have to run, not to mention some of the methodological issues as to what outcomes are desirable and at what points in the course of the dementia they should be ascertained. The second problem is that it is customary in studies of psychosocial interventions in dementia to compare the treatment of interest with ‘usual care’. However, this is difficult too. Is palliative care an ‘intervention’? And what is ‘usual care’? And does it not already have a palliative quality? Thus, it is probably impossible to test empirically whether palliative care ‘works’ as a form of dementia care across the whole pathway. In practice, we duck this question by talking about a palliative care approach but it isn’t established whether this adds anything to what we already do. Palliative care can be tested if specific aspects of management, usually towards the end of life, are being evaluated. For example, it is perfectly possible to compare the outcomes of artificial nutrition with not providing it, in terms of survival, pain, quality of life and so on (see Sampson et al [3] for a review). Although, note that either arm of this trial can be regarded as palliative care so, even if one arm does better, this doesn’t tell us if palliative care is effective. It is simply a judgement between two palliative care options. Conclusion Applying the term palliative care in dementia has some attractions and this accounts for the expansion of recent interest. However, it is a slippery concept to use as there is no agreement as to when it is best applied to dementia and there is no evidence that any thus-labelled intervention has improved outcomes. Furthermore, this may not even be an empirical question, in which case it is either a moral question (‘how do we wish to end our lives?’) or one of popular taste. So far, the discourse has been confined to professionals and experts and the voice of people with dementia is missing. ‘Palliative’ may be too clinical a word for their taste

Post-cooling stress-strain model of traditional and high-strength concrete

As concrete structures suffer from severe fire damage, but may retain a certain remaining loadbearing capacity, it is important to have material properties for assessment by calculation after fire. This paper proposes a full stress-strain model for post-cooling conditions of a traditional calcareous concrete (TCC) and a high strength siliceous concrete (HSSC)

Imputation strategies for natural effect models probing mediation

Natural effect models parameterize the natural direct and indirect effects of an exposure on an outcome in function of baseline covariates. Vansteelandt and colleagues introduced a regression mean imputation strategy for fitting these models. Compared to direct application of the mediation formula, this framework allows for (i) more easily interpretable effect estimates and (ii) more convenient hypothesis testing. So far, the statistical properties (robustness to model misspecification, and efficiency) of the considered imputation strategy are not well understood. For instance, in non-linear settings where traditional product-of-coefficients estimators for the indirect effect are applicable for assessing mediation under the null of no effect of exposure on mediator, these estimators outperform the imputation estimators in terms of efficiency when the imputation model is fitted using MLE. In this talk, we will discuss advanced imputation strategies to improve efficiency and robustness. We will discuss their implementation using the R package flexmed

Hypotension and hypocapnia during general anesthesia in piglets: study of S100b as an acute biomarker for cerebral tissue injury

BACKGROUND Hypotension and/or hypocapnia might increase general anesthesia (GA)-related neuromorbidity in infants, but safe levels of perioperative blood pressure are poorly defined. Serum protein S100b has been used as screening, monitoring, and prediction tool in the management of patients with traumatic brain injury. Using an animal model, we investigated serum S100b as an acute biomarker of cerebral hypoperfusion and cerebral cell dysfunction during hypotension, hypocapnia, or combined hypotension/hypocapnia during GA. METHODS Fifty-seven sevoflurane-midazolam anesthetized piglets aged 4 to 6 weeks were randomly allocated to control (n=9), hypotension (n=18), hypocapnia (n=20), or combined hypotension and hypocapnia (n=10). Hypotension (target mean arterial blood pressure: 35 to 38 or 27 to 30 mm Hg) was induced by blood withdrawal and nitroprusside infusion, and hypocapnia by hyperventilation (target PaCO2: 28 to 30 and 23 to 25 mm Hg). Serum S100b and albumin were measured at baseline, before and 60 minutes after the interventions, and following 60-minute recovery. RESULTS Serum S100b concentrations decreased over time (P=0.001), but there was no difference in S100b between control piglets and those exposed to hypotension, hypocapnea, or a combination of the both (P=0.105). Albumin decreased in all 4 groups (P=0.001). CONCLUSION S100b did not increase following 60 minutes of systemic hypotension and/or hypocapnia during GA in piglets. In this setting, the use of S100b as a biomarker of cerebral cell tissue dysfunction cannot be supported

Lower-Order Effects Adjustment in Quantitative Traits Model-Based Multifactor Dimensionality Reduction

Identifying gene-gene interactions or gene-environment interactions in studies of human complex diseases remains a big challenge in genetic epidemiology. An additional challenge, often forgotten, is to account for important lower-order genetic effects. These may hamper the identification of genuine epistasis. If lower-order genetic effects contribute to the genetic variance of a trait, identified statistical interactions may simply be due to a signal boost of these effects. In this study, we restrict attention to quantitative traits and bi-allelic SNPs as genetic markers. Moreover, our interaction study focuses on 2-way SNP-SNP interactions. Via simulations, we assess the performance of different corrective measures for lower-order genetic effects in Model-Based Multifactor Dimensionality Reduction epistasis detection, using additive and co-dominant coding schemes. Performance is evaluated in terms of power and familywise error rate. Our simulations indicate that empirical power estimates are reduced with correction of lower-order effects, likewise familywise error rates. Easy-to-use automatic SNP selection procedures, SNP selection based on “top” findings, or SNP selection based on p-value criterion for interesting main effects result in reduced power but also almost zero false positive rates. Always accounting for main effects in the SNP-SNP pair under investigation during Model-Based Multifactor Dimensionality Reduction analysis adequately controls false positive epistasis findings. This is particularly true when adopting a co-dominant corrective coding scheme. In conclusion, automatic search procedures to identify lower-order effects to correct for during epistasis screening should be avoided. The same is true for procedures that adjust for lower-order effects prior to Model-Based Multifactor Dimensionality Reduction and involve using residuals as the new trait. We advocate using “on-the-fly” lower-order effects adjusting when screening for SNP-SNP interactions using Model-Based Multifactor Dimensionality Reduction analysis

Wavelet-based functional mixed models for the analysis of lateralized readiness potentials

Event-related potentials recorded from the human scalp using EEG can provide important information about how the human brain processes information. To unravel cognitive processes, the so-called lateralized readiness potential (LRP) has become an especially useful temporal marker within the area of chrono-psychophysiology. Simple parametric modeling of such LRP-curves is unsufficient and nonparametric approaches allowing for arbitrary functional forms are warranted. Smoothing methods using global bandwidths and penalties are often used to model such longitudinal data with curves but fail to capture spatial heterogeneity and local features like peaks. Using kernels with local bandwidths and adaptive penalties can address these issues in the single-function setting, but are not easily generalized to the multiple-function setting. Wavelet-based functional mixed models (WFMM) as proposed by Morris and Carroll (JRSS B, 2006, Vol.68, pp179-199) may offer a valuable alternative in this setting. We aim to illustrate WFMM to LRP-data from a task switching study. More specifically we are interested to determine the timepoint/latency at which a consistent divergence in LRP-signals between task repetitions and task switches can be observed and to investigate whether this latency is influenced by other factors (such as cuing type, indication requirement, ...). Repeated testing at different timepoints induces a multiple testing problem (MTP). We compare the performance of different multiple testing procedures using the pointwise posterior credible intervals versus inference from the joint posterior credible interval