Can falls risk prediction tools correctly identify fall-prone elderly rehabilitation inpatients? A systematic review and meta-analysis

BACKGROUND: Falls of elderly people may cause permanent disability or death. Particularly susceptible are elderly patients in rehabilitation hospitals. We systematically reviewed the literature to identify falls prediction tools available for assessing elderly inpatients in rehabilitation hospitals. METHODS AND FINDINGS: We searched six electronic databases using comprehensive search strategies developed for each database. Estimates of sensitivity and specificity were plotted in ROC space graphs and pooled across studies. Our search identified three studies which assessed the prediction properties of falls prediction tools in a total of 754 elderly inpatients in rehabilitation hospitals. Only the STRATIFY tool was assessed in all three studies; the other identified tools (PJC-FRAT and DOWNTON) were assessed by a single study. For a STRATIFY cut-score of two, pooled sensitivity was 73% (95%CI 63 to 81%) and pooled specificity was 42% (95%CI 34 to 51%). An indirect comparison of the tools across studies indicated that the DOWNTON tool has the highest sensitivity (92%), while the PJC-FRAT offers the best balance between sensitivity and specificity (73% and 75%, respectively). All studies presented major methodological limitations. CONCLUSIONS: We did not identify any tool which had an optimal balance between sensitivity and specificity, or which were clearly better than a simple clinical judgment of risk of falling. The limited number of identified studies with major methodological limitations impairs sound conclusions on the usefulness of falls risk prediction tools in geriatric rehabilitation hospitals

Inflation and Holography in String Theory

The encoding of an inflating patch of space-time in terms of a dual theory is discussed. Following Bousso's interpretation of the holographic principle, we find that those are generically described not by states in the dual theory but by density matrices. We try to implement this idea on simple deformations of the AdS/CFT examples, and an argument is given as to why inflation is so elusive to string theory.Comment: 15 pages, LaTeX, 2 figures. Uses psbox.te

On SUSY curves

In this note we give a summary of some elementary results in the theory of super Riemann surfaces (SUSY curves)

Current account patterns and national real estate markets

This paper studies the association between current account and real estate valuation across countries. We find a robust and strong positive association between current account deficits and the appreciation of the real estate prices/(GDP deflator). Controlling for lagged GDP/capita growth, inflation, financial depth, institution, urban population growth and the real interest rate; a one standard deviation increase of the lagged current account deficits is associated with an appreciation of the real estate prices by 10%. This real appreciation is magnified by financial depth, and mitigated by the quality of institutions. Intriguingly, the economic importance of current account variations in accounting for the real estate valuation exceeds that of the other variables, including the real interest rate and inflation. Among the OECD countries, we find evidence of a decline over time in the cross country variation of the real estate/(GDP deflator), consistent with the growing globalization of national real estate markets. Weaker patterns apply to the non-OECD countries in the aftermath of the East Asian crisis

Can falls risk prediction tools correctly identify fall-prone elderly rehabilitation inpatients? A systematic review and meta-analysis

Background Falls of elderly people may cause permanent disability or death. Particularly susceptible are elderly patients in rehabilitation hospitals. We systematically reviewed the literature to identify falls prediction tools available for assessing elderly inpatients in rehabilitation hospitals. Methods and Findings We searched six electronic databases using comprehensive search strategies developed for each database. Estimates of sensitivity and specificity were plotted in ROC space graphs and pooled across studies. Our search identified three studies which assessed the prediction properties of falls prediction tools in a total of 754 elderly inpatients in rehabilitation hospitals. Only the STRATIFY tool was assessed in all three studies; the other identified tools (PJC-FRAT and DOWNTON) were assessed by a single study. For a STRATIFY cut-score of two, pooled sensitivity was 73% (95%CI 63 to 81%) and pooled specificity was 42% (95%CI 34 to 51%). An indirect comparison of the tools across studies indicated that the DOWNTON tool has the highest sensitivity (92%), while the PJC-FRAT offers the best balance between sensitivity and specificity (73% and 75%, respectively). All studies presented major methodological limitations. Conclusions We did not identify any tool which had an optimal balance between sensitivity and specificity, or which were clearly better than a simple clinical judgment of risk of falling. The limited number of identified studies with major methodological limitations impairs sound conclusions on the usefulness of falls risk prediction tools in geriatric rehabilitation hospitals

CDX2 autoregulation in human intestinal metaplasia of the stomach: impact on the stability of the phenotype

Background and aims Intestinal metaplasia (IM) is a gastric preneoplastic lesion that appears following Helicobacter pylori infection and confers an increased risk for development of cancer. It is induced by gastric expression of the intestine-specific transcription factor CDX2. The regulatory mechanisms involved in triggering and maintaining gastric CDX2 expression have not been fully elucidated. The Cdx2(+/-) mouse develops intestinal polyps with gastric differentiation and total loss of Cdx2 expression in the absence of structural loss of the second allele, suggesting a regulatory defect. This putative haplo-insufficiency, together with the apparent stability of IM, led to the hypothesis that CDX2 regulates its own expression through an autoregulatory loop in both contexts.Methods Gastrointestinal cell lines were co-transfected with wild-type or mutated Cdx2 promoter constructs and CDX2 expression vector for luciferase assays. Transfection experiments were also used to assess endogenous CDX2 autoregulation, evaluated by RT-PCR, qPCR and western blotting. Chromatin immunoprecipitation was performed in a cell line, mouse ileum and human IM. Results CDX2 binds to and transactivates its own promoter and positively regulates its expression in gastrointestinal human carcinoma cell lines. Furthermore, CDX2 is bound to its promoter in the mouse ileum and in human gastric IM, providing a major contribution to understanding the relevance of this autoregulatory pathway in vivo.Conclusion The results of this study demonstrate another layer of complexity in CDX2 regulation by an effective autoregulatory loop which may have a major impact on the stability of human IM, possibly resulting in the inevitable progression of the gastric carcinogenesis pathway

Measuring paw preferences in dogs, cats and rats: Design requirements and innovations in methodology

Studying behavioural lateralization in animals holds great potential for answering important questions in laterality research and clinical neuroscience. However, comparative research encounters challenges in reliability and validity, requiring new approaches and innovative designs to overcome. Although validated tests exist for some species, there is yet no standard test to compare lateralized manual behaviours between individuals, populations, and animal species. One of the main reasons is that different fine-motor abilities and postures must be considered for each species. Given that pawedness/handedness is a universal marker for behavioural lateralization across species, this article focuses on three commonly investigated species in laterality research: dogs, cats, and rats. We will present six apparatuses (two for dogs, three for cats, and one for rats) that enable an accurate assessment of paw preference. Design requirements and specifications such as zoometric fit for different body sizes and ages, reliability, robustness of the material, maintenance during and after testing, and animal welfare are extremely important when designing a new apparatus. Given that the study of behavioural lateralization yields crucial insights into animal welfare, laterality research, and clinical neuroscience, we aim to provide a solution to these challenges by presenting design requirements and innovations in methodology across species

A global method for coupling transport with chemistry in heterogeneous porous media

Modeling reactive transport in porous media, using a local chemical equilibrium assumption, leads to a system of advection-diffusion PDE's coupled with algebraic equations. When solving this coupled system, the algebraic equations have to be solved at each grid point for each chemical species and at each time step. This leads to a coupled non-linear system. In this paper a global solution approach that enables to keep the software codes for transport and chemistry distinct is proposed. The method applies the Newton-Krylov framework to the formulation for reactive transport used in operator splitting. The method is formulated in terms of total mobile and total fixed concentrations and uses the chemical solver as a black box, as it only requires that on be able to solve chemical equilibrium problems (and compute derivatives), without having to know the solution method. An additional advantage of the Newton-Krylov method is that the Jacobian is only needed as an operator in a Jacobian matrix times vector product. The proposed method is tested on the MoMaS reactive transport benchmark.Comment: Computational Geosciences (2009) http://www.springerlink.com/content/933p55085742m203/?p=db14bb8c399b49979ba8389a3cae1b0f&pi=1

Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases