Diagnostic accuracy of existing methods for identifying diabetic foot ulcers from inpatient and outpatient datasets

<p>Abstract</p> <p>Background</p> <p>As the number of persons with diabetes is projected to double in the next 25 years in the US, an accurate method of identifying diabetic foot ulcers in population-based data sources are ever more important for disease surveillance and public health purposes. The objectives of this study are to evaluate the accuracy of existing methods and to propose a new method.</p> <p>Methods</p> <p>Four existing methods were used to identify all patients diagnosed with a foot ulcer in a Department of Veterans Affairs (VA) hospital from the inpatient and outpatient datasets for 2003. Their electronic medical records were reviewed to verify whether the medical records positively indicate presence of a diabetic foot ulcer in diagnoses, medical assessments, or consults. For each method, five measures of accuracy and agreement were evaluated using data from medical records as the gold standard.</p> <p>Results</p> <p>Our medical record reviews show that all methods had sensitivity > 92% but their specificity varied substantially between 74% and 91%. A method used in Harrington et al. (2004) was the most accurate with 94% sensitivity and 91% specificity and produced an annual prevalence of 3.3% among VA users with diabetes nationwide. A new and simpler method consisting of two codes (707.1× and 707.9) shows an equally good accuracy with 93% sensitivity and 91% specificity and 3.1% prevalence.</p> <p>Conclusions</p> <p>Our results indicate that the Harrington and New methods are highly comparable and accurate. We recommend the Harrington method for its accuracy and the New method for its simplicity and comparable accuracy.</p

Understanding human functioning using graphical models

<p>Abstract</p> <p>Background</p> <p>Functioning and disability are universal human experiences. However, our current understanding of functioning from a comprehensive perspective is limited. The development of the International Classification of Functioning, Disability and Health (ICF) on the one hand and recent developments in graphical modeling on the other hand might be combined and open the door to a more comprehensive understanding of human functioning. The objective of our paper therefore is to explore how graphical models can be used in the study of ICF data for a range of applications.</p> <p>Methods</p> <p>We show the applicability of graphical models on ICF data for different tasks: Visualization of the dependence structure of the data set, dimension reduction and comparison of subpopulations. Moreover, we further developed and applied recent findings in causal inference using graphical models to estimate bounds on intervention effects in an observational study with many variables and without knowing the underlying causal structure.</p> <p>Results</p> <p>In each field, graphical models could be applied giving results of high face-validity. In particular, graphical models could be used for visualization of functioning in patients with spinal cord injury. The resulting graph consisted of several connected components which can be used for dimension reduction. Moreover, we found that the differences in the dependence structures between subpopulations were relevant and could be systematically analyzed using graphical models. Finally, when estimating bounds on causal effects of ICF categories on general health perceptions among patients with chronic health conditions, we found that the five ICF categories that showed the strongest effect were plausible.</p> <p>Conclusions</p> <p>Graphical Models are a flexible tool and lend themselves for a wide range of applications. In particular, studies involving ICF data seem to be suited for analysis using graphical models.</p

Predictive coding and representationalism

According to the predictive coding theory of cognition (PCT), brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, in the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system

Taxonomic Distinctness of Demersal Fishes of the California Current: Moving Beyond Simple Measures of Diversity for Marine Ecosystem-Based Management

BACKGROUND: Large-scale patterns or trends in species diversity have long interested ecologists. The classic pattern is for diversity (e.g., species richness) to decrease with increasing latitude. Taxonomic distinctness is a diversity measure based on the relatedness of the species within a sample. Here we examined patterns of taxonomic distinctness in relation to latitude (ca. 32-48 degrees N) and depth (ca. 50-1220 m) for demersal fishes on the continental shelf and slope of the US Pacific coast. METHODOLOGY/PRINCIPAL FINDINGS: Both average taxonomic distinctness (AvTD) and variation in taxonomic distinctness (VarTD) changed with latitude and depth. AvTD was highest at approximately 500 m and lowest at around 200 m bottom depth. Latitudinal trends in AvTD were somewhat weaker and were depth-specific. AvTD increased with latitude on the shelf (50-150 m) but tended to decrease with latitude at deeper depths. Variation in taxonomic distinctness (VarTD) was highest around 300 m. As with AvTD, latitudinal trends in VarTD were depth-specific. On the shelf (50-150 m), VarTD increased with latitude, while in deeper areas the patterns were more complex. Closer inspection of the data showed that the number and distribution of species within the class Chondrichthyes were the primary drivers of the overall patterns seen in AvTD and VarTD, while the relatedness and distribution of species in the order Scorpaeniformes appeared to cause the relatively low observed values of AvTD at around 200 m. CONCLUSIONS/SIGNIFICANCE: These trends contrast to some extent the patterns seen in earlier studies for species richness and evenness in demersal fishes along this coast and add to our understanding of diversity of the demersal fishes of the California Current