Pica associated with iron deficiency or depletion: clinical and laboratory correlates in 262 non-pregnant adult outpatients

<p>Abstract</p> <p>Background</p> <p>There are many descriptions of the association of pica with iron deficiency in adults, but there are few reports in which observations available at diagnosis of iron deficiency were analyzed using multivariable techniques to identify significant predictors of pica. We sought to identify clinical and laboratory correlates of pica in adults with iron deficiency or depletion using univariable and stepwise forward logistic regression analyses.</p> <p>Methods</p> <p>We reviewed charts of 262 non-pregnant adult outpatients (ages ≥18 y) who required treatment with intravenous iron dextran. We tabulated their sex, age, race/ethnicity, body mass index, symptoms and causes of iron deficiency or depletion, serum iron and complete blood count measures, and other conditions at diagnosis before intravenous iron dextran was administered. We excluded patients with serum creatinine >133 μmol/L or disorders that could affect erythrocyte or iron measures. Iron deficiency was defined as both SF <45 pmol/L and TS <10%. Iron depletion was defined as serum ferritin (SF) <112 pmol/L. We performed univariable comparisons and stepwise forward logistic regression analyses to identify significant correlates of pica.</p> <p>Results</p> <p>There were 230 women (184 white, 46 black; ages 19-91 y) and 32 men (31 white, 1 black; ages 24-81 y). 118 patients (45.0%) reported pica; of these, 87.3% reported ice pica (pagophagia). In univariable analyses, patients with pica had lower mean age, black race/ethnicity, and higher prevalences of cardiopulmonary and epithelial manifestations. The prevalence of iron deficiency, with or without anemia, did not differ significantly between patients with and without pica reports. Mean hemoglobin and mean corpuscular volume (MCV) were lower and mean red blood cell distribution width (RDW) and platelet count were higher in patients with pica. Thrombocytosis occurred only in women and was more prevalent in those with pica (20.4% vs. 8.3%; p = 0.0050). Mean total iron-binding capacity was higher and mean serum ferritin was lower in patients with pica. Nineteen patients developed a second episode of iron deficiency or depletion; concordance of recurrent pica (or absence of pica) was 95%. Predictors of pica in logistic regression analyses were age and MCV (negative associations; p = 0.0250 and 0.0018, respectively) and RDW and platelet count (positive associations; p = 0.0009 and 0.02215, respectively); the odds ratios of these predictors were low.</p> <p>Conclusions</p> <p>In non-pregnant adult patients with iron deficiency or depletion, lower age is a significant predictor of pica. Patients with pica have lower MCV, higher RDW, and higher platelet counts than patients without pica.</p

Opinion formation and distribution in a bounded-confidence model on various networks

In the social, behavioral, and economic sciences, it is an important problem to predict which individual opinions will eventually dominate in a large population, if there will be a consensus, and how long it takes a consensus to form. This idea has been studied heavily both in physics and in other disciplines, and the answer depends strongly on both the model for opinions and for the network structure on which the opinions evolve. One model that was created to study consensus formation quantitatively is the Deffuant model, in which the opinion distribution of a population evolves via sequential random pairwise encounters. To consider the heterogeneity of interactions in a population due to social influence, we study the Deffuant model on various network structures (deterministic synthetic networks, random synthetic networks, and social networks constructed from Facebook data). We numerically simulate the Deffuant model and conduct regression analyses to investigate the dependence of the time to reach steady states on various model parameters, including a confidence bound for opinion updates, the number of participating entities, and their willingness to compromise. We find that network structure and parameter values both have an effect on the convergence time. For some network topologies, the relationship between the convergence time and model parameters undergoes a transition at a critical value of the confidence bound. The steady-state opinion distribution also changes from consensus to multiple opinion groups at this critical value for some networks. We discuss the number of steady-state opinion groups in terms of a confidence-bound threshold for a transition from consensus to multiple-opinion steady states

Focus Real Estate/Construction/Design piece on creative techniques used by ret

Focus Real Estate/Construction/Design piece on creative techniques used by retail centers to fill vacancies during the recession. Large spaces that had been used by major department stores are now being divided into smaller retail spaces or being repurposed by non-traditional tenants

Opinion formation and distribution in a bounded-confidence model on various networks

In the social, behavioral, and economic sciences, it is an important problem to predict which individual opinions will eventually dominate in a large population, if there will be a consensus, and how long it takes a consensus to form. This idea has been studied heavily both in physics and in other disciplines, and the answer depends strongly on both the model for opinions and for the network structure on which the opinions evolve. One model that was created to study consensus formation quantitatively is the Deffuant model, in which the opinion distribution of a population evolves via sequential random pairwise encounters. To consider the heterogeneity of interactions in a population due to social influence, we study the Deffuant model on various network structures (deterministic synthetic networks, random synthetic networks, and social networks constructed from Facebook data). We numerically simulate the Deffuant model and conduct regression analyses to investigate the dependence of the time to reach steady states on various model parameters, including a confidence bound for opinion updates, the number of participating entities, and their willingness to compromise. We find that network structure and parameter values both have an effect on the convergence time. For some network topologies, the relationship between the convergence time and model parameters undergoes a transition at a critical value of the confidence bound. The steady-state opinion distribution also changes from consensus to multiple opinion groups at this critical value for some networks. We discuss the number of steady-state opinion groups in terms of a confidence-bound threshold for a transition from consensus to multiple-opinion steady states

Phytoscreening: A comparison of in planta portable gc-ms and in vitro analyses

Phytoscreening has been proven to rapidly delineate subsurface contaminant plumes for semiquantitative site assessment, with minimal impact to property or ecology through the collection and analysis of tree cores. Here, three phytoscreening methods were applied concurrently to identify multiple chlorinated volatile organic compounds (cVOCs) in a phytoremediation treatment system at a contaminated industrial facility. Tree coring, in planta gas chromatography-mass spectrometry (GC-MS), and in planta passive sampling showed general agreement, with the in planta GC-MS providing the quickest but least quantitative results. The portable GC-MS sampling and analysis method identified six cVOCs in the xylem of hybrid poplars (Populus sp.) in the phytoremediation plot. These real-time data can permit onsite identification and delineation of the contaminants, allowing for adaptive sampling during a single mobilization to a site. The in vitro methods provided quantitative data across two sampling campaigns, as relative cVOC concentrations remained similar between the two trips, despite a decrease in absolute cVOC concentrations from August to October. Overall, this research demonstrates the advantages and limitations of three phytoscreening techniques. © 2014, National Ground Water Association