Managing comorbidities in chronic kidney disease reduces utilization and costs.

BACKGROUND: Effective management of comorbid diabetes and hypertension in patients with chronic kidney disease (CKD) is important for optimal outcomes. However, little is known about this relationship from a health plan perspective. The objective of this study was to evaluate the association of effective management of comorbid diabetes and/or hypertension with healthcare resource utilization (HCRU) in patients with chronic kidney disease (CKD). METHODS: This retrospective cohort study used the Humana Research Database to identify patients with CKD Stage ≥ 3a in 2017. Eligible patients were enrolled in a Medicare Advantage Prescription Drug plan for ≥ 12 months before and after the index date (first observed evidence of CKD). Patients with end-stage renal disease, kidney transplant, or hospice election preindex were excluded. Recommended comorbid disease management included hemoglobin A1c monitoring; adherence to glucose-lowering, cardiovascular, and angiotensin-converting enzyme inhibitors/angiotensin receptor blocker medications; and nephrologist/primary care provider (PCP) visits. HCRU was evaluated for 12 months postindex. RESULTS: The final cohort of 241,628 patients was 55% female and 77% White, with an average age of 75 years. Approximately 90% of patients had Stage 3 CKD. Half had both diabetes and hypertension, and most of the remaining half had hypertension without diabetes. Patients meeting the criteria for good disease management, compared with patients not meeting those criteria, were less likely to experience an inpatient hospitalization, by as much as 40% depending on the criterion and the comorbidities present, or an emergency department visit, by as much as 30%. Total monthly healthcare costs were as much as 17% lower. CONCLUSIONS: Management of comorbid diabetes and hypertension in patients with CKD was associated with lower HCRU and costs. Care coordination programs targeting patients with CKD must give careful attention to glucose and blood pressure control. TRIAL REGISTRATION: Not applicable.

Transition-to-dialysis planning, health care use, and mortality in end-stage renal disease.

OBJECTIVES: To evaluate the association of dialysis transition planning factors (eg, nephrologist care, vascular access placement, place of dialysis) with inpatient (IP) stays, emergency department (ED) visits, and mortality. STUDY DESIGN: Retrospective cohort study. METHODS: We used the Humana Research Database to identify 7026 patients with a diagnosis of end-stage renal disease (ESRD) in 2017 who were enrolled in a Medicare Advantage Prescription Drug plan with at least 12 months preindex enrollment, with first ESRD evidence as the index date. Patients with kidney transplant, hospice election, or dialysis preindex were excluded. Transition-to-dialysis planning was defined as optimal (vascular access placed), suboptimal (nephrologist care, but no vascular access), or unplanned (first dialysis in IP stay or ED visit). RESULTS: The cohort was 41% female and 66% White, with a mean age of 70 years. Optimally planned, suboptimally planned, and unplanned transition to dialysis occurred for 15%, 34%, and 44% of the cohort, respectively. Among patients with preindex chronic kidney disease (CKD) stages 3a and 3b, 64% and 55%, respectively, had an unplanned dialysis transition. For patients with preindex CKD stages 4 and 5, 68% and 84%, respectively, had a planned transition. In adjusted models, patients with a suboptimally or optimally planned transition were 57% to 72% less likely to die, 20% to 37% less likely to experience an IP stay, and 80% to 100% more likely to experience an ED visit than patients with an unplanned dialysis transition. CONCLUSIONS: A planned transition to dialysis was associated with reduced odds of IP stays and lower mortality.

Assessing Contamination of Stream Networks near Shale Gas Development Using a New Geospatial Tool.

Chemical spills in streams can impact ecosystem or human health. Typically, the public learns of spills from reports from industry, media, or government rather than monitoring data. For example, ∼1300 spills (76 ≥ 400 gallons or ∼1500 L) were reported from 2007 to 2014 by the regulator for natural gas wellpads in the Marcellus shale region of Pennsylvania (U.S.), a region of extensive drilling and hydraulic fracturing. Only one such incident of stream contamination in Pennsylvania has been documented with water quality data in peer-reviewed literature. This could indicate that spills (1) were small or contained on wellpads, (2) were diluted, biodegraded, or obscured by other contaminants, (3) were not detected because of sparse monitoring, or (4) were not detected because of the difficulties of inspecting data for complex stream networks. As a first step in addressing the last problem, we developed a geospatial-analysis tool, GeoNet, that analyzes stream networks to detect statistically significant changes between background and potentially impacted sites. GeoNet was used on data in the Water Quality Portal for the Pennsylvania Marcellus region. With the most stringent statistical tests, GeoNet detected 0.2% to 2% of the known contamination incidents (Na ± Cl) in streams. With denser sensor networks, tools like GeoNet could allow real-time detection of polluting events.

Model-Based Clustering of Nonparametric Weighted Networks with Application to Water Pollution Analysis.

Water pollution is a major global environmental problem, and it poses a great environmental risk to public health and biological diversity. This work is motivated by assessing the potential environmental threat of coal mining through increased sulfate concentrations in river networks, which do not belong to any simple parametric distribution. However, existing network models mainly focus on binary or discrete networks and weighted networks with known parametric weight distributions. We propose a principled nonparametric weighted network model based on exponential-family random graph models and local likelihood estimation, and study its model-based clustering with application to large-scale water pollution network analysis. We do not require any parametric distribution assumption on network weights. The proposed method greatly extends the methodology and applicability of statistical network models. Furthermore, it is scalable to large and complex networks in large-scale environmental studies. The power of our proposed methods is demonstrated in simulation studies and a real application to sulfate pollution network analysis in Ohio watershed located in Pennsylvania, United States.

Direct intramolecular carbon(sp2)-nitrogen(sp2) reductive elimination from gold(iii).

The reactivity of bidentate AuIII-Cl species, [(C^N)AuCl2], with a bisphosphine or carbon donor ligands results in reductive elimination. Combined experimental and computational investigations lead to the first evidence of a direct intramolecular C(sp2)-N(sp2) bond formation from a monomeric [(C^N)AuCl2] gold(iii) complex. We show that bidentate ligated Au(iii) systems bypass transmetallation to form C(sp2)-N(sp2) species and NHC-Au-Cl. Mechanistic investigations of the reported transformation reveal a ligand-induced reductive elimination via a key AuIII intermediate. Kinetic studies of the reaction support a second-order rate process.

Assessing changes in groundwater chemistry in landscapes with more than 100 years of oil and gas development.

With recent improvements in high-volume hydraulic fracturing (HVHF, known to the public as fracking), vast new reservoirs of natural gas and oil are now being tapped. As HVHF has expanded into the populous northeastern USA, some residents have become concerned about impacts on water quality. Scientists have addressed this concern by investigating individual case studies or by statistically assessing the rate of problems. In general, however, lack of access to new or historical water quality data hinders the latter assessments. We introduce a new statistical approach to assess water quality datasets - especially sets that differ in data volume and variance - and apply the technique to one region of intense shale gas development in northeastern Pennsylvania (PA) and one with fewer shale gas wells in northwestern PA. The new analysis for the intensely developed region corroborates an earlier analysis based on a different statistical test: in that area, changes in groundwater chemistry show no degradation despite that area's dense development of shale gas. In contrast, in the region with fewer shale gas wells, we observe slight but statistically significant increases in concentrations in some solutes in groundwaters. One potential explanation for the slight changes in groundwater chemistry in that area (northwestern PA) is that it is the regional focus of the earliest commercial development of conventional oil and gas (O&G) in the USA. Alternate explanations include the use of brines from conventional O&G wells as well as other salt mixtures on roads in that area for dust abatement or de-icing, respectively.

Detecting the effects of coal mining, acid rain, and natural gas extraction in Appalachian basin streams in Pennsylvania (USA) through analysis of barium and sulfate concentrations.

To understand how extraction of different energy sources impacts water resources requires assessment of how water chemistry has changed in comparison with the background values of pristine streams. With such understanding, we can develop better water quality standards and ecological interpretations. However, determination of pristine background chemistry is difficult in areas with heavy human impact. To learn to do this, we compiled a master dataset of sulfate and barium concentrations ([SO4], [Ba]) in Pennsylvania (PA, USA) streams from publically available sources. These elements were chosen because they can represent contamination related to oil/gas and coal, respectively. We applied changepoint analysis (i.e., likelihood ratio test) to identify pristine streams, which we defined as streams with a low variability in concentrations as measured over years. From these pristine streams, we estimated the baseline concentrations for major bedrock types in PA. Overall, we found that 48,471 data values are available for [SO4] from 1904 to 2014 and 3243 data for [Ba] from 1963 to 2014. Statewide [SO4] baseline was estimated to be 15.8 ± 9.6 mg/L, but values range from 12.4 to 26.7 mg/L for different bedrock types. The statewide [Ba] baseline is 27.7 ± 10.6 µg/L and values range from 25.8 to 38.7 µg/L. Results show that most increases in [SO4] from the baseline occurred in areas with intensive coal mining activities, confirming previous studies. Sulfate inputs from acid rain were also documented. Slight increases in [Ba] since 2007 and higher [Ba] in areas with higher densities of gas wells when compared to other areas could document impacts from shale gas development, the prevalence of basin brines, or decreases in acid rain and its coupled effects on [Ba] related to barite solubility. The largest impacts on PA stream [Ba] and [SO4] are related to releases from coal mining or burning rather than oil and gas development.

Asymmetric Flows in the Intercellular Membrane during Cytokinesis.

Eukaryotic cells undergo shape changes during their division and growth. This involves flow of material both in the cell membrane and in the cytoskeletal layer beneath the membrane. Such flows result in redistribution of phospholipid at the cell surface and actomyosin in the cortex. Here we focus on the growth of the intercellular surface during cell division in a Caenorhabditis elegans embryo. The growth of this surface leads to the formation of a double-layer of separating membranes between the two daughter cells. The division plane typically has a circular periphery and the growth starts from the periphery as a membrane invagination, which grows radially inward like the shutter of a camera. The growth is typically not concentric, in the sense that the closing internal ring is located off-center. Cytoskeletal proteins anillin and septin have been found to be responsible for initiating and maintaining the asymmetry of ring closure but the role of possible asymmetry in the material flow into the growing membrane has not been investigated yet. Motivated by experimental evidence of such flow asymmetry, here we explore the patterns of internal ring closure in the growing membrane in response to asymmetric boundary fluxes. We highlight the importance of the flow asymmetry by showing that many of the asymmetric growth patterns observed experimentally can be reproduced by our model, which incorporates the viscous nature of the membrane and contractility of the associated cortex.

Bayesian approach of nearfield acoustic reconstruction with particle filters.

This paper demonstrates that inverse source reconstruction can be performed using a methodology of particle filters that relies primarily on the Bayesian approach of parameter estimation. In particular, the proposed approach is applied in the context of nearfield acoustic holography based on the equivalent source method (ESM). A state-space model is formulated in light of the ESM. The parameters to estimate are amplitudes and locations of the equivalent sources. The parameters constitute the state vector which follows a first-order Markov process with the transition matrix being the identity for every frequency-domain data frame. Filtered estimates of the state vector obtained are assigned weights adaptively. The implementation of recursive Bayesian filters involves a sequential Monte Carlo sampling procedure that treats the estimates as point masses with a discrete probability mass function (PMF) which evolves with iteration. The weight update equation governs the evolution of this PMF and depends primarily on the likelihood function and the prior distribution. It is evident from the simulation results that the inclusion of the appropriate prior distribution is crucial in the parameter estimation.