Reduced Mortality and Severe Disability Rates in the SENTIS Trial

The Safety and Efficacy of NeuroFlo Technology in Ischemic Stroke trial showed a trend for reduced all-cause mortality and positive secondary safety end point outcomes. We present further analyses of the mortality and severe disability data from the Safety and Efficacy of NeuroFlo Technology in Ischemic Stroke trial

Shifts in historical streamflow extremes in the Colorado River Basin

The global phenomenon of climate change-induced shifts in precipitation leading to “wet regions getting wetter” and “dry regions getting drier” has been widely studied. However, the propagation of these changes in atmospheric moisture within stream channels is not a direct relationship due to differences in the timing of how changing precipitation patterns interact with various land surfaces. Streamflow is of particular interest in the Colorado River Basin (CRB) due to the region’s rapidly growing population, projected temperature increases that are expected to be higher than elsewhere in the contiguous United States, and subsequent climate-driven disturbances including drought, vegetation mortality, and wildfire, which makes the region more vulnerable to changes in hydrologic extremes. Here, we determine how streamflow extremes have shifted in the CRB using two statistical methods—the Mann-Kendall trend detection analysis and Generalized Extreme Value (GEV) theorem. We evaluate these changes in the context of key flow metrics that include high and low flow percentiles, maximum and minimum 7-day flows, and the center timing of streamflow using historical gage records representative of natural flows. Monthly results indicate declines of up to 41% for high and low flows during the June to July peak runoff season, while increases of up to 24% were observed earlier from March to April. Our results highlight a key threshold elevation and latitude of 2300 m and 39° North, respectively, where there is a distinct shift in the trend. The spatiotemporal patterns observed are indicative of changing snowmelt patterns as a primary cause of the shifts. Identification of how this change varies spatially has consequences for improved land management strategies, as specific regions most vulnerable to threats can be prioritized for mitigation or adaptation as the climate warms

Simulating Human Water Regulation: The Development of an Optimal Complexity, Climate-Adaptive Reservoir Management Model for an LSM

Abstract The widespread influence of reservoirs on global rivers makes representations of reservoir outflow and storage essential components of large-scale hydrology and climate simulations across the land surface and atmosphere. Yet, reservoirs have yet to be commonly integrated into earth system models. This deficiency influences model processes such as evaporation and runoff, which are critical for accurate simulations of the coupled climate system. This study describes the development of a generalized reservoir model capable of reproducing realistic reservoir behavior for future integration in a global land surface model (LSM). Equations of increasing complexity relating reservoir inflow, outflow, and storage were tested for 14 California reservoirs that span a range of spatial and climate regimes. Temperature was employed in model equations to modulate seasonal changes in reservoir management behavior and to allow for the evolution of management seasonality as future climate varies. Optimized parameter values for the best-performing model were generalized based on the ratio of winter inflow to storage capacity so a future LSM user can generate reservoirs in any grid location by specifying the given storage capacity. Model performance statistics show good agreement between observed and simulated reservoir storage and outflow for both calibration (mean normalized RMSE = 0.48; mean coefficient of determination = 0.53) and validation reservoirs (mean normalized RMSE = 0.15; mean coefficient of determination = 0.67). The low complexity of model equations that include climate-adaptive operation features combined with robust model performance show promise for simulations of reservoir impacts on hydrology and climate within an LSM

Simulating Human Water Regulation: The Development of an Optimal Complexity, Climate-Adaptive Reservoir Management Model for an LSM

Abstract The widespread influence of reservoirs on global rivers makes representations of reservoir outflow and storage essential components of large-scale hydrology and climate simulations across the land surface and atmosphere. Yet, reservoirs have yet to be commonly integrated into earth system models. This deficiency influences model processes such as evaporation and runoff, which are critical for accurate simulations of the coupled climate system. This study describes the development of a generalized reservoir model capable of reproducing realistic reservoir behavior for future integration in a global land surface model (LSM). Equations of increasing complexity relating reservoir inflow, outflow, and storage were tested for 14 California reservoirs that span a range of spatial and climate regimes. Temperature was employed in model equations to modulate seasonal changes in reservoir management behavior and to allow for the evolution of management seasonality as future climate varies. Optimized parameter values for the best-performing model were generalized based on the ratio of winter inflow to storage capacity so a future LSM user can generate reservoirs in any grid location by specifying the given storage capacity. Model performance statistics show good agreement between observed and simulated reservoir storage and outflow for both calibration (mean normalized RMSE = 0.48; mean coefficient of determination = 0.53) and validation reservoirs (mean normalized RMSE = 0.15; mean coefficient of determination = 0.67). The low complexity of model equations that include climate-adaptive operation features combined with robust model performance show promise for simulations of reservoir impacts on hydrology and climate within an LSM

Reduced Mortality and Severe Disability Rates in the SENTIS Trial

BACKGROUND AND PURPOSE: The Safety and Efficacy of NeuroFlo Technology in Ischemic Stroke trial showed a trend for reduced all-cause mortality and positive secondary safety end point outcomes. We present further analyses of the mortality and severe disability data from the Safety and Efficacy of NeuroFlo Technology in Ischemic Stroke trial. MATERIALS AND METHODS: The Safety and Efficacy of NeuroFlo Technology in Ischemic Stroke trial was a multicenter, randomized, controlled trial that evaluated the safety and effectiveness of the NeuroFlo catheter in patients with stroke. The current analysis was performed on the as-treated population. All-cause and stroke-related mortality rates at 90 days were compared between groups, and logistic regression models were fit to obtain ORs and 95% CIs for the treated versus not-treated groups. We categorized death-associated serious adverse events as neurologic versus non-neurologic events and performed multiple logistic regression analyses. We analyzed severe disability and mortality by outcomes of the mRS. Patient allocation was gathered by use of a poststudy survey. RESULTS: All-cause mortality trended in favor of treated patients (11.5% versus 16.1%; P = .079) and stroke-related mortality was significantly reduced in treated patients (7.5% versus 14.2%; P = .009). Logistic regression analysis for freedom from stroke-related mortality favored treatment (OR, 2.41; 95% CI, 1.22, 4.77; P = .012). Treated patients had numerically fewer neurologic causes of stroke-related deaths (52.9% versus 73.0%; P = .214). Among the 90-day survivors, nominally fewer treated patients were severely disabled (mRS 5) (5.6% versus 7.5%; OR, 1.72; 95% CI, 0.72, 4.14; P = .223). Differences in allocation of care did not account for the reduced mortality rates. CONCLUSIONS: There were consistent reductions in all-cause and stroke-related mortality in the NeuroFlo-treated patients. This reduction in mortality did not result in an increase in severe disability