New Methodology for an Expert-Designed Map From International Classification of Diseases (ICD) to Abbreviated Injury Scale (AIS) 3+ Severity Injury

Objective: There has been a longstanding desire for a map to convert International Classification of Diseases (ICD) injury codes to Abbreviated Injury Scale (AIS) codes to reflect the severity of those diagnoses. The Association for the Advancement of Automotive Medicine (AAAM) was tasked by European Union representatives to create a categorical map classifying diagnoses codes as serious injury (Abbreviated Injury Scale [AIS] 3+), minor/moderate injury (AIS 1/2), or indeterminate. This study's objective was to map injury-related ICD-9-CM (clinical modification) and ICD-10-CM codes to these severity categories.

Methods: Approximately 19,000 ICD codes were mapped, including injuries from the following categories: amputations, blood vessel injury, burns, crushing injury, dislocations/sprains/strains, foreign body, fractures, internal organ, nerve/spinal cord injury, intracranial, laceration, open wounds, and superficial injury/contusion. Two parallel activities were completed to create the maps: (1) An in-person expert panel and (2) an electronic survey. The panel consisted of expert users of AIS and ICD from North America, the United Kingdom, and Australia. The panel met in person for 5 days, with follow-up virtual meetings to create and revise the maps. Additional qualitative data were documented to resolve potential discrepancies in mapping. The electronic survey was completed by 95 injury coding professionals from North America, Spain, Australia, and New Zealand over 12 weeks. ICD-to-AIS maps were created for: ICD-9-CM and ICD-10-CM. Both maps indicated whether the corresponding AIS 2005/Update 2008 severity score for each ICD code was AIS 3+, 1/2, or indeterminable. Though some ICD codes could be mapped to multiple AIS codes, the maximum severity of all potentially mapped injuries determined the final severity categorization.

Results: The in-person panel consisted of 13 experts, with 11 Certified AIS specialists (CAISS) with a median of 8 years and an average of 15 years of coding experience. Consensus was reached for AIS severity categorization for all injury-related ICD codes. There were 95 survey respondents, with a median of 8 years of injury coding experience. Approximately 15 survey responses were collected per ICD code. Results from the 2 activities were compared, and any discrepancies were resolved using additional qualitative and quantitative data from the in-person panel and survey results, respectively.

Conclusions: Robust maps of ICD-9-CM and ICD-10-CM injury codes to AIS severity categories (3+ versus <3) were successfully created from an in-person panel discussion and electronic survey. These maps provide a link between the common ICD diagnostic lexicons and the AIS severity coding system and are of value to injury researchers, public health scientists, and epidemiologists using large databases without available AIS coding.     

Long‐Term Trends of Nutrients and Sediment from the Nontidal Chesapeake Watershed: An Assessment of Progress by River and Season

To assess historical loads of nitrogen (N), phosphorus (P), and suspended sediment (SS) from the nontidal Chesapeake Bay watershed (NTCBW), we analyzed decadal seasonal trends of flow‐normalized loads at the fall‐line of nine major rivers that account for >90% of NTCBW flow. Evaluations of loads by season revealed N, P, and SS load magnitudes have been highest in January‐March and lowest in July‐September, but the temporal trends have followed similar decadal‐scale patterns in all seasons, with notable exceptions. Generally, total N (TN) load has dropped since the late 1980s, but particulate nutrients and SS have risen since the mid‐1990s. The majority of these rises were from Susquehanna River and relate to diminished net trapping at the Conowingo Reservoir. Substantial rises in SS were also observed, however, in other rivers. Moreover, the summed rise in particulate P load from other rivers is of similar magnitude as from Susquehanna. Dissolved nutrient loads have dropped in the upland (Piedmont and above) rivers, but risen in two small rivers in the Coastal Plain affected by lagged groundwater input. In addition, analysis of fractional contributions revealed consistent N trends across the upland watersheds. Finally, total N:total P ratios have declined in most rivers, suggesting the potential for changes in nutrient limitation. Overall, this integrated study of historical data highlights the value of maintaining long‐term monitoring at multiple watershed locations.     

Modeling Streamflow and Water Quality Sensitivity to Climate Change and Urban Development in 20 U.S. Watersheds

Watershed modeling in 20 large, United States (U.S.) watersheds addresses gaps in our knowledge of streamflow, nutrient (nitrogen and phosphorus), and sediment loading sensitivity to mid‐21st Century climate change and urban/residential development scenarios. Use of a consistent methodology facilitates regional scale comparisons across the study watersheds. Simulations use the Soil and Water Assessment Tool. Climate change scenarios are from the North American Regional Climate Change Assessment Program dynamically downscaled climate model output. Urban and residential development scenarios are from U.S. Environmental Protection Agency's Integrated Climate and Land Use Scenarios project. Simulations provide a plausible set of streamflow and water quality responses to mid‐21st Century climate change across the U.S. Simulated changes show a general pattern of decreasing streamflow volume in the central Rockies and Southwest, and increases on the East Coast and Northern Plains. Changes in pollutant loads follow a similar pattern but with increased variability. Ensemble mean results suggest that by the mid‐21st Century, statistically significant changes in streamflow and total suspended solids loads (relative to baseline conditions) are possible in roughly 30‐40% of study watersheds. These proportions increase to around 60% for total phosphorus and total nitrogen loads. Projected urban/residential development, and watershed responses to development, are small at the large spatial scale of modeling in this study.     

Comparing Green and Grey Infrastructure Using Life Cycle Cost and Environmental Impact: A Rain Garden Case Study in Cincinnati,OH

Green infrastructure (GI) is quickly gaining ground as a less costly, greener alternative to traditional methods of stormwater management. One popular form of GI is the use of rain gardens to capture and treat stormwater. We used life cycle assessment (LCA) to compare environmental impacts of residential rain gardens constructed in the Shepherd's Creek watershed of Cincinnati, Ohio to those from a typical detain and treat system. LCA is an internationally standardized framework for analyzing the potential environmental performance of a product or service by including all stages in its life cycle, including material extraction, manufacturing, use, and disposal. Complementary to the life cycle environmental impact assessment, the life cycle costing approach was adopted to compare the equivalent annual costs of each of these systems. These analyses were supplemented by modeling alternative scenarios to capture the variability in implementing a GI strategy. Our LCA models suggest rain garden costs and impacts are determined by labor requirement; the traditional alternative's impacts are determined largely by the efficiency of wastewater treatment, while costs are determined by the expense of tunnel construction. Gardens were found to be the favorable option, both financially (~42% cost reduction) and environmentally (62‐98% impact reduction). Wastewater utilities may find significant life cycle cost and environmental impact reductions in implementing a rain garden plan.     

Influence of Riparian Seepage Zones on Nitrate Variability in Two Agricultural Headwater Streams

Riparian seeps have been recognized for their contributions to stream flow in headwater catchments, but there is limited data on how seeps affect stream water quality. The objective of this study was to examine the effect of seeps on the variability of stream NO₃‐N concentrations in FD36 and RS, two agricultural catchments in Pennsylvania. Stream samples were collected at 10‐m intervals over reaches of 550 (FD36) and 490 m (RS) on 21 occasions between April 2009 and January 2012. Semi‐variogram analysis was used to quantify longitudinal patterns in stream NO₃‐N concentration. Seep water was collected at 14 sites in FD36 and 7 in RS, but the number of flowing seeps depended on antecedent conditions. Seep NO₃‐N concentrations were variable (0.1‐29.5 mg/l) and were often greater downslope of cropped fields compared to other land uses. During base flow, longitudinal variability in stream NO₃‐N concentrations increased as the number of flowing seeps increased. The influence of seeps on the variability of stream NO₃‐N concentrations was less during storm flow compared to the variability of base flow NO₃‐N concentrations. However, 24 h after a storm in FD36, an increase in the number of flowing seeps and decreasing streamflow resulted in the greatest longitudinal variability in stream NO₃‐N concentrations recorded. Results indicate seeps are important areas of NO₃‐N delivery to streams where targeted adoption of mitigation measures may substantially improve stream water quality.     

The Kinetics of Interesterfication on Waste Cooking Oil (Sunflower Oil) for the Production of Fatty Acid Alkyl Esters using a Whole Cell Biocatalyst (Rhizopus oryzae) and Pure Lipase Enzyme

Recent research and technology have provided promising outcomes to rely on biodiesel as the alternative and conventional source of fuel. The use of renewable sources constitutes the main stream of research. Waste Cooking Oil (WCO) was used for biodiesel production in this study. Lipase enzyme producing fungi Rhizopus oryzae 262 and commercially available pure lipase enzyme were used for comparative study in the production of FAAE. The whole cell biocatalyst and pure enzyme were immobilized using calcium alginate beads. It was prepared by optimizing with different molar ratios of calcium chloride and different percent sodium alginate. Entrapment immobilization was done for whole cell biocatalyst. PE was also immobilized by entrapment for the transesterification reaction. Four different solvents methanol, ethanol, n-propanol, n-butanol were used as the acyl acceptors. The reaction parameters like temperature, molar ratio, reaction time, and amount of enzyme to be used were also optimized for methanol alone. The same parameters were adopted for the other acyl acceptors too. Among the different acyl acceptors, methanol whose reaction parameters were optimized showed maximum conversion of triglycerides to FAAE - 94% with PE and 84% with WCB. On the whole, PE showed better catalytic converting ability with all the acyl acceptor compared to WCB, further study, it was observed that three consecutive and reversible reactions occurred in the interesterification of triglycerides. So, a kinetic model based on Michaelis-Menten equation with competitive substrate inhibition was used to find the maximum reaction rate V_i for the four solvents using pure enzyme and WCB.     

Development and Operational Testing of a Super‐Ensemble Artificial Intelligence Flood‐Forecast Model for a Pacific Northwest River

Coastal catchments in British Columbia, Canada, experience a complex mixture of rainfall‐ and snowmelt‐driven contributions to flood events. Few operational flood‐forecast models are available in the region. Here, we integrated a number of proven technologies in a novel way to produce a super‐ensemble forecast system for the Englishman River, a flood‐prone stream on Vancouver Island. This three‐day‐ahead modeling system utilizes up to 42 numerical weather prediction model outputs from the North American Ensemble Forecast System, combined with six artificial neural network‐based streamflow models representing various slightly different system conceptualizations, all of which were trained exclusively on historical high‐flow data. As such, the system combines relatively low model development times and costs with the generation of fully probabilistic forecasts reflecting uncertainty in the simulation of both atmospheric and terrestrial hydrologic dynamics. Results from operational testing by British Columbia's flood forecasting agency during the 2013‐2014 storm season suggest that the prediction system is operationally useful and robust.