The 7Q10 in South Carolina Water-Quality Regulation: Nearly Fifty Years Later

2010 S.C. Water Resources Conference - Science and Policy Challenges for a Sustainable Futur

Magnitude and Frequency of Floods in Rural Basins of South Carolina, North Carolina, and Georgia

2008 S.C. Water Resources Conference - Addressing Water Challenges Facing the State and Regio

Analyzing the Effects of the Saluda Dam on the Surface-Water Hydrology of the Congaree National Park Floodplain, South Carolina

2008 S.C. Water Resources Conference - Addressing Water Challenges Facing the State and Regio

Magnitude and Frequency of Urban Floods in the Southeastern United States

2012 S.C. Water Resources Conference - Exploring Opportunities for Collaborative Water Research, Policy and Managemen

Estimating the Magnitude and Frequency of Floods for Urban and Small, Rural Streams in Georgia, South Carolina, and North Carolina

2014 S.C. Water Resources Conference - Informing Strategic Water Planning to Address Natural Resource, Community and Economic Challenge

The Application of Topmodel to Assess Mercury Fluxes in the McTier Creek Watershed

2008 S.C. Water Resources Conference - Addressing Water Challenges Facing the State and Regio

South Carolina Digital Flood Inundation Mapping Pilot Investigation

2012 S.C. Water Resources Conference - Exploring Opportunities for Collaborative Water Research, Policy and Managemen

A Multivariable Model of Parent Satisfaction, Pain, and Opioid Administration in a Pediatric Emergency Department

Introduction: Children and adolescents are not impervious to the unprecedented epidemic of opioid misuse in the United States. In 2016 more than 88,000 adolescents between the ages of 12–17 reported misusing opioid medication, and evidence suggests that there has been a rise in opioid-related mortality for pediatric patients. A major source of prescribed opioids for the treatment of pain is the emergency department (ED). The current study sought to assess the complex relationship between opioid administration, pain severity, and parent satisfaction with children’s care in a pediatric ED. Methods: We examined data from a tertiary pediatric care facility. A health survey questionnaire was administered after ED discharge to capture the outcome of parental likelihood of providing a positive facility rating. We abstracted patient demographic, clinical, and top diagnostic information using electronic health records. Data were merged and multivariable models were constructed. Results: We collected data from 15,895 pediatric patients between the ages of 0–17 years (mean = 6.69; standard deviation = 5.19) and their parents. Approximately 786 (4.94%) patients were administered an opioid; 8212 (51.70%) were administered a non-opioid analgesic; and 3966 (24.95%) expressed clinically significant pain (pain score \u3e/= 4). Results of a multivariable regression analysis from these pediatric patients revealed a three-way interaction of age, pain severity, and opioid administration (odds ratio 1.022, 95% confidence interval, 1.006, 1.038, P = 0.007). Our findings suggest that opioid administration negatively impacted parent satisfaction of older adolescent patients in milder pain who were administered an opioid analgesic, but positively influenced the satisfaction scores of parents of younger children who were administered opioids. When pain levels were severe, the relationship between age and patient experience was not statistically significant. Conclusion: This investigation highlights the complexity of the relationship between opioid administration, pain severity, and satisfaction, and suggests that the impact of opioid administration on parent satisfaction is a function of the age of the child

Repeated measures regression mixture models

Regression mixture models are one increasingly utilized approach for developing theories about and exploring the heterogeneity of effects. In this study we aimed to extend the current use of regression mixtures to a repeated regression mixture method when repeated measures, such as diary-type and experience-sampling method, data are available. We hypothesized that additional information borrowed from the repeated measures would improve the model performance, in terms of class enumeration and accuracy of the parameter estimates. We specifically compared three types of model specifications in regression mixtures: (a) traditional single-outcome model; (b) repeated measures models with three, five, and seven measures; and (c) a single-outcome model with the average of seven repeated measures. The results showed that the repeated measures regression mixture models substantially outperformed the traditional and average single-outcome models in class enumeration, with less bias in the parameter estimates. For sample size, whereas prior recommendations have suggested that regression mixtures require samples of well over 1,000 participants, even for classes at a large distance from each other (classes with regression weights of.20 vs.70), the present repeated measures regression mixture models allow for samples as low as 200 participants with an increased number (i.e., seven) of repeated measures. We also demonstrate an application of the proposed repeated measures approach using data from the Sleep Research Project. Implications and limitations of the study are discussed

Development of a Mercury Load Model for McTier Creek, South Carolina Using TOPMODEL

2012 S.C. Water Resources Conference - Exploring Opportunities for Collaborative Water Research, Policy and Managemen