Medicine and Health Sciences Commons^™

Aggressive Diuresis And Severity-Adjusted Length Of Hospital Stay In Acute Congestive Heart Failure Patients, Muhammad U. Butt

Theses and Dissertations--Clinical Research Design

To see if aggressive diuresis in first twenty four hours is associated with a comparable number of total days in the hospital as compared to non-aggressive diuresis. In this retrospective cohort study, we compared the length of hospital stay of consecutive patients admitted in one year based on their diuresis during the first twenty-four hours of hospitalization: aggressive diuresis (group 1) i.e. > 2400mL versus non-aggressive diuresis (group 2) i.e. ≤ 2400mL urine output. Patients were excluded if in cardiogenic shock, had creatinine level above 3 mg/dL on admission, or on dialysis. A total of 194 patients were enrolled (29 in …

Using Prescription Drug Monitoring Data To Inform Population Level Analysis Of Opioid Analgesic Utilization, Huong T. T. Luu

Theses and Dissertations--Epidemiology and Biostatistics

Increased opioid analgesic (OA) prescribing has been associated with increased risk of prescription opioid diversion, misuse, and abuse. States established prescription drug monitoring programs (PDMPs) to collect and analyze electronic records for dispensed controlled substances to reduce prescription drug abuse and diversion. PDMP data can be used by prescribers for tracking patient’s history of controlled substance prescribing to inform clinical decisions.

The studies in this dissertation are focused on the less utilized potential of the PDMP data to enhance public health surveillance to monitor OA prescribing and co-prescribing and association with opioid overdose mortality and morbidity. Longitudinal analysis of OA …

Investigating The Role Of Prescription Drug Monitoring Programs In Reducing Rates Of Opioid-Related Poisonings, Nathan James Pauly

Theses and Dissertations--Pharmacy

The United States is in the midst of an opioid epidemic. In addition to other system level interventions, almost all states have responded to the crisis by implementing prescription drug monitoring programs (PDMPs). PDMPs are state-level interventions that track the dispensing of Controlled Substances. Data generated at the time of medication dispensing is uploaded to a central data server that may be used to assist in identifying drug diversion, medication misuse, or potentially aberrant prescribing practices.

Prior studies assessing the impact of PDMPs on trends in opioid-related morbidity have often failed to take into account the wide heterogeneity of program …

Using The Qbest Equation To Evaluate Ellagic Acid Safety Data: Generating A Qnoael With Confidence Levels From Disparate Literature, Cynthia Rose Dickerson

Theses and Dissertations--Pharmacy

QBEST, a novel statistical method, can be applied to the problem of estimating the No Observed Adverse Effect Level (NOAEL or QNOAEL) of a New Molecular Entity (NME) in order to anticipate a safe starting dose for beginning clinical trials. The NOAEL from QBEST (called the QNOAEL) can be calculated using multiple disparate studies in the literature and/or from the lab. The QNOAEL is similar in some ways to the Benchmark Dose Method (BMD) used widely in toxicological research, but is superior to the BMD in some ways. The QNOAEL simulation generates an intuitive curve that is comparable to the …

Scalable Feature Selection And Extraction With Applications In Kinase Polypharmacology, Derek Jones

Theses and Dissertations--Computer Science

In order to reduce the time associated with and the costs of drug discovery, machine learning is being used to automate much of the work in this process. However the size and complex nature of molecular data makes the application of machine learning especially challenging. Much work must go into the process of engineering features that are then used to train machine learning models, costing considerable amounts of time and requiring the knowledge of domain experts to be most effective. The purpose of this work is to demonstrate data driven approaches to perform the feature selection and extraction steps in …