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Machine-Learning-Based Prediction Of Sepsis Events From Vertical Clinical Trial Data: A Naïve Approach, Tyler Michael Gaddis

Theses and Dissertations

Sepsis is a potentially life-threatening condition characterized by a dysregulated, disproportionate immune response to infection by which the afflicted body attacks its own tissues, sometimes to the point of organ failure, and in the worst cases, death. According to the Centers for Disease Control and Prevention (CDC) Sepsis is reported to kill upwards of 270,000 Americans annually, though this figure may be greater given certain ambiguities in the current accepted diagnostic framework of the disease.

This study attempted to first establish an understanding of past definitions of sepsis, and to then recommend use of machine learning as integral in an …

Aging With Hiv In The United States: Trends And Impact Of Hospital Stays On Inpatient Resource Utilization, And Costs Of Care, 2003-2015, Khairul Alam Siddiqi

Theses and Dissertations

Background:

Due to advances in Antiretroviral Therapy (ART), people living with HIV (PLWH) live longer in the United States. Aging prolongs exposure to HIV and antiretroviral drugs, which could lead to an elevated risk of developing multiple age-related comorbidities [HIV Associated Non-AIDS (HANA) conditions], earlier for PLWH. Higher comorbidity burdens among older PLWH may require greater use of inpatient care, i.e., higher hospitalization, inpatient resource utilization, and costs. This study examined the trends and characteristics of comorbidities, resource utilization, and costs of hospital stays with HIV (HSWH) compared to hospital stays without HIV (HSWOH). We also assessed trends for resource …