Mortality trends in sickle cell patients.

BACKGROUND: Sickle cell disease affects a significant portion of US patients with African descent. It continues to be one of the leading causes of frequent hospitalizations and high in-hospital morality risk. Until the approval of disease-modifying therapies in last two years, medical therapy has relied mostly on management of pain episodes and the use of hydroxyurea. We discuss the nationwide analysis of trends in in-hospital mortality in patients with Sickle Cell Disease from 2000 to 2014. METHODS: Trends of in-hospital mortality in sickle cell patients were analyzed from a database provided by the Agency of Healthcare Research and Quality. From the data hospitalization rates and in-hospital mortality in categories by region in the US, hospital size, health insurance status, comorbidities and gender were examined. Patterns of in-hospital mortality were analyzed by logistic regression. RESULTS: Ratio for hospitalization and mortality among the four regions described Northeast, Midwest, South, West with respective values of 0.63%, 0.65%, 0.76% and 0.89% with P = 0.008 and OR = 1.07. Odds ratio for sickle cell patients that died during hospitalization and health insurance status was OR = 0.08. Comorbidities considered in sickle cell patients; diabetes mellitus (DM), hypertension (HTN), hyperlipidemia (HLD), chronic kidney disease (CKD), smoking status. The odds ratio for comorbidities show A-fib with a value of OR = 4.47, followed by hypertension OR = 1.92, diabetes mellitus OR = 1.44 and chronic kidney disease OR = 1.29, smoking status OR = 0.60. Mortality-hospitalization ratio by gender was: males 0.77% and females 0.69% with OR = 0.87. CONCLUSIONS: In-hospital mortality by US regions, as well as health insurance status are important measurable elements that show the impact of the disease from a public health perspective. Further and more specific data of regions by states, comorbidities by states and sex, as well as health insurance status by states will provide further insight in local mortality trends.