Outcomes of Acute Chest Syndrome in Adult Patients with Sickle Cell Disease: Predictors of Mortality

Unlabelled: Adults with sickle cell disease(SCD) are a growing population. Recent national estimates of outcomes in acute chest syndrome(ACS) among adults with SCD are lacking. We describe the incidence, outcomes and predictors of mortality in ACS in adults. We hypothesize that any need for mechanical ventilation is an independent predictor of mortality.

Methods: We performed a retrospective analysis of the Nationwide Inpatient Sample(2004-2010),the largest all payer inpatient database in United States, to estimate the incidence and outcomes of ACS needing mechanical ventilation(MV) and exchange transfusion(ET) in patients >21 years. The effects of MV and ET on outcomes including length of stay(LOS) and in-hospital mortality(IHM) were examined using multivariable linear and logistic regression models respectively. The effects of age, sex, race, type of sickle cell crisis, race, co-morbid burden, insurance status, type of admission, and hospital characteristics were adjusted in the regression models.

Results: Of the 24,699 hospitalizations, 4.6% needed MV(2.7% for <96 hours, 1.9% for ≥96 hours), 6% had ET, with a mean length of stay(LOS) of 7.8 days and an in-hospital mortality rate(IHM) of 1.6%. There was a gradual yearly increase in ACS hospitalizations that needed MV(2.6% in 2004 to 5.8% in 2010). Hb-SS disease was the phenotype in 84.3% of all hospitalizations. After adjusting for a multitude of patient and hospital related factors, patients who had MV for <96 hours(OR = 67.53,p<0.01) or those who had MV for ≥96 hours(OR = 8.73,p<0.01) were associated with a significantly higher odds for IHM when compared to their counterparts. Patients who had MV for ≥96 hours and those who had ET had a significantly longer LOS in-hospitals(p<0.001).

Conclusion: In this large cohort of hospitalized adults with SCD patients with ACS, the need for mechanical ventilation predicted higher mortality rates and increased hospital resource utilization. Identification of risk factors may enable optimization of outcomes.