Abstract

There are few studies on predictors of inpatient mortality in patients with systemic sclerosis (SSc). Knowledge of these predictors is important for the early identification of patients at high risk of inpatient death and for the recognition of modifiable factors. The aim of this study was to define factors associated with greater inpatient mortality in SSc. All admissions coded for SSc (ICD-9-710.1) at the Hospital of University of Pennsylvania, between 2001 and 2011, were reviewed. The diagnosis of SSc was confirmed, and deaths were identified by chart review. For each death, an age, sex, and race matched control with SSc (who did not die during their hospitalization) was identified. We hypothesized group differences in SSc characteristics, non-SSc co-morbidities, and admission labs. Group differences were analyzed using Student's t test as well as Chi(2) tests for dichotomous variables. Exposures associated with death in univariate analyses were used to form a final parsimonious multivariable logistic regression model. After analysis of 658 SSc admissions, 29 cases and 29 matched controls were studied. A significant difference in non-SSc lung disease (p = 0.03), aspiration events (p < 0.01), blood urea nitrogen (BUN) (p < 0.01), and hemoglobin (p = 0.03) was noted between subjects that died compared to matched controls. Odds of death were higher in patients with a higher BUN (OR = 1.06, CI = 1.02-1.11), non-SSc lung disease (OR = 3.87, CI = 1.26-11.88), and aspiration events (OR = 30, CI = 3.58-250.80) and lower in patients with a higher hemoglobin (OR = 0.73, CI = 0.54-0.97). A high BUN, a history of aspiration events, and low Hgb were found to be independently associated with risk of death. A history of lung disease, anemia, renal dysfunction, and aspiration events is associated with higher in-hospital mortality in patients with SSc. The odds of dying in the hospital were 30 times higher among patients with an aspiration event. Stringent measures should be considered to prevent aspiration in at-risk patients.

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