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Chest ; 150(6): 1260-1268, 2016 Dec.
Article in English | MEDLINE | ID: mdl-27316558

ABSTRACT

BACKGROUND: Mortality after smoke inhalation-associated acute lung injury (SI-ALI) remains substantial. Age and burn surface area are risk factors of mortality, whereas the impact of patient- and center-level variables and treatments on survival are unknown. METHODS: We performed a retrospective cohort study of burn and non-burn centers at 68 US academic medical centers between 2011 and 2014. Adult inpatients with SI-ALI were identified using an algorithm based on a billing code for respiratory conditions from smoke inhalation who were mechanically ventilated by hospital day 4, with either a length-of-stay ≥ 5 days or death within 4 days of hospitalization. Predictors of in-hospital mortality were identified using logistic regression. The primary outcome was the odds ratio for in-hospital mortality. RESULTS: A total of 769 patients (52.9 ± 18.1 years) with SI-ALI were analyzed. In-hospital mortality was 26% in the SI-ALI cohort and 50% in patients with ≥ 20% surface burns. In addition to age > 60 years (OR 5.1, 95% CI 2.53-10.26) and ≥ 20% burns (OR 8.7, 95% CI 4.55-16.75), additional risk factors of in-hospital mortality included initial vasopressor use (OR 5.0, 95% CI 3.16-7.91), higher diagnostic-related group-based risk-of-mortality assignment and lower hospital bed capacity (OR 2.3, 95% CI 1.23-4.15). Initial empiric antibiotics (OR 0.93, 95% CI 0.58-1.49) did not impact survival. These new risk factors improved mortality prediction by 9.9% (P < .001). CONCLUSIONS: In addition to older age and major surface burns, mortality in SI-ALI is predicted by initial vasopressor use, higher diagnostic-related group-based risk-of-mortality assignment, and care at centers with < 500 beds, but not by initial antibiotic therapy.


Subject(s)
Acute Lung Injury/mortality , Hospital Mortality , Smoke Inhalation Injury/mortality , Academic Medical Centers , Adult , Aged , Algorithms , Female , Humans , Male , Middle Aged , Respiration, Artificial , Retrospective Studies , Risk Factors , Survival Analysis , United States/epidemiology
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