Predicting early discharge from hospital after liver transplantation (ERDALT) at a single center: a new model
Journal Title: Annals of Hepatology - Year 2015, Vol 14, Issue 6
Abstract
Background & rationale. Limited information related to Liver Transplantation (LT) costs in South America exists. Additionally, costs analysis from developed countries may not provide comparable models for those in emerging economies. We sought to evaluate a predictive model of Early Discharge from Hospital after LT (ERDALT = length of hospital stay ≤ 8 days). A predictive model was assessed based on the odds ratios (OR) from a multivariate regression analysis in a cohort of consecutively transplanted adult patients in a single center from Argentina and internally validated with bootstrapping technique. Results. ERDALT was applicable in 34 of 289 patients (11.8%). Variables independently associated with ERDALT were MELD exception points OR 1.9 (P = 0.04), surgery time < 4 h OR 3.8 (P = 0.013), < 5 units of blood products consumption (BPC) OR 3.5 (P = 0.001) and early weaning from mechanical intubation OR 6.3 (P = 0.006). Points in the predictive scoring model were allocated as follows: MELD exception points (absence = 0 points, presence = 1 point), surgery time < 4 h (0-2 points), < 5 units of BPC (0-2 points), and early weaning (0-3 points). Final scores ranged from 0 to 8 points with a c-statistic of 0.83 (95% CI 0.77-0.90; P < 0.0001). Transplant costs were significantly lower in patients with ERDALT (median $23,078 vs. $28,986; P < 0.0001). Neither lower patient and graft survival, nor higher rates of short-term re-hospitalization and acute rejection events after discharge were observed in patients with ERDALT. In conclusion, the ERDALT score identifies patients suitable for early discharge with excellent outcomes after transplantation. This score may provide applicable models particularly for emerging economies.
Authors and Affiliations
Federico Piñero, Martín Fauda, Rodolfo Quiros, Manuel Mendizabal, Ariel González-Campaña, Demian Czerwonko, Mariano Barreiro, Silvina Montal, Ezequiel Silberman, Matías Coronel, Fernando Cacheiro, Pía Raffa, Oscar Andriani, Marcelo Silva, Luis Podestá
Keywords
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- EP ID EP78514
- DOI 10.5604/16652681.1171770
- Views 104
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