Does red blood cell storage time still influence ICU survival?

Objective: Few studies have shown that aged packed red blood cells (RBC) transfusion negatively influenced the outcome of ICU patients, probably related to storage lesions which could be decreased by leukodepletion of RBC. The purpose of this study was to evaluate the impact of aged leukodepleted-RBC pack, on the outcome of ICU patients. Design: Retrospective, observational, cohort study in a Medical Intensive Care Unit. Patients: Consecutive patients admitted during the years 2005 and 2006, and requiring a transfusion. We recorded patient's demographic data, number of RBC unit and age of each RBC, length of ICU, mortality during ICU stay. Results: Five hundred and thirty-four patients were included with global mortality was 26.6%, length of stay in ICU six days (3-14) and SAPS II 48 (35-62). RBC equaling to 5.9 were transfused per patients (22.7% < 14 days and 57.3% < 21 days). The number of RBC was significantly higher in the dead patients group, but the rate of RBC stored less than 21 days was not different (54% versus 60%; p = 0.21). In a multivariate logistic model, independent predictors of ICU death were SAPS II (OR = 1.02 per point, p < 0.001), number of RBC (OR = 1.08 per RBC, p < 0.001), length of stay in ICU (p < 0.001). Similar results were obtained while introducing the age of RBC as time dependent covariates in a multivariate Cox's model. Conclusions: RBC transfused in our ICU are old. The ICU outcome is independently associated with the number of leucodepleted RBC transfused, but not with their age

Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

Bronchiolitis obliterans syndrome (BOS), the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group), and 26 samples at or after BOS diagnosis (diagnosis group). An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group). We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1), T-cell leukemia/lymphoma protein 1A (TCL1A), and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p &lt; 0.01) and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS