The Gene Expression Barcode project, http://barcode.luhs.org, seeks to determine the genes expressed for every tissue and cell type in humans and mice. Understanding the absolute expression of genes across tissues and cell types has applications in basic cell biology, hypothesis generation for gene function and clinical predictions using gene expression signatures. In its current version, this project uses the abundant publicly available microarray data sets combined with a suite of single-array preprocessing, quality control and analysis methods. In this article, we present the improvements that have been made since the previous version of the Gene Expression Barcode in 2011. These include a variety of new data mining tools and summaries, estimated transcriptomes and curated annotations.

This study examines health outcomes in burn patients with sepsis. We hypothesized that burn patients with sepsis would have an increased odds risk for in-hospital death and longer intensive care unit (ICU) stays. This was a retrospective cohort of consecutive patients admitted to the burn ICU with total BSA (TBSA) ≥10% and/or inhalation injury between January 2008 and March 2015. Overall 407 burn patients were included; the case-rate for sepsis was 39.1% (n = 159); 20.1% (n = 82) patients were septic and 18.9% (n = 77) patients experienced septic shock. Patients with septic shock had the highest mortality rate (13.31% no sepsis vs 3.7% sepsis vs 49.4% septic shock, P < .01). Median 28-day ICU-free days was higher in patients without sepsis (23 days [Interquartile range (IQR) 14–27] no sepsis vs 0 days [IQR 0–10] sepsis vs 0 days [IQR 0–0] septic shock, P < .01). Sepsis (with or without shock) increased odds of in-hospital death (odds ratio 7.04, 95% confidence interval 1.93–25.7) in reference to the no sepsis group. With each incremental Sequential Organ Failure Assessment (SOFA) score or 10% TBSA increase, the odds risk for in-hospital death increased by 56 and 75%, respectively. Our study characterized outcomes in patients with sepsis after severe burn injury. The odds risk for in-hospital death was greater in patients with sepsis, increasing burn severity according to TBSA and SOFA score.

Objective To develop an algorithm to identify sepsis and sepsis with organ dysfunction/septic shock in burn-injured patients incorporating criteria from the American Burn Association sepsis definition that possesses good test characteristics compared to ICD-9 codes and an algorithm previously validated in non-burn injured septic patients (Martin et al method). Methods This was a retrospective cohort study of consecutive patients admitted to the burn intensive care unit between January 2008 and March 2015. Results Of the 4761 admitted, 8.6% (n=407) met inclusion criteria, of which the case rate for sepsis was 34.2% (n=139; n=48 sepsis; n=91 sepsis with organ dysfunction/septic shock). For sepsis identification, the novel algorithm had an accuracy of 86.0% (95% CI 82.2% – 89.2%), sensitivity of 66.9% (95% CI 59.1% – 74.7%) and specificity of 95.9% (95% CI 93.5% – 98.3%). The novel algorithm had better discrimination (0.81, 95% CI 0.77–0.86) than the ICD-9 method (0.77, 95% CI 0.73–0.81) although this was not significant (p=0.08). For sepsis with organ dysfunction/septic shock, the novel algorithm plus vasopressors (0.67, 95%CI 0.63–0.72) and the ICD-9 method (0.63, 95%CI 0.58–0.68) performed equivocal (p=0.15) but the Martin method (0.76, 95% CI 0.71–0.81) had superior discrimination than other methods (p<0.01). Conclusions The novel algorithm is an accurate and simple tool to identify sepsis in the burn cohort with good sensitivity and specificity and equivocal discriminative ability to ICD-9 coding. The Martin method had superior discriminative ability for identifying sepsis with organ dysfunction/septic shock in burn-injured patients than either the novel algorithm plus vasopressors or ICD-9 coding.