A community approach to mortality prediction in sepsis via gene expression analysis.

Improved risk stratification and prognosis prediction in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here, we present prognostic models for 30-day mortality generated independently by three scientific groups by using 12 discovery cohorts containing transcriptomic data collected from primarily community-onset sepsis patients. Predictive performance is validated in five cohorts of community-onset sepsis patients in which the models show summary AUROCs ranging from 0.765-0.89. Similar performance is observed in four cohorts of hospital-acquired sepsis. Combining the new gene-expression-based prognostic models with prior clinical severity scores leads to significant improvement in prediction of 30-day mortality as measured via AUROC and net reclassification improvement index These models provide an opportunity to develop molecular bedside tests that may improve risk stratification and mortality prediction in patients with sepsis.y NIGMS Glue Grant Legacy Award R24GM102656. J.F.B.-M., R.A., and E.T. were supported by Instituto de Salud Carlos III (grants EMER07/050, PI13/02110, PI16/01156). R.J.L. was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR001417. The CAPSOD study was supported by NIH (U01AI066569, P20RR016480, HHSN266200400064C). P.K. is supported by grants from Bill Melinda Gates Foundation, R01 AI125197-01, 1U19AI109662, and U19AI057229, outside the submitted work. The GAinS study was supported by the National Institute for Health Research through the Comprehensive Clinical Research Network for patient recruitment; Wellcome Trust (Grants 074318 [to J.C.K.], and 090532/Z/09/Z [core facilities Wellcome Trust Centre for Human Genetics including High-Throughput Genomics Group]); European Research Council under the European Union’s Seventh Framework Programme (FP7/2007–2013)/ERC Grant agreement no. 281824 (to J.C.K.), the Medical Research Council (98082 [to J.C.K.]); UK Intensive Care Society; and NIHR Oxford Biomedical Research Centre. The Duke HAI study was supported by a research agreement between Duke University and Novartis Vaccines and Diagnostics, Inc. According to the terms of the agreement, representatives of the sponsor had an opportunity to review and comment on a draft of the manuscript. The authors had full control of the analyses, the preparation of the manuscript, and the decision to submit the manuscript for publication. For the University of Florida ‘P50’ Study, data were obtained from the Sepsis and Critically Illness Research Center (SCIRC) at the University of Florida College of Medicine, which is supported in part by NIGMS P50 GM111152. This work was supported by Defense Advanced Research Projects Agency and the Army Research Office through Grant W911NF-15-1-0107.

Detecting short-term change and variation in health-related quality of life: within- and between-person factor structure of the SF-36 health survey

BACKGROUND: A major goal of much aging-related research and geriatric medicine is to identify early changes in health and functioning before serious limitations develop. To this end, regular collection of patient-reported outcome measure (PROMs) in a clinical setting may be useful to identify and monitor these changes. However, existing PROMs were not designed for repeated administration and are more commonly used as one-time screening tools; as such, their ability to detect variation and measurement properties when administered repeatedly remain unknown. In this study we evaluated the potential of the RAND SF-36 Health Survey as a repeated-use PROM by examining its measurement properties when modified for administration over multiple occasions. METHODS: To distinguish between-person (i.e., average) from within-person (i.e., occasion) levels, the SF-36 Health Survey was completed by a sample of older adults (N = 122, M(age) = 66.28 years) daily for seven consecutive days. Multilevel confirmatory factor analysis (CFA) was employed to investigate the factor structure at both levels for two- and eight-factor solutions. RESULTS: Multilevel CFA models revealed that the correlated eight-factor solution provided better model fit than the two-factor solution at both the between-person and within-person levels. Overall model fit for the SF-36 Health Survey administered daily was not substantially different from standard survey administration, though both were below optimal levels as reported in the literature. However, individual subscales did demonstrate good reliability. CONCLUSIONS: Many of the subscales of the modified SF-36 for repeated daily assessment were found to be sufficiently reliable for use in repeated measurement designs incorporating PROMs, though the overall scale may not be optimal. We encourage future work to investigate the utility of the subscales in specific contexts, as well as the measurement properties of other existing PROMs when administered in a repeated measures design. The development and integration of new measures for this purpose may ultimately be necessary

How do plants achieve immunity? Defence without specialized immune cells

Vertebrates have evolved a sophisticated adaptive immune system that relies on an almost infinite diversity of antigen receptors that are clonally expressed by specialized immune cells that roam the circulatory system. These immune cells provide vertebrates with extraordinary antigen-specific immune capacity and memory, while minimizing self-reactivity. Plants, however, lack specialized mobile immune cells. Instead, every plant cell is thought to be capable of launching an effective immune response. So how do plants achieve specific, self-tolerant immunity and establish immune memory? Recent developments point towards a multilayered plant innate immune system comprised of self-surveillance, systemic signalling and chromosomal changes that together establish effective immunity