Research in the effects of climate change on plant disease continues to be limited, but some striking progress has been made. At the genomic level, advances in technologies for the high-throughput analysis of gene expression have made it possible to begin discriminating responses to different biotic and abiotic stressors and potential trade-offs in responses. At the scale of the individual plant, enough experiments have been performed to begin synthesizing the effects of climate variables on infection rates, though pathosystemspecific characteristics make synthesis challenging. Models of plant disease have now been developed to incorporate more sophisticated climate predictions. At the population level, the adaptive potential of plant and pathogen populations may prove to be one of the most important predictors of the magnitude of climate change effects. Ecosystem ecologists are now addressing the role of plant disease in ecosystem processes and the challenge of scaling up from individual infection probabilities to epidemics and broader impacts.

We developed and tested a gene expression-based classification method for pediatric septic shock that meets the time constraints of the critical care environment, and can potentially inform therapeutic decisions.

Objective PERSEVERE, a pediatric sepsis risk model, uses biomarkers to estimate baseline mortality risk for pediatric septic shock. It is unknown how PERSEVERE performs within distinct septic shock phenotypes. We tested PERSEVERE in children with septic shock and thrombocytopenia-associated multiple organ failure (TAMOF), and in those without new onset thrombocytopenia but with multiple organ failure (MOF). Design PERSEVERE-based mortality risk was generated for each study subject (n = 660). A priori, we determined that if PERSEVERE did not perform well in both the TAMOF and MOF cohorts, we would revise PERSEVERE to incorporate admission platelet counts. Setting Multiple pediatric intensive care units in the United States. Interventions Standard care. Measurements and Main Results PERSEVERE performed well in the TAMOF cohort (AUC 0.84 [95% CI: 0.77 – 0.90]), but less well in the MOF cohort (AUC 0.71; [0.61 – 0.80]). PERSEVERE was revised using 424 subjects previously reported in the derivation phase. PERSEVERE-II had an AUC of 0.89 (0.85 – 0.93) and performed equally well across TAMOF and MOF cohorts. PERSEVERE-II performed well when tested in 236 newly enrolled subjects. Sample size calculations for a clinical trial testing the efficacy of plasma exchange for children with septic shock and TAMOF indicated PERSEVERE-II-based stratification could substantially reduce the number of patients necessary, when compared to no stratification. Conclusions Testing PERSEVERE in the context of septic shock phenotypes prompted a revision incorporating platelet count. PERSEVERE-II performs well upon testing, independent of TAMOF or MOF status. PERSEVERE-II could potentially serve as a prognostic enrichment tool.

BackgroundThe potential benefits of corticosteroids for septic shock may depend on initial mortality risk.ObjectiveWe determined associations between corticosteroids and outcomes in children with septic shock who were stratified by initial mortality risk.MethodsWe conducted a retrospective analysis of an ongoing, multi-center pediatric septic shock clinical and biological database. Using a validated biomarker-based stratification tool (PERSEVERE), 496 subjects were stratified into three initial mortality risk strata (low, intermediate, and high). Subjects receiving corticosteroids during the initial 7 days of admission (n = 252) were compared to subjects who did not receive corticosteroids (n = 244). Logistic regression was used to model the effects of corticosteroids on 28-day mortality and complicated course, defined as death within 28 days or persistence of two or more organ failures at 7 days.ResultsSubjects who received corticosteroids had greater organ failure burden, higher illness severity, higher mortality, and a greater requirement for vasoactive medications, compared to subjects who did not receive corticosteroids. PERSEVERE-based mortality risk did not differ between the two groups. For the entire cohort, corticosteroids were associated with increased risk of mortality (OR 2.3, 95% CI 1.3–4.0, p = 0.004) and a complicated course (OR 1.7, 95% CI 1.1–2.5, p = 0.012). Within each PERSEVERE-based stratum, corticosteroid administration was not associated with improved outcomes. Similarly, corticosteroid administration was not associated with improved outcomes among patients with no comorbidities, nor in groups of patients stratified by PRISM.ConclusionsRisk stratified analysis failed to demonstrate any benefit from corticosteroids in this pediatric septic shock cohort.

Objective The development of acute kidney injury in patients with sepsis is associated with worse outcomes. Identifying those at risk for septic acute kidney injury could help to inform clinical decision making. We derived and tested a multibiomarker-based model to estimate the risk of septic acute kidney injury in children with septic shock. Design Candidate serum protein septic acute kidney injury biomarkers were identified from previous transcriptomic studies. Model derivation involved measuring these biomarkers in serum samples from 241 subjects with septic shock obtained during the first 24 hours of admission and then using a Classification and Regression Tree approach to estimate the probability of septic acute kidney injury 3 days after the onset of septic shock, defined as at least two-fold increase from baseline serum creatinine. The model was then tested in a separate cohort of 200 subjects. Setting Multiple PICUs in the United States. Interventions None other than standard care. Measurements and Main Results The decision tree included a first-level decision node based on day 1 septic acute kidney injury status and five subsequent biomarker-based decision nodes. The area under the curve for the tree was 0.95 (CI95, 0.91–0.99), with a sensitivity of 93% and a specificity of 88%. The tree was superior to day 1 septic acute kidney injury status alone for estimating day 3 septic acute kidney injury risk. In the test cohort, the tree had an area under the curve of 0.83 (0.72–0.95), with a sensitivity of 85% and a specificity of 77% and was also superior to day 1 septic acute kidney injury status alone for estimating day 3 septic acute kidney injury risk. Conclusions We have derived and tested a model to estimate the risk of septic acute kidney injury on day 3 of septic shock using a novel panel of biomarkers. The model had very good performance in a test cohort and has test characteristics supporting clinical utility and further prospective evaluation.