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BackgroundThe objective of this study was to evaluate the ability of endothelial biomarkers to early predict clinical deterioration of patients admitted to the emergency department (ED) with a suspected sepsis. This was a prospective, multicentre, international study conducted in EDs. Adult patients with suspected acute bacterial infection and sepsis were enrolled but only those with confirmed infection were analysed. The kinetics of biomarkers and organ dysfunction were collected at T0, T6 and T24 hours after ED admission to assess prognostic performances of sVEGFR2, suPAR and procalcitonin (PCT). The primary outcome was the deterioration within 72 h and was defined as a composite of relevant outcomes such as death, intensive care unit admission and/or SOFA score increase validated by an independent adjudication committee.ResultsAfter adjudication of 602 patients, 462 were analysed including 124 who deteriorated (27%). On admission, those who deteriorated were significantly older (73 [60–82] vs 63 [45–78] y-o, p < 0.001) and presented significantly higher SOFA scores (2.15 ± 1.61 vs 1.56 ± 1.40, p = 0.003). At T0, sVEGFR2 (5794 [5026–6788] vs 6681 [5516–8059], p < 0.0001), suPAR (6.04 [4.42–8.85] vs 4.68 [3.50–6.43], p < 0.0001) and PCT (7.8 ± 25.0 vs 5.4 ± 17.9 ng/mL, p = 0.001) were associated with clinical deterioration. In multivariate analysis, low sVEGFR2 expression and high suPAR and PCT levels were significantly associated with early deterioration, independently of confounding parameters (sVEGFR2, OR = 1.53 [1.07–2.23], p < 0.001; suPAR, OR = 1.57 [1.21–2.07], p = 0.003; PCT, OR = 1.10 [1.04–1.17], p = 0.0019). Combination of sVEGFR2 and suPAR had the best prognostic performance (AUC = 0.7 [0.65–0.75]) compared to clinical or biological variables.ConclusionssVEGFR2, either alone or combined with suPAR, seems of interest to predict deterioration of patients with suspected bacterial acute infection upon ED admission and could help front-line physicians in the triage process.

PurposeFine sediment deposition is an important component of the catchment sediment budget and affects river morphology, biology, and contaminant transfer. However, the driving factors of fine sediment deposition remain poorly understood at the catchment scale, limiting our ability to model this process.MethodsFine sediment deposition and river reach characteristics were collected over the entire river network of three medium-sized (200–2200 km2) temperate catchments, corresponding to 11,302 river reaches. This unique database was analyzed and used to develop and evaluate a random forest model. The model was used to predict sediment deposition and analyze its driving factors.ResultsFine sediment deposition displayed a high spatial variability and a weak but significant relationship with the Strahler order and river reach width (Pearson coefficient r =  −0.4 and 0.4, respectively), indicating the likely nonlinear influence of river reach characteristics. The random forest model predicted fine sediment deposition intensity with an accuracy of 81%, depending on the availability of training data. Bed substrate granularity, flow condition, reach depth and width, and the proportion of cropland and forest were the six most influential variables on fine sediment deposition intensity, suggesting the importance of both hillslope and within-river channel processes in controlling fine sediment deposition.ConclusionThis study presented and analyzed a unique dataset. It also demonstrated the potential of random forest approaches to predict fine sediment deposition at the catchment scale. The proposed approach is complementary to measurements and process-based models. It may be useful for improving the understanding of sediment connectivity in catchments, the design of future measurement campaigns, and help prioritize areas to implement mitigation strategies.