Predictive value of S100-B and copeptin for outcomes following seizure: the BISTRO International Cohort Study.

OBJECTIVE: To evaluate the performance of S100-B protein and copeptin, in addition to clinical variables, in predicting outcomes of patients attending the emergency department (ED) following a seizure. METHODS: We prospectively included adult patients presented with an acute seizure, in four EDs in France and the United Kingdom. Participants were followed up for 28 days. The primary endpoint was a composite of seizure recurrence, all-cause mortality, hospitalization or rehospitalisation, or return visit in the ED within seven days. RESULTS: Among the 389 participants included in the analysis, 156 (40%) experienced the primary endpoint within seven days and 195 (54%) at 28 days. Mean levels of both S100-B (0.11 μg/l [95% CI 0.07-0.20] vs 0.09 μg/l [0.07-0.14]) and copeptin (23 pmol/l [9-104] vs 17 pmol/l [8-43]) were higher in participants meeting the primary endpoint. However, both biomarkers were poorly predictive of the primary outcome with a respective area under the receiving operator characteristic curve of 0.57 [0.51-0.64] and 0.59 [0.54-0.64]. Multivariable logistic regression analysis identified higher age (odds ratio [OR] 1.3 per decade [1.1-1.5]), provoked seizure (OR 4.93 [2.5-9.8]), complex partial seizure (OR 4.09 [1.8-9.1]) and first seizure (OR 1.83 [1.1-3.0]) as independent predictors of the primary outcome. A second regression analysis including the biomarkers showed no additional predictive benefit (S100-B OR 3.89 [0.80-18.9] copeptin OR 1 [1.00-1.00]). CONCLUSION: The plasma biomarkers S100-B and copeptin did not improve prediction of poor outcome following seizure. Higher age, a first seizure, a provoked seizure and a partial complex seizure are independently associated with adverse outcomes

Joint Inversion of Surface-wave Dispersion, P-wave Refraction and Apparent Resistivity Data

We present here a joint-inversion algorithm to build a resistivity, P-wave, and S-wave velocity model from apparent resistivity, surface wave dispersion and P-wave refraction data. This algorithm can also include apriori information available for the site, as well as any physical links among the model parameters, and the result is an internally consistent multi-parametric model. The obtained model resolves more properly the true model because the joint inversion mitigates some problems related to the individual inversion of each type of experimental data like solution non-uniqueness, illness, or lack of resolution, which might lead to interpretation ambiguities. We describe the proposed algorithm and we show the result of its application on a smoothly laterally varying synthetic mode

Differences between acoustic and elastic waveforms for an offshore CO2 storage setting

We investigate the differences between the acoustic and elastic waveforms for streamer seismic data, and discuss the implications in the context of characterization and monitoring of CO2 storage in the offshore setting. For this purpose, we synthesize a set of 2D streamer seismic data by means of both the acoustic and elastic wave equations for the Smeaheia CO2 storage, implemented into an finite-element simulation tool. It is shown that the differences are significant, except very near offset for the current geological setting. Therefore, we recommend to use the elastic waveform for the full waveform inversion application

The TRIAGE-ProADM Score for an Early Risk Stratification of Medical Patients in the Emergency Department - Development Based on a Multi-National, Prospective, Observational Study

INTRODUCTION: The inflammatory biomarker pro-adrenomedullin (ProADM) provides additional prognostic information for the risk stratification of general medical emergency department (ED) patients. The aim of this analysis was to develop a triage algorithm for improved prognostication and later use in an interventional trial. METHODS: We used data from the multi-national, prospective, observational TRIAGE trial including consecutive medical ED patients from Switzerland, France and the United States. We investigated triage effects when adding ProADM at two established cut-offs to a five-level ED triage score with respect to adverse clinical outcome. RESULTS: Mortality in the 6586 ED patients showed a step-wise, 25-fold increase from 0.6% to 4.5% and 15.4%, respectively, at the two ProADM cut-offs ( 0.75-1.5nmol/L, 0.0001). Risk stratification by combining ProADM within cut-off groups and the triage score resulted in the identification of 1662 patients (25.2% of the population) at a very low risk of mortality (0.3%, n = 5) and 425 patients (6.5% of the population) at very high risk of mortality (19.3%, n = 82). Risk estimation by using ProADM and the triage score from a logistic regression model allowed for a more accurate risk estimation in the whole population with a classification of 3255 patients (49.4% of the population) in the low risk group (0.3% mortality, n = 9) and 1673 (25.4% of the population) in the high-risk group (15.1% mortality, n = 252). CONCLUSIONS: Within this large international multicenter study, a combined triage score based on ProADM and established triage scores allowed a more accurate mortality risk discrimination. The TRIAGE-ProADM score improved identification of both patients at the highest risk of mortality who may benefit from early therapeutic interventions (rule in), and low risk patients where deferred treatment without negatively affecting outcome may be possible (rule out)