Cost-effectiveness in extracorporeal life support in critically ill adults in the Netherlands

Background: Extracorporeal life support (ECLS) is used to support the cardiorespiratory function in case of severe cardiac and/or respiratory failure in critically ill patients. According to the ELSO guidelines ECLS should be considered when estimated mortality risk approximates 80%. ECLS seems an efficient therapy in terms of survival benefit, but no undisputed evidence is delivered yet. The aim of the study is to assess the health-related quality of life after ECLS treatment and its cost effectiveness. Methods: We will perform a prospective observational cohort study. All adult patients who receive ECLS in the participating centers will be included. Exclusion criteria are patients in whom the ECLS is only used to bridge a procedure (like a high risk percutaneous coronary intervention or surgery) or the absence of informed consent. Data collection includes patient characteristics and data specific for ECLS treatment. Severity of illness and mortality risk is measured as precisely as possible using measurements for the appropriate age group and organ failure. For analyses on survival patients will act as their own control as we compare the actual survival with the estimated mortality on initiation of ECLS if conservative treatment would have been continued. Survivors are asked to complete validated questionnaires on health related quality of life (EQ5D-5 L) and on medical consumption and productivity losses (iMTA/iPCQ) at 6 and 12 months. Also the health related quality of life 1 month prior to ECLS initiation will be obtained by a questionnaire, if needed provided by relatives. With an estimated overall survival of 62% 210 patients need to be recruited to make a statement on cost effectiveness for all ECLS indications. Discussion: If our hypothesis that ECLS treatment is cost-effective is confirmed by this prospective study this could lead to an even broader use of ECLS treatment

Constraints on the Nucleon Strange Form Factors at Q^2 ~ 0.1 GeV^2

We report the most precise measurement to date of a parity-violating asymmetry in elastic electron-proton scattering. The measurement was carried out with a beam energy of 3.03 GeV and a scattering angle =6 degrees, with the result A_PV = -1.14 +/- 0.24 (stat) +/- 0.06 (syst) parts per million. From this we extract, at Q^2 = 0.099 GeV^2, the strange form factor combination G_E^s + 0.080 G_M^s = 0.030 +/- 0.025 (stat) +/- 0.006 (syst) +/- 0.012 (FF) where the first two errors are experimental and the last error is due to the uncertainty in the neutron electromagnetic form factor. This result significantly improves current knowledge of G_E^s and G_M^s at Q^2 ~0.1 GeV^2. A consistent picture emerges when several measurements at about the same Q^2 value are combined: G_E^s is consistent with zero while G_M^s prefers positive values though G_E^s=G_M^s=0 is compatible with the data at 95% C.L.Comment: minor wording changes for clarity, updated references, dropped one figure to improve focu

Clustering identifies endotypes of traumatic brain injury in an intensive care cohort: a CENTER-TBI study

Background While the Glasgow coma scale (GCS) is one of the strongest outcome predictors, the current classification of traumatic brain injury (TBI) as ‘mild’, ‘moderate’ or ‘severe’ based on this fails to capture enormous heterogeneity in pathophysiology and treatment response. We hypothesized that data-driven characterization of TBI could identify distinct endotypes and give mechanistic insights. Methods We developed an unsupervised statistical clustering model based on a mixture of probabilistic graphs for presentation (< 24 h) demographic, clinical, physiological, laboratory and imaging data to identify subgroups of TBI patients admitted to the intensive care unit in the CENTER-TBI dataset (N = 1,728). A cluster similarity index was used for robust determination of optimal cluster number. Mutual information was used to quantify feature importance and for cluster interpretation. Results Six stable endotypes were identified with distinct GCS and composite systemic metabolic stress profiles, distinguished by GCS, blood lactate, oxygen saturation, serum creatinine, glucose, base excess, pH, arterial partial pressure of carbon dioxide, and body temperature. Notably, a cluster with ‘moderate’ TBI (by traditional classification) and deranged metabolic profile, had a worse outcome than a cluster with ‘severe’ GCS and a normal metabolic profile. Addition of cluster labels significantly improved the prognostic precision of the IMPACT (International Mission for Prognosis and Analysis of Clinical trials in TBI) extended model, for prediction of both unfavourable outcome and mortality (both p < 0.001). Conclusions Six stable and clinically distinct TBI endotypes were identified by probabilistic unsupervised clustering. In addition to presenting neurology, a profile of biochemical derangement was found to be an important distinguishing feature that was both biologically plausible and associated with outcome. Our work motivates refining current TBI classifications with factors describing metabolic stress. Such data-driven clusters suggest TBI endotypes that merit investigation to identify bespoke treatment strategies to improve care

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees

Selaginella conduplicata

Pteridophyte