Probabilistic prediction of arrivals and hospitalizations in emergency departments in Île-de-France.

Background: Forecasts of future demand is foundational for effective resource allocation in emergency departments (EDs). As ED demand is inherently variable, it is important for forecasts to characterize the range of possible future demand. However, extant research focuses primarily on producing point forecasts using a wide variety of prediction algorithms.

Pilot deployment of a machine-learning enhanced prediction of need for hemorrhage resuscitation after trauma - the ShockMatrix pilot study.

Importance: Decision-making in trauma patients remains challenging and often results in deviation from guidelines. Machine-Learning (ML) enhanced decision-support could improve hemorrhage resuscitation.

Aim: To develop a ML enhanced decision support tool to predict Need for Hemorrhage Resuscitation (NHR) (part I) and test the collection of the predictor variables in real time in a smartphone app (part II).

To be or not to be, when synthetic data meet clinical pharmacology: A focused study on pharmacogenetics.

The use of synthetic data in pharmacology research has gained significant attention due to its potential to address privacy concerns and promote open science. In this study, we implemented and compared three synthetic data generation methods, CT-GAN, TVAE, and a simplified implementation of Avatar, for a previously published pharmacogenetic dataset of 253 patients with one measurement per patient (non-longitudinal). The aim of this study was to evaluate the performance of these methods in terms of data utility and privacy trade off.

Generalizing treatment effects with incomplete covariates: Identifying assumptions and multiple imputation algorithms.

We focus on the problem of generalizing a causal effect estimated on a randomized controlled trial (RCT) to a target population described by a set of covariates from observational data. Available methods such as inverse propensity sampling weighting are not designed to handle missing values, which are however common in both data sources. In addition to coupling the assumptions for causal effect identifiability and for the missing values mechanism and to defining appropriate estimation strategies, one difficulty is to consider the specific structure of the data with two sources and treatment and outcome only available in the RCT.

Association between in-ICU red blood cells transfusion and 1-year mortality in ICU survivors.

Background: Impact of in-ICU transfusion on long-term outcomes remains unknown. The purpose of this study was to assess in critical-care survivors the association between in-ICU red blood cells transfusion and 1-year mortality.

Methods: FROG-ICU, a multicenter European study enrolling all-comers critical care patients was analyzed (n = 1551).

Association of Early Norepinephrine Administration With 24-Hour Mortality Among Patients With Blunt Trauma and Hemorrhagic Shock.

Importance: Hemorrhagic shock is a common cause of preventable death after injury. Vasopressor administration for patients with blunt trauma and hemorrhagic shock is often discouraged.

Objective: To evaluate the association of early norepinephrine administration with 24-hour mortality among patients with blunt trauma and hemorrhagic shock.

Effect of fibrinogen concentrate administration on early mortality in traumatic hemorrhagic shock: A propensity score analysis.

Background: Fibrinogen concentrate is widely used in traumatic hemorrhagic shock despite weak evidence in the literature. The aim of the study was to evaluate the effect of fibrinogen concentrate administration within the first 6 hours on 24-hour all-cause mortality in traumatic hemorrhagic shock using a causal inference approach.

Methods: Observational study from a French multicenter prospective trauma registry was performed.

Regulatory T Cells in Melanoma Revisited by a Computational Clustering of FOXP3+ T Cell Subpopulations.

CD4(+) T cells that express the transcription factor FOXP3 (FOXP3(+) T cells) are commonly regarded as immunosuppressive regulatory T cells (Tregs). FOXP3(+) T cells are reported to be increased in tumor-bearing patients or animals and are considered to suppress antitumor immunity, but the evidence is often contradictory. In addition, accumulating evidence indicates that FOXP3 is induced by antigenic stimulation and that some non-Treg FOXP3(+) T cells, especially memory-phenotype FOXP3(low) cells, produce proinflammatory cytokines.

Measuring multivariate association and beyond.

Simple correlation coefficients between two variables have been generalized to measure association between two matrices in many ways. Coefficients such as the RV coefficient, the distance covariance (dCov) coefficient and kernel based coefficients are being used by different research communities. Scientists use these coefficients to test whether two random vectors are linked.