Early preschool wheeze trajectories are predominantly non-allergic with distinct biologic and microbiome traits.

Background: Disentangling preschool wheezing heterogeneity in terms of clinical traits, temporal patterns, and collective healthcare burden is critical for precise and effective interventions.

Objective: We aimed to collectively define contributions and distinct characteristics of respiratory phenotypes based on longitudinal wheeze and atopic sensitization patterns in the first 5 years of life.

Methods: Group-based trajectory analysis was performed in the CHILD Cohort study to identify distinct wheeze and allergic sensitization trajectories.

Determining the interplay of prenatal parental BMI in shaping child BMI trajectories: the CHILD Cohort Study.

Background: Obesity is a major public health concern affecting millions of people globally. Early identification of individuals susceptible to obesity is crucial for reducing the burden of obesity. Obesity is often defined based on body-mass-index (BMI), and tracking BMI trajectories from early childhood offers a valuable tool for risk stratification.

Identifying biomarker-driven subphenotypes of cardiogenic shock: analysis of prospective cohorts and randomized controlled trials.

Background: Cardiogenic shock (CS) is a heterogeneous clinical syndrome, making it challenging to predict patient trajectory and response to treatment. This study aims to identify biological/molecular CS subphenotypes, evaluate their association with outcome, and explore their impact on heterogeneity of treatment effect (ShockCO-OP, NCT06376318).

Methods: We used unsupervised clustering to integrate plasma biomarker data from two prospective cohorts of CS patients: CardShock (N = 205 [2010-2012, NCT01374867]) and the French and European Outcome reGistry in Intensive Care Units (FROG-ICU) (N = 228 [2011-2013, NCT01367093]) to determine the optimal number of classes.

Joint clustering multiple longitudinal features: A comparison of methods and software packages with practical guidance.

Clustering longitudinal features is a common goal in medical studies to identify distinct disease developmental trajectories. Compared to clustering a single longitudinal feature, integrating multiple longitudinal features allows additional information to be incorporated into the clustering process, which may reveal co-existing longitudinal patterns and generate deeper biological insight. Despite its increasing importance and popularity, there is limited practical guidance for implementing cluster analysis approaches for multiple longitudinal features and evaluating their comparative performance in medical datasets.

Identification of obstructive sleep apnea in children with obesity: A cluster analysis approach.

Background: Obstructive sleep apnea (OSA) is a heterogeneous disorder with a prevalence of 25%-60% in children with obesity. There is a lack of diagnostic tools to identify those at high risk for OSA.

Method: Children with obesity, aged 8-19 years old, were enrolled into an ongoing multicenter, prospective cohort study related to OSA.

Review of Randomized Controlled Trials Using e-Health Interventions for Patients With Eating Disorders.

Background: In a world of technological advancements, electronic devices and services seem to be a promising way to increase patients' engagement in treatment and to help manage their symptoms. Here, we identified and analyzed the current evidence of RCTs to evaluate the effectiveness and acceptability of e-health interventions in the eating disorder (ED) field.

Methods: We screened an initial cluster of 581 papers.