Replacement therapy in pregnant women with von Willebrand disease during delivery: Factor levels and pharmacokinetics.

Limited data are available on VWF activity (VWF:Act) and factor VIII (FVIII:C) levels during delivery after VWF/FVIII concentrate administration in women with von Willebrand disease (VWD). We aimed to evaluate treatment with a specific VWF/FVIII concentrate on factor levels in women with VWD during delivery and the postpartum period. A retrospective single-center study was conducted between January 1, 2008, and August 1, 2022.

Absent or Hidden? Hyperactivity in Females With ADHD.

Objective: This study aimed to objectively assess signs of hyperactivity in adults suspected of having ADHD, addressing potential sex bias in diagnosis.

Methods: About 13,179 (49% female) adults with an average age of 33 years with ADHD and 1,910 (41% female) adults with an average age of 36 years without ADHD were included. Motor activity was measured using the Quantified Behavioral Test, analyzing "provoked," and "basal" activity.

A quantitative method for the analysis of total and unbound concentrations of amoxicillin, ampicillin, ceftazidime, ceftriaxone, ertapenem, fosfomycin and penicillin G in human plasma with liquid chromatography-tandem mass spectrometry assay.

Monitoring antibiotic plasma levels is critical in populations with altered pharmacokinetics, such as critically ill patients in neonatal or adult intensive care units. This study aimed to develop and validate a rapid, reproducible and sensitive liquid chromatography-tandem mass spectrometry assay (LC-MS/MS) for measuring total and unbound concentrations of amoxicillin, ampicillin, ceftazidime, ceftriaxone, ertapenem, fosfomycin and penicillin G in human plasma. The method required 20 and 250 μl sample volumes for measuring total and unbound concentrations, respectively.

Mixed effect estimation in deep compartment models: Variational methods outperform first-order approximations.

This work focusses on extending the deep compartment model (DCM) framework to the estimation of mixed-effects. By introducing random effects, model predictions can be personalized based on drug measurements, enabling the testing of different treatment schedules on an individual basis. The performance of classical first-order (FO and FOCE) and machine learning based variational inference (VI) algorithms were compared in a simulation study.