Real-world experience with long-term albumin in patients with cirrhosis and ascites.

Background & Aims: Long-term albumin (LTA) is currently standard of care for patients with decompensated cirrhosis in many Italian hepatology centres. In this real-life study, we aimed to describe patient, logistical and treatment-related characteristics in daily clinical practice and to identify predictors of response.

Methods: We performed a multicentre, retrospective, observational study in patients with cirrhosis and ascites receiving LTA between 01/2016 and 02/2022 and followed until death, TIPS (transjugular intrahepatic portosystemic shunt) placement, transplantation or 02/2023.

Comparing machine learning and deep learning models to predict cognition progression in Parkinson's disease.

Cognitive decline in Parkinson's disease (PD) varies widely. While models to predict cognitive progression exist, comparing traditional probabilistic models to deep learning methods remains understudied. This study compares sequential modeling techniques to identify cognitive progression in individuals with and without PD.

Eleven Years of Change: Disease Progression in Biomarker-Defined Sporadic Parkinson's Disease.

Long-term longitudinal data on outcomes in sporadic Parkinson's Disease are limited, especially from cohorts with extensive biological characterization. Recent advances in biomarkers characterization of Parkinson's Disease necessitate an updated examination of long-term progression within contemporary cohorts like the Parkinson's Progression Markers Initiative, which enrolled individuals within 2 years of clinical diagnosis of Parkinson's Disease. Our study leverages the Neuronal Synuclein Disease framework, which defines the disease based on biomarker assessed presence of neuronal alpha-synuclein and dopamine deficit, rather than based on conventional clinical diagnostic criteria.

Predicting Cerebrospinal Fluid Alpha-Synuclein Seed Amplification Assay Status from Demographics and Clinical Data.

Objective: To develop and externally validate models to predict probabilities of alpha-synuclein (a-syn) positive or negative status in vivo in a mixture of people with and without Parkinson's disease (PD) using easily accessible clinical predictors.

Methods: Uni- and multi-variable logistic regression models were developed in a cohort of participants from the Parkinson Progression Marker Initiative (PPMI) study to predict cerebrospinal fluid (CSF) a-syn status as measured by seeding amplification assay (SAA). Models were externally validated in a cohort of participants from the Systemic Synuclein Sampling Study (S4) that had also measured CSF a-syn status using SAA.