34 research outputs found
Consensus guidelines for the diagnosis and management of pyridoxine-dependent epilepsy due to α-aminoadipic semialdehyde dehydrogenase deficiency
Pyridoxine-dependent epilepsy (PDE-ALDH7A1) is an autosomal recessive condition due to a deficiency of α-aminoadipic semialdehyde dehydrogenase, which is a key enzyme in lysine oxidation. PDE-ALDH7A1 is a developmental and epileptic encephalopathy that was historically and empirically treated with pharmacologic doses of pyridoxine. Despite adequate seizure control, most patients with PDE-ALDH7A1 were reported to have developmental delay and intellectual disability. To improve outcome, a lysine-restricted diet and competitive inhibition of lysine transport through the use of pharmacologic doses of arginine have been recommended as an adjunct therapy. These lysine-reduction therapies have resulted in improved biochemical parameters and cognitive development in many but not all patients. The goal of these consensus guidelines is to re-evaluate and update the two previously published recommendations for diagnosis, treatment, and follow-up of patients with PDE-ALDH7A1. Members of the International PDE Consortium initiated evidence and consensus-based process to review previous recommendations, new research findings, and relevant clinical aspects of PDE-ALDH7A1. The guideline development group included pediatric neurologists, biochemical geneticists, clinical geneticists, laboratory scientists, and metabolic dieticians representing 29 institutions from 16 countries. Consensus guidelines for the diagnosis and management of patients with PDE-ALDH7A1 are provided. This article is protected by copyright. All rights reserved
Definition of strategies for the reduction of operational inefficiencies in a stroke unit
Stroke disease is the second common cause of death in the world and is then of particular concern to policy-makers. Additionally, it is a meaningful problem leaving a high number of people with severe disabilities, placing a heavy burden on society and incurring prolonged length of stay. In this respect, it is necessary to develop analytic models providing information on care system behavior in order to detect potential operational inefficiencies along the stroke patient journey and subsequently design improvement strategies. However, modeling stroke care is highly complex due to the multiple clinical outcomes and different pathways. Therefore, this paper presents an integrated approach between Discrete-event Simulation (DES) and Markov models so that integrated planning of healthcare services relating to stroke care and the evaluation of potential improvement scenarios can be facilitated, made more logically robust and easy to understand. First, a stroke care system from Colombia was characterized by identifying the exogenous and endogenous variables of the process. Afterward, an input analysis was conducted to define the probability distributions of the aforementioned variables. Then, both DES and Markov models were designed and validated to provide deeper analysis of the entire patient journey. Finally, the possible adoption of thrombolytic treatment on patients with stroke disease was assessed based on the proposed approaches within this paper. The results evidenced that the length of stay (LOS) decreased by 12,89% and the mortality ratio was diminished by 21,52%. Evaluation of treatment cost per patient is also carried out
Identification of a large intronic transposal insertion in SLC17A5 causing sialic acid storage disease
Growth and Development of Preterm/Very Low Birthweight Infants at 12 to 24 Months of Corrected Age: A Marker of Quality Survival
Knowledge base and mini-expert platform for the diagnosis of inborn errors of metabolism
Purpose: Recognizing individuals with inherited diseases can be difficult because signs and symptoms often overlap those of common medical conditions. Focusing on inborn errors of metabolism (IEMs), we present a method that brings the knowledge of highly specialized experts to professionals involved in early diagnoses. We introduce IEMbase, an online expert-curated IEM knowledge base combined with a prototype diagnosis support (mini-expert) system. Methods: Disease-characterizing profiles of specific biochemical markers and clinical symptoms were extracted from an expert-compiled IEM database. A mini-expert system algorithm was developed using cosine similarity and semantic similarity. The system was evaluated using 190 retrospective cases with established diagnoses, collected from 15 different metabolic centers. Results: IEMbase provides 530 well-defined IEM profiles and matches a user-provided phenotypic profile to a list of candidate diagnoses/genes. The mini-expert system matched 62% of the retrospective cases to the exact diagnosis and 86% of the cases to a correct diagnosis within the top five candidates. The use of biochemical features in IEM annotations resulted in 41% more exact phenotype matches than clinical features alone. Conclusion: IEMbase offers a central IEM knowledge repository for many genetic diagnostic centers and clinical communities seeking support in the diagnosis of IEM