People with amyotrophic lateral sclerosis (pALS) require complex, multi-disciplinary care, resulting in extensive healthcare resource utilization (HCRU). To investigate the relationship between HCRU and ALS progression, the study objectives were (i) to characterize HCRU in pALS and (ii) to establish whether this varied according to disease stage, as defined using three different methodologies: neurologist-defined early/mid/late stage, the King's clinical staging system for ALS, and the Milan Torino Staging system for ALS (MiToS). Real-world data were drawn from the Adelphi ALS Disease-Specific Programme™, a point-in-time survey of neurologists in France, Germany, Italy, Spain, the UK, and the USA conducted July 2020-March 2021. The analysis included survey responses from 142 physicians with respect to 880 pALS. With advancing ALS stage, significant differences were observed in the number of healthcare professional consultations and X-rays per person (both p < 0.05 for all staging systems), and the proportion of pALS with emergency room admissions, intensive care unit admissions, and assisted ventilation (all p < 0.05 for all staging systems). Across stages, >55% of pALS received care from a general neurologist and a general/primary care practitioner. With increasing stage, there was a significant difference in the proportion receiving care from a physical therapist, pulmonologist/respiratory care practitioner, respiratory therapist, speech/language therapist, and palliative care team, and in the proportion receiving care only from professional caregivers (all p < 0.05 for all staging systems). This study confirmed the substantial HCRU required to support pALS through all stages of ALS and highlighted an increasing need for healthcare resources as the disease progresses.
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http://dx.doi.org/10.1016/j.jns.2023.120764 | DOI Listing |
BMC Med Educ
January 2025
Department of International Public Health, Emergency Obstetric and Quality of Care Unit, Liverpool School of Tropical Medicine, Pembrooke Place, L3, 5QA, Liverpool, UK.
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ORCHID Centre for Outcomes and Experience Research in Child Health, Illness and Disability Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
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Institute for Health Services Research and Clinical Epidemiology, Faculty of Medicine, Philipps-University Marburg, Marburg, Germany.
Background: The COVID-19 pandemic entailed a global health crisis, significantly affecting medical service delivery in Germany as well as elsewhere. While intensive care capacities were overloaded by COVID cases, not only elective cases but also non-COVID cases requiring urgent treatment unexpectedly decreased, potentially leading to a deterioration in health outcomes. However, these developments were only uncovered retrospectively.
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Centro de Salud Retiro, Hospital Universitario Gregorio Marañon, C/Lope de Rueda, 43, 28009, Madrid, Spain.
Background: Natural language processing (NLP) enables the extraction of information embedded within unstructured texts, such as clinical case reports and trial eligibility criteria. By identifying relevant medical concepts, NLP facilitates the generation of structured and actionable data, supporting complex tasks like cohort identification and the analysis of clinical records. To accomplish those tasks, we introduce a deep learning-based and lexicon-based named entity recognition (NER) tool for texts in Spanish.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
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Department of Rural Health, College of Health, Medicine and Wellbeing, University of Newcastle, Tamworth, NSW, Australia.
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