Trends in the diagnostic delay and pathway for amyotrophic lateral sclerosis patients across different countries

BackgroundAmyotrophic lateral sclerosis (ALS) is a rapidly progressive neurodegenerative disease with a median survival of 2–5 years. An early diagnosis is essential for providing ALS patients the finest management possible. Studies from different countries report a similar median diagnostic delay of around 12 months, which is still far from desirable. We analyzed the diagnostic pathway in different countries in order to identify the major challenges.MethodsWe studied a cohort of 1,405 ALS patients from five different centers, in four different countries (Turkey, Germany, Poland, and Portugal), which collaborated in a common database. Demographic, disease and sociocultural factors were collected. Time from first symptom onset to first medical evaluation and to diagnosis, the specialist assessment and investigations requested were analyzed. Factors contributing to diagnostic delay were evaluated by multivariate linear regression.ResultsThe median diagnostic delay from first symptom onset was 11 months and was similar between centers. Major differences were seen in the time from symptom onset to first medical evaluation. An earlier first medical evaluation was associated with a longer time to diagnosis, highlighting that ALS diagnosis is not straightforward in the early stages of the disease. The odds for ALS diagnosis were superior when evaluated by a neurologist and increased over time. Electromyography was decisive in establishing the diagnosis.ConclusionsWe suggest that a specific diagnostic test for ALS—a specific biomarker—will be needed to achieve early diagnosis. Early referral to a neurologist and to electromyography is important for early ALS diagnosis

Congenital malformations in neonates: analysis of morbidity and associated factors

Objective: To evaluate the neonatal morbidity due to congenital malformations in the city of Petrolina-PE, from 2008 to 2013. Methods: A descriptive study with data from the Information System on Live Births (Sinasc). The analyzes were carried out through frequency distribution and measures of central tendency and dispersion. The associations were tested by the Pearson and Kruskal Wallis chi-square tests. Significance was set at 5% and 95% confidence. Results: 436 cases of congenital malformations were recorded in the study period, with 2011 being the highest occurrence year. The mothers of the newborns were young (25.2 years old), single, upper level of education and household. In general multiparous, with single gestation, vaginal delivery and performed up to six prenatal visits. The newborns were males, at 39 weeks or more of gestation and with normal weight (> = 2500g). The malformations of the musculoskeletal system were the most frequent followed by the genitourinary system. Congenital malformations were especially associated with neonatal characteristics such as gender and weight. In all causes the mean weight was greater than 2500g (p <0.05). The causes of malformation of greater occurrence in both sexes were osteomuscular (p <0.05). The aspects of the mother did not present significant differences in the present study (p> 0.05). Conclusion: The present study evidenced relevant aspects in the occurrence of morbidities due to congenital malformations, directing to a greater attention the occurrence of these diseases especially in relation to the newborn

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Updated evaluation of the safety, efficacy and tolerability of Tafamidis in the treatment of hereditary transthyretin amyloid polyneuropathy

© 2023 The Author(s). This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.Hereditary amyloid transthyretin (ATTRv) amyloidosis is a devastating hereditary multisystemic disease affecting predominantly the peripheral and autonomic nervous systems and the heart. ATTRv is caused by mutations in the transthyretin (TTR) gene, leading to extracellular deposition of amyloid fibrils in multiple organs including the peripheral nervous system. If untreated, it is associated with a fatal outcome 10-12 years after disease onset. Different treatments are available for patients with ATTRv polyneuropathy. Tafamidis 20 mg is approved in Europe since 2011 for early stages of ATTRv polyneuropathy (stage I - able to walk without support) and it is recommended as first-line therapy in these patients. Tafamidis is a TTR stabilizer that selectively binds to TTR and kinetically stabilizes both wild-type native TTR and mutant TTR. Consequently, it has the potential to prevent the amyloidogenic cascade initiated by TTR tetramer dissociation into its monomers and subsequent misfolding and aggregation. Tafamidis is an oral drug, taken once per day, with proved efficacy, safety and tolerability in ATTRv-PN patients as demonstrated in different clinical trials and open-label extension studies as well in clinical practice setting with around 10 years of experience. Tafamidis treatment started in the earliest stages of the disease is associated with better neurological outcomes. A multidisciplinary approach in referral centres is also fundamental for monitoring patients to assess individual response to treatment.info:eu-repo/semantics/publishedVersio

Early diagnostic tools in hereditary amyloidosis related to transthyretin hATTR V30M autonomic neuropathy

© 2019 Informa UK Limited, trading as Taylor & Francis GroupHereditary amyloidosis related to transthyretin (hATTR) is a fatal progressive, autosomal dominant disease caused by mutations in the TTR gene. The most common TTR mutation worldwide is the V30M with a neuropathic phenotype, originating early impairment of small fibres responsible for the autonomic and sensory abnormalities frequently found as the first manifestation of disease. Diagnostic tools to assess autonomic function are essential in the diagnosis of small fibre neuropathy (SFNP) in early stages of disease, allowing an early treatment management.info:eu-repo/semantics/publishedVersio

Hereditary sensory autonomic neuropathy type II: Report of two novel mutations in the FAM134B

International audienc

Combined central and peripheral demyelination after COVID-19 vaccination

© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany 2022.Combined central and peripheral demyelination (CCPD) is a rare neurological entity that afects both the central and peripheral nervous system with demyelinating lesions. The pattern of involvement of the central nervous system (CNS) includes frequent bilateral optical neuritis, involvement of grey matter and occasional longitudinally extensive transverse myelitis (LETM) in the absence of oligoclonal bands (OCB) or antibodies such as antiaquaporin-4 (AQP4) and anti-myelin oligodendrocyte glycoprotein (MOG). Peripheral nervous system (PNS) involvement occurs mainly as a chronic infammatory demyelinating polyneuropathy (CIDP)-like disease. Infections and vaccinations are known triggers. CCPD typically evolves aggressively with progressive cumulative neurological impairment despite immunosuppression.info:eu-repo/semantics/publishedVersio