608 research outputs found

    Sensory impairments and cognitive disorders in older age

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    Age-related and neuropathological changes in the olfactory, visual, auditory, and motor systems suggesting that sensory and motor changes may precede the cognitive symptoms of Alzheimer’s disease (AD) by several years and may signify increase the risk of developing AD. In particular, peripheral age-related hearing impairment and social isolation have been identified as potentially modifiable dementia risk factors. The impact of age-related hearing and vision impairments on cognition appeared to be especially important among the oldest old suggesting a strong link of these connections with frailty, a critical intermediate status of the aging process at higher risk for negative health-related outcomes. The link among age-related hearing and vision impairments and cognition suggested the potential for correcting hearing and vision losses so that older subjects can function better cognitively with improved social involvement, quality of life, and lifetime cognitive health

    Blockchain-Based Innovations for Population-Based Registries for Rare Neurodegenerative Diseases

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    Rare diseases are difficult if not impossible to study outside of population-based registries. Particularly in the context of rare neurodegenerative diseases characterized by case heterogeneity, difficult differential diagnosis by specialists, and small numbers of patients, registries make otherwise unfeasible incidence studies cost-effective and manageable. Building up and maintaining such registries is challenging and requires strong, active, and collaborative networks. Centralization around a leading institution provides structure and consistency, but this single-site storage leads to inefficiency and bottlenecks and is prone to failures, attacks, and manipulation. Furthermore, a substantial amount of trust is required between parties sharing data in a traditional registry. Patients are increasingly reluctant to share data in light of regular news reports about healthcare data breaches. Underfunded rare disease specialized centers are also hesitant to exchange with the leading institution out of fear that the low numbers of patients may seek treatment elsewhere. A lack of electronic health records and information system interoperability in certain settings leads to information silos and only further exacerbate the other issues. Blockchain technology may provide unique, innovative solutions to many of these challenges. Specifically, through digital trust and the use of an immutable distributed ledger, automated data transaction processing, guaranteed integrity, and enhanced security, blockchain technology seems to be perfectly suitable to optimize current population-based rare neurodegenerative disease registry construction and maintenance

    Explainable machine learning radiomics model for Primary Progressive Aphasia classification

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    IntroductionPrimary Progressive Aphasia (PPA) is a neurodegenerative disease characterized by linguistic impairment. The two main clinical subtypes are semantic (svPPA) and non-fluent/agrammatic (nfvPPA) variants. Diagnosing and classifying PPA patients represents a complex challenge that requires the integration of multimodal information, including clinical, biological, and radiological features. Structural neuroimaging can play a crucial role in aiding the differential diagnosis of PPA and constructing diagnostic support systems.MethodsIn this study, we conducted a white matter texture analysis on T1-weighted images, including 56 patients with PPA (31 svPPA and 25 nfvPPA), and 53 age- and sex-matched controls. We trained a tree-based algorithm over combined clinical/radiomics measures and used Shapley Additive Explanations (SHAP) model to extract the greater impactful measures in distinguishing svPPA and nfvPPA patients from controls and each other.ResultsRadiomics-integrated classification models demonstrated an accuracy of 95% in distinguishing svPPA patients from controls and of 93.7% in distinguishing svPPA from nfvPPA. An accuracy of 93.7% was observed in differentiating nfvPPA patients from controls. Moreover, Shapley values showed the strong involvement of the white matter near left entorhinal cortex in patients classification models.DiscussionOur study provides new evidence for the usefulness of radiomics features in classifying patients with svPPA and nfvPPA, demonstrating the effectiveness of an explainable machine learning approach in extracting the most impactful features for assessing PPA

    LATE LIFE DEPRESSION AND LATE ONSET DEPRESSION: ARE THE SAME CLINICAL AND PATHOPSYSIOLOGICAL PICTURE?

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    Phenomenological differences between older patients with late- and early-onset depression may reflect differences in aetiology and neuropathological processes involved in these two types of depression. Early- onset depression has been mainly correlated to a family history of depression while late-onset depression has been principally correlated to vascular dysfunction. The same cortical and sub-cortical areas are involved in both types of depression. However, lesions in these brain areas and cognitive impairment are most pronounced in late-onset depression. Based on these observations we propose a common neuroanatomical substrate but different pathophysiological processes implicated in these two types of depression

    Blockchain-Based Innovations for Population-Based Registries for Rare Neurodegenerative Diseases

    Get PDF
    Rare diseases are difficult if not impossible to study outside of population-based registries. Particularly in the context of rare neurodegenerative diseases characterized by case heterogeneity, difficult differential diagnosis by specialists, and small numbers of patients, registries make otherwise unfeasible incidence studies cost-effective and manageable. Building up and maintaining such registries is challenging and requires strong, active, and collaborative networks. Centralization around a leading institution provides structure and consistency, but this single-site storage leads to inefficiency and bottlenecks and is prone to failures, attacks, and manipulation. Furthermore, a substantial amount of trust is required between parties sharing data in a traditional registry. Patients are increasingly reluctant to share data in light of regular news reports about healthcare data breaches. Underfunded rare disease specialized centers are also hesitant to exchange with the leading institution out of fear that the low numbers of patients may seek treatment elsewhere. A lack of electronic health records and information system interoperability in certain settings leads to information silos and only further exacerbate the other issues. Blockchain technology may provide unique, innovative solutions to many of these challenges. Specifically, through digital trust and the use of an immutable distributed ledger, automated data transaction processing, guaranteed integrity, and enhanced security, blockchain technology seems to be perfectly suitable to optimize current population-based rare neurodegenerative disease registry construction and maintenance

    Hospitalizations due to respiratory failure in patients with Amyotrophic Lateral Sclerosis and their impact on survival: A population-based cohort study

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    Background: Respiratory failure, infections and aspiration pneumonia, are the main causes of morbidity and mortality in Amyotrophic Lateral Sclerosis (ALS). In a population-based cohort, we assessed (a) hospital utilization and (b) impact of hospitalization for respiratory failure on survival. Methods: All patients with incident ALS in Friuli Venezia Giulia region, Italy, from 2002 to 2009, were identified through multiple sources. Diagnosis was validated through clinical documentation review. For each patient, we extracted the records of all hospitalizations after ALS diagnosis from the regional hospitalization database. Cox proportional hazards model survival Hazard Ratio (HR), with 95 % Confidence Interval (95 % CI), was calculated. Results: Out of 262 patients, 98.1 % had at least 1 and 58.0 % 653 hospitalizations. Emergency admissions occurred in 77.5 % of patients and a diagnosis of respiratory failure in 55.0 %. Patients underwent a total of 885 hospitalizations. The leading diagnosis was respiratory failure (31.6 % of hospitalizations). This diagnosis occurred most frequently in emergency (45.6 %) than in elective admissions (26.4 %). The second leading diagnosis was pneumonia (14.2 %), 24.9 and 6.3 % respectively. The leading procedure was mechanical ventilation (18.4 %), performed in 29.9 % of emergency and in 12.4 % of elective admissions. After adjustment for site of onset, age and diagnostic delay, a first hospitalization for respiratory failure had a strong adverse effect on survival (HR 4.00; 95 % CI 3.00; 5.34). Conclusions: Respiratory failure, pneumonia and aspiration pneumonia were major determinants of hospitalizations and emergency admissions and often dealt with in emergency admissions. A first hospitalization for respiratory failure had a strong adverse effect on survival. Strategies to improve home management of respiratory conditions in patients with ALS and to optimize hospital care utilization are neede

    Status Epilepticus Severity Score (STESS): A tool to orient early treatment strategy

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    Background : Status epilepticus (SE) treatment ranges from small benzodiazepine doses to coma induction. For some SE subgroups, it is unclear how the risk of an aggressive therapeutic approach balances with outcome improvement. We recently developed a prognostic score (Status Epilepticus Severity Score, STESS), relying on four outcome predictors (age, history of seizures, seizure type and extent of consciousness impairment), determined before treatment institution. Our aim was to assess whether the score might have a role in the treatment strategy choice. Methods : This cohort study involved adult patients in three centers. For each patient, the STESS was calculated before primary outcome assessment: survival vs. death at discharge. Its ability to predict survival was estimated through the negative predictive value for mortality (NPV). Stratified odds ratios (OR) for mortality were calculated considering coma induction as exposure; strata were defined by the STESS level. Results : In the observed 154 patients, the STESS had an excellent negative predictive value (0.97). A favorable STESS was highly related to survival (P < 0.001), and to return to baseline clinical condition in survivors (P < 0.001). The combined Mantel-Haenszel OR for mortality in patients stratified after coma induction and their STESS was 1.5 (95 % CI: 0.59-3.83). Conclusion : The STESS reliably identifies SE patients who will survive. Early aggressive treatment could not be routinely warranted in patients with a favorable STESS, who will almost certainly survive their SE episode. A randomized trial using this score would be needed to confirm this hypothesi

    The Role of Age on Beta-Amyloid1–42 Plasma Levels in Healthy Subjects

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    Beta-amyloid (Ab) plaques have been observed in the brain of healthy elderlies with frequencies strongly influenced by age. The aim of the study is to evaluate the role of age and other biochemical and hematological parameters on Ab1–42 plasma levels in cognitively and neurologically normal individuals. Two-hundred and seventy-five normal subjects stratified by age groups (&lt;35 years, 35–65 years, and &gt;65 years) were included in the study. Ab1–42 plasma levels significantly correlated with age (rs = 0.27; p &lt; 0.0001) in the whole sample, inversely correlated with age in the first age group (rs = 0.25, p = 0.01), positively correlated in the second group (rs = 0.22, p = 0.03), while there was no significant correlation in the older group (rs = 0.02, p = 0.86). Both age (b- estimate = 0.08; p &lt; 0.001) and cholesterol (b-estimate = 0.03; p = 0.009) were significantly associated with Ab1–42 plasma level in multivariable analysis. However, only the association with age survived post hoc adjustment for multiple comparisons. The different effects of age on the Ab level across age groups should be explored in further studies to better understand the age-dependent variability. This could better define the value of plasma Ab as a biomarker of the Alzheimer neuropathology
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