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Biomarkers are objectively measured characteristics of a biologic or pathogenic process, which can have a variety of applications, including diagnosing disease and measuring response to therapeutic interventions. Historically, the diagnosis of dementing neurodegenerative diseases has relied on clinical characterization of patients during life, using established clinical diagnostic criteria to assign the diagnosis that best matches the patient’s phenotype, and later performing postmortem brain autopsy to make a definitive diagnosis. Biomarkers have been developed to measure pathophysiological changes that are hallmarks of different neurodegenerative diseases. For example, in Alzheimer’s disease (AD), biomarkers can detect and measure the two pathological hallmarks, amyloid plaques and tau tangles, in living people, using PET, CSF, or plasma testing. Biomarkers have the potential to redefine the diagnosis of AD and neurodegenerative diseases as biological processes rather than as clinical entities. Biomarkers will transform our ability to evaluate and treat neurodegenerative diseases by improving diagnostic accuracy.
Cognitive assessment is used to detect, characterize, and monitor the degree of cognitive impairment in dementia and its earlier stages. Brief cognitive assessments are frequently used across diverse clinical settings and offer scalability as a frontline marker aimed at enhancing the clinical efficiency of diagnostic work-up. These tools have a potential to facilitate early detection and diagnosis of symptomatic cognitive impairment, which is a crucial first step to providing medical and supportive care that benefits people with cognitive impairment and their care partners and for identifying pre-surgical or hospitalized patients who may benefit from delirium prevention interventions. This chapter provides an overview of the most commonly used brief cognitive measures in clinical practice, recent developments and novel measures, and future directions for use of brief cognitive tools across clinical settings including primary, dementia specialist, preoperative, and inpatient care. Recommendations for cultural considerations and optimal implementation paradigms are also discussed.
Pierre Robin Sequence is characterised by a small lower jaw, tongue displacement and, often, a U-shaped cleft palate, leading to breathing and feeding problems. Orthodontic airway plates have been developed as a non-invasive treatment option. A systematic review was conducted to evaluate the outcomes of orthodontic airway plates in children with Pierre Robin Sequence.
Methods
Databases were searched for studies published up to December 2024, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.
Results
Ten clinical studies with a total of 598 patients were included, among which 483 had isolated Pierre Robin Sequence, and 115 had syndromic Pierre Robin Sequence. Orthodontic airway plates improved airway obstruction and helped avoid tracheostomy in most patients. A small proportion of syndromic cases still required surgery. Feeding outcomes improved, with fewer children needing tube feeding. Speech development was good, though hypernasality persisted in some.
Conclusion
Orthodontic airway plates are a minimally invasive yet effective way to manage airway complications in Pierre Robin Sequence patients.
Alzheimer’s disease typically manifests age 65 or older with a predominant memory dysfunction followed by a progressive impairment of other cognitive domains. Aging is the main risk factor for AD development. However, up to 10% of patients present an early onset (under 65), manifesting more frequently with atypical phenotypes. Amyloid plaques and neurofibrillary tangles due to tau deposition are the main hallmarks of the disease. Despite sharing the same neuropathological features, AD phenotypes present differential tau distribution patterns in cortical areas, being tau-pathology topographically related to the clinical syndrome. In addition to aging, several other factors may contribute to AD pathology and its clinical expression. AD is currently understood as a disease continuum starting with a preclinical phase, progressively leading to mild cognitive impairment and dementia. The development of biological and neuroimaging biomarkers detecting in vivo the defining features of AD has remarkably improved the accuracy and early diagnosis of AD in the last decades.
Spatial neglect is a heterogeneous post-stroke disorder with subtypes differing in reference frames, processing stages, and spatial domains. While egocentric peri-personal neglect recovery has been studied, recovery trajectories of allocentric peri-personal visuospatial and personal neglect remain unclear. This study investigated recovery time courses of egocentric and allocentric peri-personal visuospatial and personal neglect during the first 12 weeks post-stroke; whether initial severity predicts recovery and defines distinct patient clusters; and how subtypes interrelate over time.
Method:
Forty-one first-ever stroke patients were evaluated at weeks 3, 5, 8, and 12 post-stroke using the Broken Hearts Test, Line Bisection Test, Visuospatial Search Time Test, and Fluff Test. Recovery was analyzed using linear mixed models, clustering with Gaussian finite mixture models, and interrelationships using Spearman correlations.
Results:
Significant improvements occurred in egocentric and allocentric peri-personal visuospatial and personal neglect, primarily between weeks 3 and 5, followed by a plateau. The Line Bisection Test detected no changes. Higher initial severity predicted greater residual impairment. Cluster analysis identified near-normal, mild, and moderate-to-severe baseline subgroups with distinct recovery trajectories. Moderate-to-good correlations (ρ = 0.33 – 0.55) emerged between egocentric and allocentric neglect at week 3 and when timepoints were pooled.
Conclusion:
Neglect improved mainly between weeks 3 and 5 after which recovery plateaued, mirroring motor and language recovery and suggesting a shared time-limited window. Initial severity was a determinant of recovery, highlighting the value of early severity stratification to monitor and support recovery potential after stroke. As subtypes are distinctive, assessment should include multiple neglect tests.
This chapter focuses on the challenges and experiences of caregiving in dementia, emphasizing the importance of protecting caregiver health and well-being. It discusses effective communication strategies, provides a list of useful web-based educational resources for caregivers, and explores direct and indirect caregiver support interventions. The chapter highlights the need for better support and resources for caregivers, including access to respite care and palliative care services. It also provides strategies for healthcare providers to better engage and support caregivers. Overall, the chapter emphasizes the need to prioritize caregiver health and well-being in dementia care to improve outcomes for both caregivers and individuals with dementia.
Alzheimer’s disease (AD) is the most common type of dementia, accounting for approximately 60% of dementia cases (either alone or in combination); vascular dementia (VaD) accounts for another 10–20%. Most epidemiologic research on dementia has examined prevalence, incidence, and risk factors for either all-cause dementia or AD. This chapter discusses the epidemiology of all-cause dementia and AD, as well as advancement in VaD-related risk factors. Numerous prospective, observational studies have identified a variety of factors that may prevent or delay dementia onset. To better understand the epidemiology of dementia and the potential benefits of implementing interventions, future studies need to address the life course and long preclinical aspects of this disorder. More work is needed to understand the epidemiology and risk factors for non-AD or VaD dementias.
Evaluating pauses in natural speech is a promising strategy for improving reliability, validity, and efficiency in assessing cognitive functions in people with mild cognitive impairment (MCI) and Alzheimer’s dementia (AD).
Method:
We conducted a quantitative meta-analysis of studies employing automated pause analysis. We included measures of speaking rate for comparison.
Results:
We identified 13 studies evaluating pause measures and 8 studies of speaking rate in people with MCI (n’s = 276 & 109, respectively) and AD (n’s = 170 & 81, respectively) and healthy aged controls (n’s = 492 & 231, respectively). Studies evaluated speech across various tasks, including standard neuropsychological, reading, and free/conversational tasks. People with AD and MCI showed longer pauses than controls at approximately 1.20 and 0.62 standard deviations, respectively, though there was substantial heterogeneity across studies. A more modest effect, of 0.66 and 0.27 SDs, was observed between these groups in speech rate. The largest effects were observed for standardized memory tasks.
Conclusions:
Of the many ways that speech can be objectified, pauses appear particularly important for understanding cognition in AD. Pause analysis has the benefit of being face valid, interpretable in ratio format as a reaction time, tied to known socio-cognitive functions, and relatively easy to measure, compute, and interpret. Automation of speech analysis can greatly expand the assessment of AD and potentially improve early identification of one of the most devastating and costly diseases affecting humans.
This chapter discusses the neuropathology of dementia, focusing on the degenerative dementia syndromes commonly encountered by dementia specialists. It highlights the concept of selective vulnerability, where specific neuron types in specific brain regions decline and die, leading to progressive dysfunction. Alzheimer’s disease (AD) is the most prevalent cause of dementia, characterized by neurofibrillary pathology and the presence of neuritic plaques and neurofibrillary tangles. Dementia with Lewy Bodies (DLB), multiple system atrophy (MSA), and frontotemporal dementia (FTD) are also discussed, along with their respective clinical features and underlying pathology. The chapter emphasizes the complexity of neurodegenerative diseases and the need for more integrative models to understand their pathogenesis and develop effective therapies.
The population of people over the age of 80 is increasing in nearly all regions of the world. Age is tightly linked to the prevalence of dementia and is also linked to the frequency of protein deposition that does not meet neuropathological criteria for dementias, sometimes of unclear recognized importance. Among those over the age of 80, Alzhiemer’s disease remains the most common neuropathology with or without cerebrovascular disease or other co-pathology. Comorbid pathology is increasingly common in older age. The frequency of pure vascular dementia diminishes with age. The tight neuropathological to clinical correlates of dementia seen in younger populations are not as strong in the oldest-old where individuals without dementia oftern demonstrate substantial disease-specific neuropathology and those with dementia sometimes don’t evidence expected neuropathology. In addition to covering these concepts, new entities including Aging-related Tau Astrogliopathy (ARTAG), Limbic Predominant Age-related TDP-43 Proteinopathy (LATE) and Primary Age-related Tauopathy (PART) are briefly discussed.
This chapter discusses the diagnostic evaluation, physical examination, initial diagnostic formulation, investigations, and management of individuals with cognitive and/or behavioral changes. It emphasizes the importance of obtaining a comprehensive history from the patient and an informant, as well as conducting a thorough physical examination. The chapter also provides sample questions for assessing different cognitive domains and lists clues that suggest a non-Alzheimer’s disease etiology of cognitive/behavioral changes. It suggests various diagnostic studies and consultations that may be necessary for each patient. The document highlights the principles of management, including treating reversible causes, minimizing psychoactive medications, promoting regular sleep and exercise, and providing caregiver support. It also discusses the availability of pharmacologic therapies and the importance of providing information and support to families facing dementia-related issues.
Machine learning (ML) models show promise in predicting post-traumatic stress disorder (PTSD) treatment outcomes, but it is unknown how their predictions compare to those of clinicians. This study directly compared the accuracy of clinicians’ predictions of patient treatment outcomes with those of three ML models.
Methods
Twenty clinicians providing cognitive processing therapy repeatedly predicted outcomes for 194 veterans. We compared their accuracy against three ML models on two key endpoints: clinically meaningful symptom reduction (≥10-point PCL-5 decrease) and posttreatment severity (final PCL-5 < 33). Clinician predictions were compared against a recurrent neural network, a mixed-effects random forest, and a generalized linear mixed-effects model. We analyzed prediction accuracy and the association between clinician confidence and accuracy using logistic mixed-effects models.
Results
ML models were significantly more accurate than clinicians at predicting whether a patient’s posttreatment PCL-5 score would be below 33 (p < .001). However, no significant difference in accuracy was found for predicting a ≥10-point symptom reduction (p = .734). Clinician confidence increased throughout treatment and was significantly associated with greater prediction accuracy for both outcomes (ORs = 1.06, ps < .001).
Conclusions
ML models can outperform clinicians in predicting posttreatment symptom severity, particularly early in treatment, suggesting they could be a useful tool for identifying patients at risk for suboptimal outcomes. However, ML models were not superior in predicting symptom reduction, where clinicians also performed at a high level. Findings support the selective use of ML to enhance, rather than replace, clinical judgment in PTSD treatment.
Congenital junctional ectopic tachycardia is a rare arrhythmia that poses significant management challenges. This report presents a case of neonatal-onset congenital junctional ectopic tachycardia treated with cedilanid, amiodarone, and propafenone but persisted in episodes. Sinus rhythm was restored following the initiation of ivabradine therapy. The review of the literature indicates that ivabradine demonstrates efficacy in the treatment of paediatric junctional ectopic tachycardia, particularly in refractory cases, without significant side effects. These findings suggest that ivabradine has broad applications in the treatment of refractory arrhythmias.
This population-based cross-sectional study investigated the complex interplay of factors influencing high ultra-processed food (UPF) consumption among Brazilian adolescents using a hierarchical socio-ecological model. Data from 100 028 adolescents (13–17 years) enrolled in public and private schools nationwide were collected via self-administered questionnaires from the 2019 National School Health Survey. High UPF consumption was defined as ≥ 7 subgroups consumed on the previous day based on the NOVA classification. Poisson regression adjusted for complex sampling and hierarchical structure identified prevalence ratios (PR) for associated factors. High UPF consumption was significantly associated with younger age (PR = 1·22; 95 % CI 1·11, 1·34), regular breakfast consumption (PR = 1·32; 95 % CI 1·23, 1·42), regular screen time during meals (PR = 1·36; 95 % CI 1·27, 1·45), frequent UPF purchases at and around school (PR for canteen: 1·57; 95 % CI 1·43, 1·72; street vendors: 1·71; 95 % CI 1·55, 1·89), higher maternal education (PR 1·23, 95 % CI 1·12, 1·36) and lower parental supervision (PR 1·34, 95 % CI 1·11, 1·62). Living in the South (PR 1·50, 95 % CI 1·34, 1·69), Southeast (PR 1·30, 95 % CI 1·17, 1·44) and Midwest regions (PR 1·21, 95 % CI 1·09, 1·34) also correlated with higher consumption. Conversely, high body satisfaction and attending private school showed an inverse association. These findings underscore the intricate, multilevel influences on UPF consumption among Brazilian adolescents. Integrated interventions, spanning schools, family environments and public policies are crucial for promoting healthier eating habits and preventing obesity in this vulnerable population.
Loss of signals from substantia nigra (SN) and locus coeruleus (LC) on neuromelanin (NM)-sensitive sequences of MRI is reported as a potential biomarker in patients with Parkinson’s disease (PD) and related diseases. This scoping review aims to consolidate current knowledge on MRI techniques to visualize and quantify these signals and their clinical applications in PD. Publicly available databases were searched for original studies using MRI to quantify NM in PD and other related disorders. Different studies were compared based on MRI sequence, quantification techniques and correlations with clinical scores. Furthermore, studies on genetic forms of PD and prodromal PD were also evaluated and compared. The most common MRI sequences used were T1-weighted sequences and gradient echo sequences. Different studies used different quantitative measures such as signal-to-noise ratio, contrast-to-noise ratio and contrast ratio. Morphometric evaluations such as volume and area of the SN and LC signals were also used. Most studies showed evidence of significant difference in the signals in different stages of PD compared to controls both at the SN and LC. There were significant correlations between the SN and LC signals and clinical scores. Hence, quantification of these signals may be reliable in diagnosis and disease monitoring in PD. The relative ease of signal quantification and widespread availability of MRI may make it a quantitative surrogate biomarker.