Prodromal Research Articles

Age-associated differences in FIRES: Characterizing prodromal presentation and long-term outcomes via the web-based NORSE/FIRES Family Registry.

Febrile infection-related epilepsy syndrome (FIRES) is a rare clinical presentation of refractory status epilepticus following a febrile infection. This study analyzes data from the NORSE/FIRES Family Registry, an international web-based registry available in six languages with data entered by patients, families, and clinicians to explore clinical presentations, survivorship, and long-term outcomes in adult and pediatric FIRES patients. We characterize and examine differences in demographics, prodromal symptoms, seizure frequency, anti-seizure medications (ASMs), quality of life, cognition, mood, and anxiety in adults vs pediatric populations with FIRES. Eighty-six participants were included in the study. Pediatric patients (n = 54) were predominantly male (77.8%) and experienced a significantly higher post-FIRES seizure burden than adult survivors (67.7% ≥12 seizures/month in pediatrics vs 11.8% in adults, p <.001). Adults (n = 32) were more likely to be female (59.4%) and have flu-like prodromal symptoms (90.6%). At ≥6 months post-FIRES, both groups exhibited high ASM use, with the majority (87.5%) taking three or more medications. Pediatric patients reported worse mood and anxiety outcomes compared to adults (p <.005). Self-reported quality of life and cognition were rated as moderate across in adults (5.2/10) and pediatric(4.7/10) patients, although pediatric patients indicated poorer cognition. Our findings highlight the challenges in managing post-FIRES outcomes across different age groups, particularly in pediatric patients who face a higher seizure burden and report worse cognitive outcomes.

Longitudinal FDG-PET Metabolic Change Along the Lewy Body Continuum

Although 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established cross-sectional biomarker of brain metabolism in dementia with Lewy bodies (DLB), the longitudinal change in FDG-PET has not been characterized. To investigate longitudinal FDG-PET in prodromal DLB and DLB, including a subsample with autopsy data, and report estimated sample sizes for a hypothetical clinical trial in DLB. Longitudinal case-control study with mean (SD) follow-up of 3.8 (2.3) years. Cases were recruited consecutively between 2007 and 2022 at a referral center and among the population. Patients with probable DLB or mild cognitive impairment with Lewy bodies (MCI-LB) were included. Individuals without cognitive impairment were included from a population-based cohort balanced on age and sex for comparison. All participants completed at least 1 follow-up assessment by design. Patients with MCI-LB and DLB. Rate of change in FDG-PET was assessed as standardized uptake value ratios (SUVr). Clinical progression was assessed with the Clinical Dementia Rating Sum of Boxes (CDR-SB) score. Thirty-five patients with probable DLB, 37 patients with MCI-LB, and 100 individuals without cognitive impairment were included. The mean (SD) age of the DLB and MCI-LB groups combined (n = 72) was 69.6 (8.2) years; 66 patients (92%) were men and 6 (8%) were women. At follow-up, 18 participants (49%) with MCI-LB had progressed to probable DLB. Patients with MCI-LB had a faster decline in FDG-SUVr, compared with that of participants without cognitive impairment, in the posterior cingulate, occipital, parietal, temporal, and lateral frontal cortices. The same regions showed greater metabolic decline in patients with DLB than in participants without cognitive impairment, with the addition of anterior-middle cingulate, insula, and medial frontal orbital cortices. Rates of change in FDG-PET in these brain regions were combined into a region of interest (ROI) labeled longitudinal FDG-PET LB meta-ROI. The rate of change in FDG-SUVr in the meta-ROI correlated with the rate of change in CDR-SB, and sample size estimates were reported for potential clinical trials in DLB. Findings were confirmed in the subsample with neuropathologic confirmation (n = 20). This study found that brain hypometabolism begins to evolve during the prodromal stages of DLB with changes paralleling symptomatic progression. These data may inform clinical practice and trials planning to use FDG-PET for biologic staging, monitoring disease progression, and potentially assessing treatment response.

Development and Validation of a Brief Age-Normed Screening Tool for Subthreshold Psychosis Symptoms in Youth.

Improvements in screening tools for early subthreshold psychosis symptoms are needed to facilitate early identification and intervention efforts, especially given the challenges of rapidly differentiating age-appropriate experiences from potential early signs of emerging psychosis. Tools can be lengthy and time-consuming, impacting their utility and accessibility across clinical settings, and age-normed data are limited. To address this gap, we sought to develop and validate a brief, empirically derived, age-normed, subthreshold psychosis screening tool, for public use. Computerized adaptive test simulation was used to derive a 5-item short form with age norm equivalencies from a 12-item PRIME-Screen-Revised (PRIME-12) administered to 7053 youth (Mage = 15.8, SD = 2.7; 54% female; 33% Black). Concurrent validity was assessed (n = 758) using contemporaneous administration of the PRIME-5 and the Structured Interview for Prodromal Syndromes. Comparability of criterion-related validity of the PRIME-5, PRIME-12, and Scale of Prodromal Symptoms (SOPS) was assessed by relating scores to psychosis-risk-relevant criteria. Finally, self-report versus assessor-administered PRIME total scores were compared (n = 131) to assess their concurrent validity. Correlations among PRIME-5, PRIME-12, and SOPS were comparable and moderate, supporting their convergent validity. The PRIME-5 also showed comparable criterion-related validity, demonstrating similar relationships with psychosis-risk indicators as the other tools. Self-reported and assessor-administered PRIME-5 were moderately correlated. Public availability of a brief, age-normed, and validated screening tool-which can be assessor or self-administered-will expedite and improve early identification of youth (age 11 and older) at risk for psychosis.

Plasma S100β is a predictor for pathology and cognitive decline in Alzheimer’s disease

BackgroundBlood–brain barrier dysfunction is one characteristic of Alzheimer’s disease (AD) and is recognized as both a cause and consequence of the pathological cascade leading to cognitive decline. The goal of this study was to assess markers for barrier dysfunction in postmortem tissue samples from research participants who were either cognitively normal individuals (CNI) or diagnosed with AD at the time of autopsy and determine to what extent these markers are associated with AD neuropathologic changes (ADNC) and cognitive impairment.MethodsWe used postmortem brain tissue and plasma samples from 19 participants: 9 CNI and 10 AD dementia patients who had come to autopsy from the University of Kentucky AD Research Center (UK-ADRC) community-based cohort; all cases with dementia had confirmed severe ADNC. Plasma samples were obtained within 2 years of autopsy. Aβ40, Aβ42, and tau levels in brain tissue samples were quantified by ELISA. Cortical brain sections were cleared using the X-CLARITY™ system and immunostained for neurovascular unit-related proteins. Brain slices were then imaged using confocal microscopy and analyzed for microvascular diameters and immunoreactivity coverage using Fiji/ImageJ. Isolated human brain microvessels were assayed for tight-junction protein expression using the JESS™ automated Western blot system. S100 calcium-binding protein B (S100β), matrix metalloproteinase (MMP)-2, MMP-9, and neuron-specific enolase (NSE) levels in plasma were quantified by ELISA. All outcomes were assessed for linear associations with global cognitive function (MMSE, CDR) and cerebral atrophy scores by Pearson, polyserial, or polychoric correlation, as appropriate, along with generalized linear modeling or generalized linear mixed-level modeling.ResultsAs expected, we detected elevated Aβ and tau pathology in brain tissue sections from AD patients compared to CNI. However, we found no differences in microvascular diameters in cleared AD and CNI brain tissue sections. We also observed no differences in claudin-5 protein levels in capillaries isolated from AD and CNI tissue samples. Plasma biomarker analysis showed that AD patients had 12.4-fold higher S100β plasma levels, twofold lower NSE plasma levels, 2.4-fold higher MMP-9 plasma levels, and 1.2-fold lower MMP-2 plasma levels than CNI. Data analysis revealed that elevated S100β plasma levels were predictive of AD pathology and cognitive impairment.ConclusionOur data suggest that among different markers relevant to barrier dysfunction, plasma S100β is the most promising diagnostic biomarker for ADNC. Further investigation is necessary to assess how plasma S100β levels relate to these changes and whether they may predict clinical outcomes, particularly in the prodromal and early stages of AD.

Case report: Reversible splenial lesion syndrome preceding the onset of multiple sclerosis

BackgroundThe reversible splenial lesion syndrome is frequently associated with systemic and central nervous system infections. Whether an infection associated with the occurrence of the reversible splenial lesion syndrome could play a role in the later development of multiple sclerosis is unknown.MethodsCase Report.ResultsA 27-year-old woman developed an infection-related reversible splenial lesion syndrome. Diagnostic findings did not establish a specific type of infection, but revealed evidence for a potential disposition towards autoimmunity. 32 months after the initial presentation, new clinical and radiological manifestations developed that led to a diagnosis of multiple sclerosis.ConclusionsIn susceptible individuals, infectious disease processes involving the central nervous system, such as described in this case, might be a factor in the pathogenesis of multiple sclerosis. More research on the prodromal stage of multiple sclerosis is needed to better understand the relationship between infections and autoimmunity.

Annual Research Review: Psychosis in children and adolescents: key updates from the past 2 decades on psychotic disorders, psychotic experiences, and psychosis risk

Psychosis in children and adolescents has been studied on a spectrum from (common) psychotic experiences to (rare) early‐onset schizophrenia spectrum disorders. This research review looks at the state‐of‐the‐art for research across the psychosis spectrum, from evidence on psychotic experiences in community and clinical samples of children and adolescents to findings from psychosis risk syndrome research, to evidence on early‐onset psychotic disorders. The review also looks at new opportunities to capture psychosis risk in childhood and adolescence, including opportunities for early intervention, identifies important unanswered questions, and points to future directions for prevention research.

Prodromal Parkinson's Disease: What We Know and What We do Not Know

Prodromal Parkinson's Disease (PD) represents a critical phase preceding the clinical onset of the disease, characterized by subtle and often non-motor symptoms that precede the classic motor manifestations. Understanding this prodromal phase is essential for early diagnosis, intervention, and potentially altering the disease course. This narrative review aims to elucidate the current knowledge on the prodromal phase of PD, highlighting known biomarkers, genetic predispositions, and environmental factors that contribute to early detection. Furthermore, it examines the limitations and gaps in our understanding, including the variability in prodromal symptoms, challenges in identifying definitive biomarkers, and the need for longitudinal studies. By synthesizing the existing literature, this review provides a comprehensive overview of what we know about prodromal PD and underscores the areas that require further research to enhance early diagnostic accuracy and develop preventative strategies.

Predicting Parkinson's Disease Using a Deep-Learning Algorithm to Analyze Prodromal Medical and Prescription Data.

Parkinson's disease (PD) is characterized by various prodromal symptoms, and these symptoms are mostly investigated retrospectively. While some symptoms such as rapid eye movement sleep behavior disorder are highly specific, others are common. This makes it challenging to predict those at risk of PD based solely on less-specific prodromal symptoms. The prediction accuracy when using only less-specific symptoms can be improved by analyzing the vast amount of information available using sophisticated deep-learning techniques. This study aimed to improve the performance of deep-learning-based screening in detecting prodromal PD using medical-claims data, including prescription information. We sampled 820 PD patients and 8,200 age- and sex-matched non-PD controls from Korean National Health Insurance cohort data. A deep-learning algorithm was developed using various combinations of diagnostic codes, medication codes, and prodromal periods. During the prodromal period from year -3 to year 0, predicting PD using only diagnostic codes yielded a high accuracy of 0.937. Adding medication codes for the same period did not increase the accuracy (0.931-0.935). For the earlier prodromal period (year -6 to year -3), the accuracy of PD prediction decreased to 0.890 when using only diagnostic codes. The inclusion of all medication-codes data increased that accuracy markedly to 0.922. A deep-learning algorithm using both prodromal diagnostic and medication codes was effective in screening PD. Developing a surveillance system with automatically collected medical-claims data for those at risk of developing PD could be cost-effective. This approach could streamline the process of developing disease-modifying drugs by focusing on the most-appropriate candidates for inclusion in accurate diagnostic tests.

Brain network analysis reveals hemispheric aberrant topology in patients with idiopathic REM sleep behavior disorder.

Idiopathic REM sleep behavior disorder (iRBD) is recognized as a prodromal stage of neuro-degenerative disease. While brain network analysis is a well-documented approach for characterizing disease-related dysfunctions, the specific patterns in iRBD, particularly those related to hemispheric aberrations remain largely unexplored. To address this gap, this study investigated the topological abnormalities of multi-band EEG networks in patients with iRBD. Specifically, eyes-open resting-state EEG signals were collected from 30 iRBD patients and 30 matched health control (HC) participants. Graph theoretical analysis was then employed to explore network properties at the whole-brain and the hemispheric level. At the whole-brain level, we found aberrant increased local and global efficiency along with a distinct pattern of increased frontal and decreased parietal nodal efficiency in alpha band of iRBD patients. At the hemispheric level, iRBD networks displayed more efficient topological properties in the left hemisphere. Additionally, significant hemispheric asymmetry was observed in alpha-band iRBD network compared to that of HC. In sum, these findings provide novel insights into the disrupted network reorganization in iRBD and suggest aberrant hemispheric asymmetry as a potential neural biomarker for early diagnosis and monitoring of the disease.

Genetic predisposition to high circulating levels of interleukin 6 and risk for Alzheimer's disease. Discovery and replication.

Aging is accompanied by immune dysregulation, which has been implicated in Alzheimer's disease (AD) pathogenesis. Individuals who are genetically predisposed to elevated levels of proinflammatory mediators might be at increased risk for AD. To investigate whether genetic propensity for higher circulating levels of interleukin 6 (IL-6) is associated with AD risk. We analyzed data from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD). Mean follow-up was 2.9 (SD, 0.8) years. Baseline assessment was from 11/2009 to 11/2016, and cognitive follow-up from 01/2013 to 07/2019. Associations of interest were also examined in the UK Biobank (UKB) for replication purposes (mean follow-up was 12.9 (SD, 2.4) years; baseline assessment was from 12/2006 to 10/2010). Population-based study. The HELIAD sample included 622 participants ≥65 years of age without baseline dementia or amnestic mild cognitive impairment (aMCI-the prodromal stage of AD). The UKB sample included 142,637 participants ≥60 years of age without prevalent dementia. Genetic predisposition to elevated circulating levels of IL-6 was estimated using a polygenic risk score (PRS), calculated based on the summary statistics of a current GWAS meta-analysis. AD and MCI diagnoses were based on standard clinical criteria [HELIAD], or hospital records and death registry data [UKB]. Associations with AD or aMCI incidence [HELIAD] and AD incidence [UKB] were examined with Cox regression models. In HELIAD, mean age was 73.4 (SD, 5.0) years; 363 (58%) women. An increase in IL-6 PRS by 1 standard deviation unit (SDU) was associated with up to a 43% increase in the risk for incident AD/aMCI (HRGWAS significance threshold of 0.01, 1.43 [95%CI, 1.14 - 1.80]). In UKBB, mean age was 64.2 (SD, 2.8) years; 73,707 (52%) women. A 1 SDU increase in IL-6 PRS was associated with up to an 8% increase in the risk for incident AD (HRGWAS significance threshold of 0.2, 1.08 [95%CI, 1.04 - 1.12]). Genetic predisposition to higher circulating levels of IL-6 was associated with an increased risk for AD, supporting the role of IL-6-related pathways in AD pathogenesis, and suggesting that genetic predisposition to proinflammatory states might trigger or accelerate AD-related neuropathology.

Association between choroidal microvasculature in the eye and Alzheimer's disease risk in cognitively healthy mid-life adults: A pilot study.

We explored associations between measurements of the ocular choroid microvasculature and Alzheimer's disease (AD) risk. We measured the choroidal vasculature appearing in optical coherence tomography (OCT) scans of 69 healthy, mid-life individuals in the PREVENT Dementia cohort. The cohort was prospectively split into low-, medium-, and high-risk groups based on the presence of known risk factors (apolipoprotein E [APOE] ε4 genotype and family history of dementia [FH]). We used ordinal logistic regression to test for cross-sectional associations between choroidal measurements and AD risk. Choroidal vasculature was progressively larger between ordinal risk groups, and significantly associated with risk group prediction. APOE ε4 carriers had thicker choroids and larger vascularity compared to non-carriers. Similar trends were observed for those with a FH. Our results suggest a potential link between the choroidal vasculature and AD risk. However, these exploratory findings should be replicated in a larger sample. Ocular choroidal microvasculature is of interest in relation to neurodegeneration due to its autonomic response to systemic, pathophysiological change.Choroidal changes in the prodromal stage of Alzheimer's disease (AD) are unexplored.The PREVENT Dementia cohort offers a unique, non-invasive study of the microvasculature in mid-life individuals at increased risk for developing AD.Significantly increased ocular choroidal vasculature was associated with increased risk (apolipoprotein E carrier and/or family history of dementia) for AD.These exploratory results suggest a potential association between the ocular choroidal vasculature and AD risk. However, findings should be replicated in a larger sample.

Mean mares? Habitat features influence female aggression in response to social instability in the feral horse (Equus caballus).

It is unclear how habitat features alter animal responses to social instability. Only by uncovering such interactions can we fully understand the evolutionary drivers and fitness consequences of sociality. We capitalize on a management-induced manipulation of social stability in an island population of free-ranging feral horses (Equus caballus), living across three distinct habitat types. We tested whether female group-changing behaviour (a reliable measure of social instability) affected (i) female-female aggression, (ii) rank within female dominance hierarchies, (iii) stability of female hierarchies (in the groups they joined and/or left), and (iv) how habitat characteristics shaped these responses. Female group-changing behaviour positively predicted aggression from other females, but only when habitat features such as visibility and freshwater distribution were considered. We found no strong association among female group-changing behaviour and the aggression initiated, female rank or the stability of female dominance hierarchies. Our work reveals that animal responses to social instability are nuanced and impacted by the surrounding habitat. A better understanding of these impacts can help elucidate evolutionary drivers of sociality and mitigate unintended effects of management practices.

Prediction of Phenoconversion into Alpha-Synucleinopathy in Patients with isolated REM Sleep Behavior Disorder Using Event-Related Potentials During Visuospatial Attention Tasks.

Isolated REM sleep behavior disorder (iRBD) is recognized as a prodromal stage of alpha-synucleinopathies. Predicting phenoconversion in iRBD patients remains a key challenge. We aimed to investigate whether event-related potentials (ERPs) recorded during visuospatial attention task can serve as predictors of phenoconversion in iRBD patients. We conducted a longitudinal study with 126 iRBD patients (aged 67.1 ± 6.4, 77 males) and 41 healthy controls (HCs; aged 66.1 ± 6.9, 29 males). Among the patients, those who further developed synucleinopathies during the follow-up period (average 6.3 years) were classified as converters (iRBD-CV), while the others as non-converters (iRBD-NC). Posner's visuospatial cueing task was performed at baseline. The N2 and P3 components were acquired for both the cue and target (valid and invalid) stimuli. Based on group comparisons, Kaplan-Meier survival analysis was performed. Twenty-nine patients converted to alpha-synucleinopathies (aged 69.4 ± 7.1, 14 males). iRBD patients exhibited overall reductions in N2 components for cue, valid, and invalid stimuli compared to HC (p = 0.012, 0.047, and 0.001, respectively). iRBD-CV patients displayed a significant increase in cue-elicited P3 (p < 0.001) and a decreasing trend in cue-elicited N2 (p = 0.079) compared to iRBD-NC. These ERP alterations were strongly associated with faster rate of phenoconversion (p < 0.001 for both components). Our findings suggest that altered cue-elicited ERPs could serve as early biomarkers for predicting phenoconversion in iRBD patients, likely reflecting attention-related neurodegeneration pathways. These biomarkers potentially enable the detection of preclinical phenotypes in alpha-synucleinopathies, facilitating timely intervention.

Computational modeling of selective attention differentiates subtypes of amnestic mild cognitive impairment

ABSTRACT Individuals with amnestic mild cognitive impairment (aMCI), a prodromal stage of Alzheimer’s disease and other dementias, show inhibition deficits in addition to episodic memory. How the latent processes of selective attention (i.e., from perception to motor response) contribute to these inhibition deficits remains unclear. Therefore, the present study examined contributions of selective attention to aMCI-related inhibition deficits using computational modeling of attentional dynamics. Two models of selective attention – the dual-stage two-phase model and the shrinking spotlight model – were fitted to individual participant data from a flanker task completed by 34 individuals with single-domain aMCI (sdaMCI, 66–86 years), 20 individuals with multiple-domain aMCI (mdaMCI, 68–88 years), and 52 healthy controls (64–88 years). Findings showed greater commission errors in the mdaMCI group compared to controls. Final-fitting model parameters indicated inhibitory and early perceptual deficits in mdaMCI , and impaired spatial allocation of attention in both MCI groups. Model parameters differentiated mdaMCI from sdaMCI and controls with moderate-to-high sensitivity and specificity. Impairments in perception and selective attention may contribute to inhibition deficits in both aMCI subtypes.

Machine Learning Recognizes Stages of Parkinson's Disease Using Magnetic Resonance Imaging.

Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), are debilitating conditions that affect millions worldwide, and the number of cases is expected to rise significantly in the coming years. Because early detection is crucial for effective intervention strategies, this study investigates whether the structural analysis of selected brain regions, including volumes and their spatial relationships obtained from regular T1-weighted MRI scans (N = 168, PPMI database), can model stages of PD using standard machine learning (ML) techniques. Thus, diverse ML models, including Logistic Regression, Random Forest, Support Vector Classifier, and Rough Sets, were trained and evaluated. Models used volumes, Euclidean, and Cosine distances of subcortical brain structures relative to the thalamus to differentiate among control (HC), prodromal (PR), and PD groups. Based on three separate experiments, the Logistic Regression approach was optimal, providing low feature complexity and strong predictive performance (accuracy: 85%, precision: 88%, recall: 85%) in PD-stage recognition. Using interpretable metrics, such as the volume- and centroid-based spatial distances, models achieved high diagnostic accuracy, presenting a promising framework for early-stage PD identification based on MRI scans.

Review: Efficacy of preventative interventions for children and adolescents at clinical high risk of psychosis - a systematic review and meta-analysis of intervention studies.

Despite evidence suggesting that age moderates the response to preventative treatment for those at clinical high risk of psychosis (CHR-P), no meta-analysis has assessed the effectiveness of preventative interventions for CHR-P children and adolescents. Our aim was to synthesise evidence assessing preventative interventions on a wide range of mental health outcomes for CHR-P children and adolescents. A systematic search was conducted on Ovid MEDLINE, Pubmed, APA PsycInfo and Web of Science until June 2024 (PROSPERO: CRD42023406696). Intervention studies that had a mean participant age of under 18 years old that reported on mental health outcomes for CHR-P participants were selected. A meta-analysis was conducted for independent studies reporting the effectiveness of interventions on different outcomes (transition to psychosis, attenuated positive, negative and total prodromal psychotic symptoms, depressive symptoms and global functioning) compared to control conditions of no intervention or placebo. Evidence from other studies was also reported narratively. Twenty-four studies and 1319 CHR-P children and adolescents were included. Compared to no intervention or placebo, preventative interventions were effective for positive symptoms (SMD = 0.379, p = .022, 95% CI 0.055, 0.703), negative symptoms (SMD = 0.583, p = .004, 95% CI 0.187, 0.980), total symptoms (SMD = 0.677, p = .002, 95% CI 0.249, 1.105) and functioning (SMD = 0.944, p = .038, 95% CI 0.052, 1.836) but not reducing transition to psychosis or depressive symptoms. There are disparities in the effectiveness of preventative interventions for different outcomes, with transition to psychosis not being the only relevant outcome. Differences in the efficacy of preventative interventions emerged between CHR-P children and adolescents versus adults.

Random survival forest model for early prediction of Alzheimer's disease conversion in early and late Mild cognitive impairment stages.

With a clinical trial failure rate of 99.6% for Alzheimer's Disease (AD), early diagnosis is critical. Machine learning (ML) models have shown promising results in early AD prediction, with survival ML models outperforming typical classifiers by providing probabilities of disease progression over time. This study utilized various ML survival models to predict the time-to-conversion to AD for early (eMCI) and late (lMCI) Mild Cognitive Impairment stages, considering their different progression rates. ADNI data, consisting of 291 eMCI and 546 lMCI cases, was preprocessed to handle missing values and data imbalance. The models used included Random Survival Forest (RSF), Extra Survival Trees (XST), Gradient Boosting (GB), Survival Tree (ST), Cox-net, and Cox Proportional Hazard (CoxPH). We evaluated cognitive, cerebrospinal fluid (CSF) biomarkers, and neuroimaging modalities, both individually and combined, to identify the most influential features. Our results indicate that RSF outperformed traditional CoxPH and other ML models. For eMCI, RSF trained on multimodal data achieved a C-Index of 0.90 and an IBS of 0.10. For lMCI, the C-Index was 0.82 and the IBS was 0.16. Cognitive tests showed a statistically significant improvement over other modalities, underscoring their reliability in early prediction. Furthermore, RSF-generated individual survival curves from baseline data facilitate clinical decision-making, aiding clinicians in developing personalized treatment plans and implementing preventive measures to slow or prevent AD progression in prodromal stages.

The Negative Symptom Inventory-Psychosis Risk (NSI-PR): Psychometric Validation of the Final 11-Item Version.

The lack of psychometrically validated assessment tools designed specifically to assess negative symptoms in individuals at clinical high risk (CHR) for psychosis represents a significant barrier to the early identification and prevention of psychosis. To address this need, the Negative Symptom Inventory-Psychosis Risk (NSI-PR) was developed based on the iterative, data-driven approach recommended by the National Institute of Mental Health consensus conference on negative symptoms. This manuscript reports the results of the second study phase that psychometrically validates the final 11-item version of the scale in data collected across 3 sites. A total of 222 participants (144 CHR and 78 clinical help-seeking controls) completed the NSI-PR, 1 week of ecological momentary assessment (EMA), and additional convergent and discriminant validity measures. Structural analyses replicated the previously reported strong fit for the 5-factor (anhedonia, avolition, asociality, alogia, and blunted affect) and hierarchical structures (2 super-ordinate dimensions and 5 lower-level domains). The 5 domains and 2 dimensions generally demonstrated good internal consistency, temporal stability, and interrater reliability. Convergent validity was demonstrated in relation to the 16-item beta version of the NSI-PR, Structured Interview for Psychosis-risk Syndromes negative subscale, Global Functioning Scale social and role, and EMA measures. Discriminant validity was supported by low correlations with positive, disorganized, and general psychiatric symptoms. Findings indicate the final 11-item version of the NSI-PR has sound psychometric properties. The scale, which is designed specifically for CHR individuals, is brief and appropriate for use in research and clinical contexts. Accompanying training materials have been developed to support its use in multisite trials.

Impact of Lewy bodies disease on visual skills and memory abilities: from prodromal stages to dementia

Dementia with Lewy bodies (DLB) and its prodromal presentation with mild cognitive impairment is characterized by prominent deficits in attention/executive domains and in visual processing abilities with relative sparing of memory. Neuropsychological research is continuously refining the tools to define more in detail the patterns of relatively preserved and impaired cognitive abilities that help differential diagnosis between DLB and Alzheimer disease (AD). This review summarizes the main studies exploring specific cognitive tasks investigating different visual processing abilities and verbal memory that better differentiate DLB from AD. The findings provide evidence that substantial impairments in visual-spatial and visual-constructional abilities and relatively better performance on memory tasks that depend on hippocampal function characterize the prodromal stage of DLB. The ability to detect early indicators of prodromal DLB through clinical and cognitive assessments is the first step to guide instrumental diagnostic work-ups and provide the opportunity for early intervention.

Consent work in intimacy coordination and adult content creation

ABSTRACT This article draws on the researcher’s training and experience as a certified intimacy coordinator to examine how labour from professional sex work to intimacy coordination necessitates nuanced approaches to consent. What I call consent work – practices of communication, negotiation, and boundary setting – supports bodily autonomy while guiding portrayals of intimacy and nudity in film, television, theatre, and erotic media. I begin by discussing intimacy coordinators’ communication and consent frameworks to create context for my ensuing investigation. Next, utilizing data from interviews with online sex workers, I explore their sophisticated personal and community-oriented harm reduction techniques that, without formal training, dovetail with those in the intimacy coordination industry. Continuing my qualitative analysis, I describe the ways in which my interlocutors’ use of knowledge from consensual BDSM reflects the breadth of practices that inform consent work while illuminating the links between kink and intimacy coordination. Finally, I unpack how consent models remain entangled within systems of inequality and exclusion while owing much to marginalized communities’ contributions to contemporary understandings of bodily autonomy. Overall, consent work and its capacious lineage contribute to the expanding literature on intimacy coordination and highlight the field’s under-researched intersections with adult content creation.