Prodromal Research Articles

Association between blood-based protein biomarkers and brain MRI in the Alzheimer's disease continuum: a systematic review.

Blood-based biomarkers (BBM) are becoming easily detectable tools to reveal pathological changes in Alzheimer's disease (AD). A comprehensive and up-to-date overview of the association between BBM and brain MRI parameters is not available. This systematic review aimed to summarize the literature on the associations between the main BBM and MRI markers across the clinical AD continuum. A systematic literature search was carried out on PubMed and Web of Science and a total of 33 articles were included. Hippocampal volume was positively correlated with Aβ42 and Aβ42/Aβ40 and negatively with Aβ40 plasma levels. P-tau181 and p-tau217 concentrations were negatively correlated with temporal grey matter volume and cortical thickness. NfL levels were negatively correlated with white matter microstructural integrity, whereas GFAP levels were positively correlated with myo-inositol values in the posterior cingulate cortex/precuneus. These findings highlight consistent associations between various BBM and brain MRI markers even in the pre-clinical and prodromal stages of AD. This suggests a possible advantage in combining multiple AD-related markers to improve accuracy of early diagnosis, prognosis, progression monitoring and treatment response.

Is there a prodrome to NMOSD? An investigation of neurologic symptoms preceding the first NMOSD attack

Background: It is unknown whether people with aquaporin-4 antibody positive (AQP4-IgG+) neuromyelitis optica spectrum disorder (NMOSD) experience a prodrome, although a few cases report AQP4 + serology up to 16 years before the first attack. Objectives: To evaluate whether individuals with AQP4-IgG + NMOSD have prodromal neurologic symptoms preceding the first attack. Methods: We reviewed medical records of participants meeting the 2015 diagnostic criteria for AQP4-IgG + NMOSD from four demyelinating disease centres in the Canadian NMOSD cohort study CANOPTICS. We searched for neurologic symptoms occurring at least 30 days before the first attack. Results: Of 116 participants with NMOSD, 17 (14.7%) had prodromal neurologic symptoms. The median age was 48 years (range 25–83) at first attack; 16 (94.1%) were female. Participants presented with numbness/tingling (n = 9), neuropathic pain (n = 5), visual disturbance (n = 4), tonic spasms (n = 2), Lhermitte sign (n = 2), severe headache (n = 2), incoordination (n = 2), weakness (n = 1), psychosis (n = 1) or seizure (n = 1). Of eight who underwent magnetic resonance imaging (MRI) brain, orbits and/or spinal cord, five had T2 lesions. Within 1.5–245 months (median 14) from the onset of prodromal neurologic symptoms, participants experienced their first NMOSD attack. Conclusions: One in seven people with NMOSD experienced neurologic symptoms before their first attack. Further investigation of a possible NMOSD prodrome is warranted.

The Multiple Sclerosis Prodrome in a Retrospective Pediatric Cohort

BackgroundEvidence suggests a prodromal phase in multiple sclerosis (MS), with increased health care use preceding the first demyelinating event (FDE). Although prior studies have explored this in adults, limited data exist for pediatric cases. We aimed to analyze health care utilization and prodromal symptoms in the two years before FDE in patients with pediatric-onset MS (POMS). MethodsFrom 122 patients at the Pediatric Multiple Sclerosis & Demyelinating Diseases Center at Washington University School of Medicine from 2011 to 2021, 37 POMS cases were identified. Of these, 21 with at least two years of records preceding FDE were included. Retrospective analysis covered symptoms and health care utilization in the two-year period before FDE, including ambulatory visits, hospital admissions, and office calls. ResultsPatients showed increased health care utilization in the year preceding FDE (period B; 96 interactions) compared with the prior year (period A; 77 interactions) and an increase in the percentage of neurology-related encounters (P < 0.001). There was an increase in all office calls from period A to period B (P = 0.01). Neurological complaints included headaches (28.6%), visual (19.0%), sensory (14.3%), and balance (14.3%) in the two years before FDE, and 28.6% of patients presented for psychiatric complaints. Common non-neurological complaints included infection, dermatologic, and musculoskeletal issues and injury. ConclusionsOur POMS cohort showed increased health care use before FDE, consistent with population-based data. This study emphasizes diverse symptoms in prodromal POMS, with headaches being the most common neurological symptom in the two-year period before FDE.

Enhancing early Parkinson’s disease detection through multimodal deep learning and explainable AI: insights from the PPMI database

Parkinson’s is the second most common neurodegenerative disease, affecting nearly 8.5M people and steadily increasing. In this research, Multimodal Deep Learning is investigated for the Prodromal stage detection of Parkinson's Disease (PD), combining different 3D architectures with the novel Excitation Network (EN) and supported by Explainable Artificial Intelligence (XAI) techniques. Utilizing data from the Parkinson’s Progression Markers Initiative, this study introduces a joint co-learning approach for multimodal fusion, enabling end-to-end training of deep neural networks and facilitating the learning of complementary information from both imaging and clinical modalities. DenseNet with EN outperformed other models, showing a substantial increase in accuracy when supplemented with clinical data. XAI methods, such as Integrated Gradients for ResNet and DenseNet, and Attention Heatmaps for Vision Transformer (ViT), revealed that DenseNet focused on brain regions believed to be critical to prodromal pathophysiology, including the right temporal and left pre-frontal areas. Similarly, ViT highlighted the lateral ventricles associated with cognitive decline, indicating their potential in the Prodromal stage. These findings underscore the potential of these regions as early-stage PD biomarkers and showcase the proposed framework's efficacy in predicting subtypes of PD and aiding in early diagnosis, paving the way for innovative diagnostic tools and precision medicine.

Use of virtual reality in bipolar disorder: a systematic review.

Virtual reality (VR) is a technology that allows to interact with recreated digital environments and situations with enhanced realism. VR has shown good acceptability and promise in different mental health conditions. No systematic review has evaluated the use of VR in Bipolar Disorder (BD). This PRISMA-compliant systematic review searched PubMed and Web of Science databases (PROSPERO: CRD42023467737) to identify studies conducted in individuals with BD in which VR was used. Results were systematically synthesized around four categories (cognitive and functional evaluation, clinical assessment, response to VR and safety/acceptability). Eleven studies were included (267 individuals, mean age = 36.6 years, 60.7% females). Six studies using VR to carry out a cognitive evaluation detected impairments in neuropsychological performance and delayed reaction times. VR was used to assess emotional regulation. No differences in well-being between VR-based and physical calm rooms were found. A VR-based stress management program reduced subjective stress, depression, and anxiety levels. VR-based cognitive remediation improved cognition, depressive symptoms, and emotional awareness. 48.7% of the individuals with BD considered VR-based cognitive remediation 'excellent', whereas 28.2% considered it 'great'. 87.2% of individuals did not report any side effects. 81.8% of studies received a global quality rating of moderate. Emerging data point towards a promising use of VR in BD as an acceptable assessment/intervention tool. However, multiple unstudied domains as comorbidity, relapse and prodromal symptoms should be investigated. Research on children and adolescents is also recommended. Further research and replication of findings are required to disentangle which VR-interventions for which populations and outcomes are effective.

Local Anesthetic Systemic Toxicity in Pregnancy: A Retrospective Cohort Analysis.

Introduction Local anesthetic systemic toxicity (LAST) is a rare complication of regional anesthesia. Pregnancy is a risk factor due to gestational physiologic changes. Labor and disorders of pregnancy can mask or delay symptoms of LAST, slowing appropriate intervention. This study examines LAST within a larger cohort and identifies features that help distinguish LAST in pregnant women from LAST in nonpregnant patients. Methods The TriNetX database was used to compare pregnant and nonpregnant patients with LAST from 2013 to 2023. Cohorts were matched on age, race, obesity status, diabetes, metabolic disorders, local anesthetic type, and cardiovascular, liver, kidney, and respiratory disease. Outcomes included prodromal symptoms of LAST and symptoms of cardiac and central nervous system excitation and depression. Results Matching occurred for 276 pregnant and 276 nonpregnant patients. Pregnant cohorts had a significantly higher risk of cardiac depression (risk ratio (RR)=1.96 (95% confidence interval (CI): 1.44-2.66), p<0.01) and significantly lower risk of cardiac excitation (RR=0.38 (95% CI: 0.22-0.63), p<0.01), prodromal symptoms (RR=0.17 (95% CI: 0.09-0.33), p<0.01), central nervous system excitation (RR=0.44 (95% CI: 0.21-0.90), p=0.02), and central nervous system depression (RR=0.24 (95% CI: 0.13-0.48), p<0.01) than nonpregnant cohorts. Conclusion Pregnant patients with LAST were more likely to exhibit cardiac depression and less likely to manifest prodromal symptoms, cardiac excitation, and central nervous system excitation and depression than nonpregnant patients. Physiological changes during pregnancy and prompt detection and treatment may explain these differences. These findings highlight the variable nature of LAST and how pregnancy may influence its clinical presentation.

Diagnostic Dilemma between Scrub Typhus Meningoencephalitis and Dengue Encephalopathy Resolved! - A Novel Prediction Score.

Scrub typhus and dengue, common etiologies of acute encephalitis syndrome, present with similar clinico-laboratory profiles but differ in management protocol. We aimed to devise a score differentiating between scrub typhus meningoencephalitis (STM) and dengue encephalopathy (DE). A prospective cohort of 204 children, (aged 6 months to 14 years) presenting with acute encephalitis syndrome in a public teaching hospital in northern India was subjected to standardized workup including serum IgM against Orientia tsutsugamushi and Dengue virus. Clinico-laboratory features were compared between STM and DE using univariate and multivariate analysis. Area under the receiver operating characteristic (ROC) curve (AUROC) for the score derived from independent predictors and its sensitivity, specificity, predictive values was calculated at cutoffs. STM and DE IgM ELISA were positive in 38 (18.6%) and 41 (20.1%) children, respectively. Longer duration of fever, prodromal stage, respiratory complaints and pneumonia were significantly frequent in STM; however, swelling, petechiae and myalgia were significantly prevalent in DE. STM had higher blood total leukocyte count (TLC), higher CSF protein and lower CSF sugar compared to DE. At admission, TLC >10,000/mm3, pneumonia, absence of myalgia and petechiae were independent predictors for differentiating STM from DE. AUROC of novel score (range: -5 to 5) was 0.879 (95% CI: 0.805-0.952). Score at cutoff ≥5 had 100% specificity and 100% PPV for differentiating STM from DE. Prediction score may benefit physicians to differentiate between these two infections and treat them accordingly.

A large language model-based clinical decision support system for syncope recognition in the emergency department: A framework for clinical workflow integration

Differentiation of syncope from transient loss of consciousness can be challenging in the emergency department (ED). Natural Language Processing (NLP) enables the analysis of free text in the electronic medical records (EMR).The present paper aimed to develop a large language models (LLM) for syncope recognition in the ED and proposed a framework for model integration within the clinical workflow.Two models, based on both the Italian and Multilingual Bidirectional Encoder Representations from Transformers (BERT) language model, were developed using consecutive EMRs. The “triage” model was only based on notes contained in the “triage” section of the EMR. The “anamnesis” model added data contained in the “medical history” section. Interpretation and calibration plots were generated.The Italian and Multi BERT models were developed and tested on both 15,098 and 15,222 EMRs, respectively. The triage model had an AUC of 0·95 for the Italian BERT and 0·94 for the Multi BERT. The anamnesis model had an AUC of 0·98 for the Italian BERT and 0·97 for Multi BERT. The LLM identified syncope when not explicitly mentioned in the EMR and also recognized common prodromal symptoms preceding syncope.Both models identified syncope patients in the ED with a high discriminative capability from nurses and doctors’ notes, thus potentially acting as a tool helping physicians to differentiate syncope from others transient loss of consciousness.

Association of severe hyposmia and frontal lobe dysfunction in patients with Parkinson's disease

Backgrounds and objectivesSevere hyposmia (SH) is a prodromal symptom of dementia associated with Parkinson's disease (PD) caused by Lewy bodies deposited in the limbic regions that connect the frontal and temporal lobes. We aimed to clarify the association between hyposmia and frontal lobe dysfunction (FLD) among patients with PD. MethodsPatients with PD and Hoehn & Yahr stage 1–3 at on-periods without apparent dementia were screened. FLD was defined as a score of ≤14 on the Frontal Assessment Battery (FAB). SH was defined as an average recognition threshold >4 in the T&T Olfactometer. For each subscore, a recognition score of ≥4 was defined as SH. We examined whether SH and its subscores were associated with FLD and evaluated which FAB subscore might be lower in PD patients with SH using Poisson regression analysis with a robust variance estimator. ResultsWe included 189 patients (median age, 68 years; 107 [57 %] male). FLD was observed in 53 (28 %) patients. Multivariable analysis showed that SH (PR 1.789, 95 % confidence intervals (CI) 1.115–2.872, p = 0.016) was associated with FLD. Regarding odor domains, only SH for fruity smells was associated with FLD (PR 1.970, 95 % CI 1.306–2.972, p = 0.001). Patients with SH had a higher subscore only for FAB-1 (similarity [conceptualization], p = 0.030), indicating linguistically mediated executive dysfunction. ConclusionIn patients with PD, SH is associated with FLD, especially with linguistically mediated executive dysfunction. Particularly, SH for fruity smells may be a sensitive indicator of FLD.

"I know when to stop": Sentinels and counter-strategies against drowsy driving in narcolepsy and idiopathic hypersomnia.

To collect prodromal symptoms experienced by participants with narcolepsy and idiopathic hypersomnia (considered "hypersomnolence experts") prior to drowsy driving and counter-strategies used to maintain alertness. Systematic, face-to-face interview (using a semi-structured questionnaire), including clinical measures, frequency of car accidents/near misses, and symptoms experienced before impending drowsy driving episodes and counter-strategies. Among 61 participants (32 with narcolepsy, 29 with idiopathic hypersomnia; 56 drivers), 61% of drivers had at least one lifetime accident/near miss. They had a higher sleepiness score (14 ± 4 vs. 11 ± 5, P<0.04) than those without an accident/near miss, but no other differences in demographics, driving experience, medical conditions, symptoms, sleep tests, and treatment. All but three participants experienced prodromal symptoms of drowsy driving, which included postural and motor changes (86.9%: axial hypotonia - e.g., eyelid droop, stereotyped movements), cognitive impairment (53.3%: automatic steering, difficulty concentrating/shifting, dissociation, mind wandering, dreaming), sensory (65%: paresthesia, pain, stiffness, heaviness, blunted perceptions such as a flat dashboard with loss of 3D, illusions and hallucinations), and autonomic symptoms (10%, altered heart/breath rate, penile erection). Counterstrategies included self-stimulation from external sources (pain, cold air, music, drinks, driving with bare feet), motor changes (upright posture, movements), and surprise (sudden braking). Drowsy driving symptoms can result from "local" NREM, entry in N1 sleep, and hybrid wake/REM sleep states. These rich qualitative insights from participants with narcolepsy and idiopathic hypersomnia, as well as sophisticated counter-strategies, can be gathered to reduce the crash risk in this population, but also in inexperienced healthy drivers.

Virtual Triage Early Detection of Inappropriate Care Seeking Intent Among Patients With Life-Threatening Cardiac Symptoms

Reports indicate that only 19% of patients with prodromal symptoms of sudden cardiac arrest seek the appropriate level of care acuity, which may be due partly to individuals being unable to distinguish which acute symptoms require urgent care. This study evaluated the degree to which patient-users of artificial intelligence-based virtual triage presenting with prodromal symptoms of a possibly life-threatening cardiac condition intended to seek the needed emergency care. A dataset of 746,282 virtual triage patient-users was examined to assess the characteristics of those reporting symptoms of potentially life-threatening cardiac conditions with no intention to seek emergency care. Of 3,968 patient-users over age 35 with severe cardiac symptoms, 89.4% did not plan to seek emergency care. A majority of patient-users did not appear to understand the level of care acuity to seek, or planned to engage self-care or to visit an outpatient physician, instead of seeking emergency care. These findings reinforce the need for much improved patient education among patients at risk for potentially life-threatening cardiac symptoms which require urgent medical care. Virtual triage (or symptom checkers) with care referral may have value in patient engagement and education to achieve this objective.

Machine Learning Predicts Phenoconversion from Polysomnography in Isolated REM Sleep Behavior Disorder.

Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of alpha-synucleinopathies. This study aimed at developing a fully-automated machine learning framework for the prediction of phenoconversion in patients with iRBD by using data recorded during polysomnography (PSG). A total of 66 patients with iRBD were included, of whom 18 converted to an overt alpha-synucleinopathy within 2.7 ± 1.0 years. For each patient, a baseline PSG was available. Sleep stages were scored automatically, and time and frequency domain features were derived from electromyography (EMG) and electroencephalography (EEG) signals in REM and non-REM sleep. Random survival forest was employed to predict the time to phenoconversion, using a four-fold cross-validation scheme and by testing several combinations of features. The best test performances were obtained when considering EEG features in REM sleep only (Harrel's C-index: 0.723 ± 0.113; Uno's C-index: 0.741 ± 0.11; integrated Brier score: 0.174 ± 0.06). Features describing EEG slowing had high importance for the machine learning model. This is the first study employing machine learning applied to PSG to predict phenoconversion in patients with iRBD. If confirmed in larger cohorts, these findings might contribute to improving the design of clinical trials for neuroprotective treatments.

Fighters and friends: female dominance hierarchy and male territoriality in a multicoloured poisonous frog

Fighters and friends: female dominance hierarchy and male territoriality in a multicoloured poisonous frog

Clinical characteristics of overlapping syndrome in patients with GFAP-IgG and MOG-IgG: a case series of 8 patients and literature review.

The overlapping syndrome of anti-GFAP and anti-MOG antibodies is extremely rare. This retrospective study reports 8 adult cases of the GFAP-MOG overlapping syndrome. We reviewed the clinical characteristics of 8 adult patients with the GFAP-MOG overlapping syndrome from Jan 2019 and Sep 2023 at the Third Affiliated Hospital, Sun Yat-sen University. Moreover, we searched the literature and included all case reports with this overlapping syndrome since 2018 on PubMed. The predominant clinical syndrome was meningoencephalomyelitis (5/8), followed by meningoencephalitis (2/8), and myelitis (1/8). Five patients had a flu-like prodromal symptom or diarrhea. No neoplasms were found in these patients. Regarding brain MRI, T2-weighted/fluid-attenuated inversion recovery hyperintensities were in 7 patients and leptomeningeal enhancement was in 4 patients. However, only one patient had periventricular radial linear enhancement. Besides, two patients had large space-occupying lesions. For spinal MRI, T2-hyperintensities were observed in 4 patients, in which 3 patients had longitudinally extensive lesions. All patients were treated with immunotherapy, the median follow-up period was 18months (range, 3-36months). Three patients presented relapses during the follow-up, but all cases recovered to mRS scores ≤ 2 at last follow-up. In addition, we also reviewed 14 cases (including 7 adults and 7 children) with this overlapping syndrome by literature review. Our findings provide data to understandthe clinical features and prognosis of the GFAP-MOG overlapping syndrome. Recognizing this overlapping syndrome will expand our knowledge, allowing for better management of these patients.

Modeling multiple-criterion diagnoses by heterogeneous-instance logistic regression.

Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD) that causes a significant burden in caregiving and medical costs. Clinically, the diagnosis of MCI is determined by the impairment statuses of five cognitive domains. If one of these cognitive domains is impaired, the patient is diagnosed with MCI, and if two out of the five domains are impaired, the patient is diagnosed with AD. In medical records, most of the time, the diagnosis of MCI/AD is given, but not the statuses of the five domains. We may treat the domain statuses as missing variables. This diagnostic procedure relates MCI/AD status modeling to multiple-instance learning, where each domain resembles an instance. However, traditional multiple-instance learning assumes common predictors among instances, but in our case, each domain is associated with different predictors. In this article, we generalized the multiple-instance logistic regression to accommodate the heterogeneity in predictors among different instances. The proposed model is dubbed heterogeneous-instance logistic regression and is estimated via the expectation-maximization algorithm because of the presence of the missing variables. We also derived two variants of the proposed model for the MCI and AD diagnoses. The proposed model is validated in terms of its estimation accuracy, latent status prediction, and robustness via extensive simulation studies. Finally, we analyzed the National Alzheimer's Coordinating Center-Uniform Data Set using the proposed model and demonstrated its potential.

Alterations in Gray Matter Structural Networks in Amnestic Mild Cognitive Impairment: A Source-Based Morphometry Study.

Amnestic mild cognitive impairment (aMCI), considered as the prodromal stage of Alzheimer's disease, is characterized by isolated memory impairment and cerebral gray matter volume (GMV) alterations. Previous structural MRI studies in aMCI have been mainly based on univariate statistics using voxel-based morphometry. We investigated structural network differences between aMCI patients and cognitively normal older adults by using source-based morphometry, a multivariate approach that considers the relationship between voxels of various parts of the brain. Ninety-one aMCI patients and 80 cognitively normal controls underwent structural MRI and neuropsychological assessment. Spatially independent components (ICs) that covaried between participants were estimated and a multivariate analysis of covariance was performed with ICs as dependent variables, diagnosis as independent variable, and age, sex, education level, and site as covariates. aMCI patients exhibited reduced GMV in the precentral, temporo-cerebellar, frontal, and temporal network, and increased GMV in the left superior parietal network compared to controls (pFWER < 0.05, Holm-Bonferroni correction). Moreover, we found that diagnosis, more specifically aMCI, moderated the positive relationship between occipital network and Mini-Mental State Examination scores (pFWER < 0.05, Holm-Bonferroni correction). Our results showed GMV alterations in temporo-fronto-parieto-cerebellar networks in aMCI, extending previous results obtained with univariate approaches.

Idiopathic Systemic Capillary Leak Syndrome: Report of a Pediatric Case.

The idiopathic systemic capillary leak syndrome is characterized by recurrent episodes of hypovolemia, with an unknown cause, presenting as a distributive and hypovolemic shock, due to fluid loss to the extravascular space. We describe a case of a previously healthy seven-year-old boy, who started with prodromal symptoms (abdominal pain, fatigue, nausea), followed by a fluid extravasation phase, with hemoconcentration, hypoproteinemia, and muscular edema in the abdominal wall and lower limbs, accompanied by pain - compartment syndrome. After a couple of days, spontaneous and fast recovery was noted, with clinical and analytic improvement. The inflammatory markers were always normal, and the blood cultures were negative. In this case, it is possible to distinguish the three idiopathic systemic capillary leak syndromes phases, as described in the literature. Although rare, this syndrome can be fatal, and the differential diagnosis with other causes of shock represents a challenge.

Update on Atypical Femoral Fractures.

➤ Atypical femoral fractures (AFFs) are stress fractures between the lesser trochanter and the metaphyseal flare that are most commonly related to prolonged (3 to 5 years) antiresorptive medication use.➤ An important finding is a visible transverse line in the lateral cortex, known as the "dreaded black line." Complete fractures are transverse and have minimal comminution.➤ Prodromal symptoms including hip, groin, thigh, and knee pain are present in more than one-half of cases and are usually misdiagnosed.➤ Nonoperative treatment for all patients with AFF includes withdrawal of bisphosphonates, assessment for secondary causes of osteoporosis, and optimization of vitamin D and calcium.➤ Incomplete fractures without a visible line can initially be treated nonoperatively with protected weight-bearing.➤ Intramedullary nailing is indicated for complete fractures and incomplete fractures with a visible fracture line. Delayed healing after fixation should be anticipated.➤ Treatment with parathyroid hormone (PTH) analogs (teriparatide and abaloparatide) after AFF prevents other fractures in high-risk patients, but the effect on healing of the fracture is unclear.

Sleep disturbance, suicidal ideation and psychosis-risk symptoms in individuals at clinical high risk for psychosis

Insomnia and suicidal ideation (SI) are common in schizophrenia, including in individuals at clinical high-risk for psychosis (CHR-P). Previous studies have found associations between sleep disturbance, SI, and psychopathology in schizophrenia. We explored these associations in a CHR-P cohort. We leveraged data from CHR-P individuals in the North American Prodrome Longitudinal Studies (NAPLS-3) (n = 688) cohort. We investigated relationships between sleep disturbance (Scale of Prodromal Symptoms [SOPS]; Calgary Depression Scale for Schizophrenia [CDSS], and the Pittsburgh Sleep Quality Index [PSQI]), suicidal ideation (CDSS), and psychosis-risk symptoms. The prevalence of terminal insomnia, sleep disturbance, and SI in NAPLS3 was 25 %, 69 %, and 29 %, respectively. After controlling for potential confounders, multiple indices of sleep disturbance (SOPS, PSQI: OR = 1.05–1.40) were significant indicators of concurrent SI. Terminal insomnia was not associated with conversion to psychosis. Multiple indices of sleep problems were associated with higher total and subscale psychosis-risk symptom scores (β = 0.09–0.39). Sleep problems are prevalent and associated with SI and more severe psychosis-risk symptoms in CHR-P individuals. These findings underscore the importance of designing longitudinal intervention studies to investigate whether the treatment of sleep disturbances may reduce suicidality and symptoms in this population.

The Relationship between Clinical and Psychophysical Assessments of Visual Perceptual Disturbances in Individuals at Clinical High Risk for Psychosis: A Preliminary Study.

This study investigated relations between a measure of early-stage visual function and self-reported visual anomalies in individuals at clinical high risk for psychosis (CHR-P). Eleven individuals at CHR identified via the Structured Interview for Psychosis-Risk Syndromes (SIPS) were recruited from a CHR-P research program in NYC. The sample was ~36% female, ranging from 16 to 33 years old (M = 23.90, SD = 6.14). Participants completed a contrast sensitivity task on an iPad with five spatial frequencies (0.41-13 cycles/degree) and completed the self-report Audio-Visual Abnormalities Questionnaire. Higher contrast sensitivity (better performance) to low spatial frequencies was associated with higher perceptual (r = 0.616, p = 0.044) and visual disturbances (r = 0.667, p = 0.025); lower contrast sensitivity to a middle spatial frequency was also associated with higher perceptual (r = -0.604, p = 0.049) and visual disturbances (r = -0.606, p = 0.048). This relation between the questionnaire and contrast sensitivity to low spatial frequency may be indicative of a reduction in lateral inhibition and "flooding" of environmental stimuli. The association with middle spatial frequencies, which play a critical role in face processing, may result in a range of perceptual abnormalities. These findings demonstrate that self-reported perceptual anomalies occur in these individuals and are linked to performance on a measure of early visual processing.