BACKGROUND: Neurobehavioural comorbidities have a detrimental effect on the quality of life of people with epilepsy, yet tracking their impact is challenging as behaviour may vary with seizures and anti-seizure medication (ASM) side effects. Smartphones have the potential to monitor day-to-day neurobehavioural patterns objectively. We present the case of a man in his late twenties with drug-resistant focal epilepsy in whom we ascertained the effects of ASM withdrawal and a convulsive seizure on his touchscreen interactions.
METHODS: Using a dedicated app, we recorded over 185 days the timestamps of 718,357 interactions. We divided the various smartphone behaviours according to the next-interval dynamics of the interactions by using a joint interval distribution (JID). During two ASM load transitions, namely before versus during tapering and tapering versus restarting medication, we used cluster-based permutation tests to compare the JIDs. We also compared the JID of the seizure day to the average of the previous 3 days.
RESULTS: The cluster-based permutation tests revealed significant differences, with accelerated next-interval dynamics during tapering and a reversal upon medication restart. The day of the convulsion exhibited a marked slowing of next-interval dynamics compared to the preceding 3 days.
CONCLUSIONS: Our findings suggest that the temporal dynamics of smartphone touchscreen interactions may help monitor neurobehavioural comorbidities in neurological care.

In Japan, the diagnostic criteria for the higher brain dysfunction (HBD) emerged in 2005 in response to social needs for support for the patients and their families. The issue of cognitive dysfunction after brain trauma is not unique to Japan. The purpose of this study was to reveal the current status of family members of HBD patients from their perspective, focusing on the changes before and after the establishment of diagnostic criteria in Japan. We conducted a questionnaire survey for family members supporting the HBD patients. The questionnaire included the causative condition, explanation on HBD by health professionals, and problems/difficulties they encountered. This research involved family members of 278 HBD cases (males = 211, age 49 years). The major underlying cause was head injury (n = 139). Compared to patients diagnosed pre-2005, a significantly larger proportion of family members after 2005 received information on the condition during the acute phase (within one month) (p < 0.001), including that from physicians (p < 0.001). Nearly half of the families cited a lack of awareness of HBD among the professionals as a problem. In Japan, awareness of HBD in the society is gradually increasing especially after the current diagnostic criteria were implemented, and there has been a steady increase over time in early diagnosis. Yet, there still remain those not appropriately diagnosed. To salvage those patients and the families left behind, we are suggesting several recommendations to further augment clinical practice and the healthcare systems in Japan.

UNASSIGNED: Large language models (LLMs) have shown promising performance in various healthcare domains, but their effectiveness in identifying specific clinical conditions in real medical records is less explored. This study evaluates LLMs for detecting signs of cognitive decline in real electronic health record (EHR) clinical notes, comparing their error profiles with traditional models. The insights gained will inform strategies for performance enhancement.
UNASSIGNED: This study, conducted at Mass General Brigham in Boston, MA, analyzed clinical notes from the four years prior to a 2019 diagnosis of mild cognitive impairment in patients aged 50 and older. We used a randomly annotated sample of 4,949 note sections, filtered with keywords related to cognitive functions, for model development. For testing, a random annotated sample of 1,996 note sections without keyword filtering was utilized. We developed prompts for two LLMs, Llama 2 and GPT-4, on HIPAA-compliant cloud-computing platforms using multiple approaches (e.g., both hard and soft prompting and error analysis-based instructions) to select the optimal LLM-based method. Baseline models included a hierarchical attention-based neural network and XGBoost. Subsequently, we constructed an ensemble of the three models using a majority vote approach.
UNASSIGNED: GPT-4 demonstrated superior accuracy and efficiency compared to Llama 2, but did not outperform traditional models. The ensemble model outperformed the individual models, achieving a precision of 90.3%, a recall of 94.2%, and an F1-score of 92.2%. Notably, the ensemble model showed a significant improvement in precision, increasing from a range of 70%-79% to above 90%, compared to the best-performing single model. Error analysis revealed that 63 samples were incorrectly predicted by at least one model; however, only 2 cases (3.2%) were mutual errors across all models, indicating diverse error profiles among them.
UNASSIGNED: LLMs and traditional machine learning models trained using local EHR data exhibited diverse error profiles. The ensemble of these models was found to be complementary, enhancing diagnostic performance. Future research should investigate integrating LLMs with smaller, localized models and incorporating medical data and domain knowledge to enhance performance on specific tasks.

Studies have suggested associations between gestational exposure to caffeine and adverse outcomes, however the evidence is still limited. Therefore, a systematic review was conducted to investigate the association between prenatal caffeine exposure and neurobehavioral disorders. The MEDLINE (PubMed), EMBASE, Scopus, Web of Science, and LILACS databases were searched. Observational studies involving women with documented caffeine consumption during pregnancy were eligible for inclusion. The outcomes evaluated were behavioral and intellectual development, Attention Deficit Hyperactivity Disorder, and related behaviors. The data were analyzed by qualitative synthesis. The ROBINS-I tool was employed to assess the risk of bias, and the certainty of evidence was evaluated using GRADE (PROSPERO: CRD42023421164). The search yielded fourteen studies that met the inclusion/exclusion criteria. The sample size among pregnant women ranged from 173 to 64,189, and among children ranged from 88 to 49,190. Maternal caffeine consumption during pregnancy ranged from 0 to 1000 mg/day, with the highest levels observed during mid-pregnancy. Seven studies indicated a potential association between prenatal caffeine exposure and neurobehavioral/neurodevelopment deficits, one study showed that prenatal caffeine exposure improved peer problems, and six studies did not show a significant effect of prenatal caffeine consumption on neurobehavioral disorders. The included studies were classified as moderate for the risk of bias and with very low certainty of evidence. Thus, the evidence is insufficient to confirm with certainty that the prenatal caffeine exposure leads to neurobehavioral disorders. Studies heterogenicity, as well as their variable quality and the presence of several confounding factors, generate uncertainty.

OBJECTIVE: Motor neuron disease (MND) is a neurodegenerative disease, progressively impacting function and self-perceived quality of life (QoL). Up to 50% of people with MND can present with cognitive and behavioural impairment, with an associated increase in caregiver burden or strain. However, there has been no systematic exploration of the relationship between QoL and cognitive or behavioural impairment in MND. The aim was to determine if there is a relationship between QoL and cognitive/behavioural impairment in MND, while also supplementarily looking to determine the types of cognitive/behavioural and QoL measures utilised in these studies.
METHODS: A systematic search was performed across multiple databases (PsychINFO, Embase, Medline, AMED) for research published up to the date of February 22, 2023. Studies utilising quantitative methods of measuring QoL, cognitive/behavioural functioning/impairment were included. Findings examining relationships between QoL-cognitive/behavioural impairment were extracted and synthesised.
RESULTS: A total of 488 studies were identified, with 14 studies included in the systematic review. All 14 studies were observational (11 cross-sectional, 3 longitudinal). 13 studies utilised MND non-specific measures, particularly in relation to QoL and cognitive impairment. Of 8 studies measuring behavioural impairment 62.5% (N = 5) found either a lower QoL difference or association. Only 33.3% (N = 4) of 12 studies measuring cognitive impairment found a lower QoL difference or association.
CONCLUSIONS: This systematic review shows that behavioural impairment may have an impact on QoL in MND. There is variability in types of assessments used to measure QoL and also cognitive/behavioural impairment, most of which are disease-non-specific. Recommendations for future research are to use comprehensive disease-specific, multidomain measures to further elucidate the QoL-cognitive/behavioural impairment relationship.

UNASSIGNED: Clinical guidelines recommend incorporating non-cognitive markers like mild behavioral impairment (MBI) and sleep disturbance (SD) into dementia screening to improve detection.
UNASSIGNED: We investigated the longitudinal associations between MBI, SD, and incident dementia.
UNASSIGNED: Participant data were from the National Alzheimer\'s Coordinating Center in the United States. MBI was derived from the Neuropsychiatric Inventory Questionnaire (NPI-Q) using a published algorithm. SD was determined using the NPI-Q nighttime behaviors item. Cox proportional hazard regressions with time-dependant variables for MBI, SD, and cognitive diagnosis were used to model associations between baseline 1) MBI and incident SD (n = 11,277); 2) SD and incident MBI (n = 10,535); 3) MBI with concurrent SD and incident dementia (n = 13,544); and 4) MBI without concurrent SD and incident dementia (n = 11,921). Models were adjusted for first-visit age, sex, education, cognitive diagnosis, race, and for multiple comparisons using the Benjamini-Hochberg method.
UNASSIGNED: The rate of developing SD was 3.1-fold higher in older adults with MBI at baseline compared to those without MBI (95% CI: 2.8-3.3). The rate of developing MBI was 1.5-fold higher in older adults with baseline SD than those without SD (95% CI: 1.3-1.8). The rate of developing dementia was 2.2-fold greater in older adults with both MBI and SD, as opposed to SD alone (95% CI:1.9-2.6).
UNASSIGNED: There is a bidirectional relationship between MBI and SD. Older adults with SD develop dementia at higher rates when co-occurring with MBI. Future studies should explore the mechanisms underlying these relationships, and dementia screening may be improved by assessing for both MBI and SD.

UNASSIGNED: Distinguishing functional seizures (FS) from epileptic seizures (ES) poses a challenge due to similar clinical manifestations. The creation of a clinical scoring system that assists in accurately diagnosing patients with FS would be a valuable contribution to medical practice. This score has the potential to enhance clinical decision-making and facilitate prompt diagnosis of patients with FS.
UNASSIGNED: Participants who met the inclusion criteria were randomly divided into three distinct groups: training, validation, and test cohorts. Demographic and semiological variables were analyzed in the training cohort by univariate analyses. Variables that showed a significant difference between FS and ES were then further scrutinized in two multivariate logistic regression models. The CFSS was developed based on the odds ratio of the discriminating variables. Using the validation group, the optimal cutoff value was determined based on the AUC, and then the CFSS was evaluated in the test cohort to assess its performance.
UNASSIGNED: The developed score yielded an AUC of 0.78 in the validation cohort, and a cutoff point of 6 was established with a focus on maximizing sensitivity without significantly compromising specificity. The score was then applied in the test cohort, where it achieved a sensitivity of 86.96% and a specificity of 73.81%.
UNASSIGNED: We have developed a new tool that shows promising results in identifying patients suspicious of FS. With further analysis through prospective studies, this innovative, simple tool can be integrated into the diagnostic process of FS.

OBJECTIVE: The primary aim was to evaluate apathy assessment measures in relation to cognitive impairment among Hispanic/Latin Americans.
METHODS: A systematic review on the relationship between apathy and cognitive impairment among Hispanic/Latin Americans across normal aging and neurocognitive disorders was conducted according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and using APA PsycInfo, Embase, and PubMed databases. Inclusion criteria required (1) a sample of English or Spanish-speaking adults ages 18 years and older, (2) with measures of apathy, (3) assessment of cognitive functioning or diagnosis of neurocognitive disorder, (4) with at least 18.5% Hispanic/Latin American represented in the sample.
RESULTS: Only 14 papers met criteria to be included in this review. Of the 12 cross-sectional studies, 9 demonstrated significant associations between increased apathy and cognitive impairment, 1 demonstrated a descriptive difference between apathy and cognitive status (ie, no hypothesis test conducted), while 2 demonstrated null effects. These cross-sectional studies consisted of community and clinic samples of participants across North and South America. Two longitudinal studies conducted in North America demonstrated non-significant associations of apathy with cognitive status.
CONCLUSIONS: The Neuropsychiatric Inventory (NPI) and Neuropsychiatric Inventory Questionnaire (NPI-Q) apathy subscales were the most used measures for apathy in this review (85.7% of included studies). However, validity evidence from a review of apathy measures has warranted caution against the use of the NPI outside the context of screening for apathy. This potential measurement bias with Hispanic/Latin Americans apathy research limits conclusions drawn from the present review.

Description Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) viral infection is notable for a high degree of symptom diversity. Emerging evidence suggests viral invasion of the central nervous system. Therefore, serious neurological and psychiatric manifestations are anticipated. We present the case of a 67-year-old male physician who has a history of stable bipolar disorder for decades and was recently hospitalized for persistent COVID-19 symptoms with documented positive serology. He presented with new and acute onset neuropsychiatric symptoms of disinhibition proximate to the viral infection. We postulate neuroinvasion as the putative origin of the patient\'s psychiatric instability. Furthermore, an investigation is needed to expand upon our understanding of the potential for neuropsychiatric morbidity related to SARS-CoV-2 for prompt diagnosis and appropriate management. There are also no current studies addressing the risks for neurological and psychiatric symptomatology in SARS-CoV-2 infected patients with persistent chronic mental illness.

Studies suggest that gestational exposure to lead (Pb) is related to spontaneous abortions, preterm birth, lower infant birth weight and length, and neurological dysfunctions. However, the evidence about its effects during pregnancy exposure on fetal and child development is still poor. Thus, the aim of this systematic review was to verify the association between prenatal exposure to Pb and the occurrence of neurobehavioral deficits, miscarriages, and child mortality. Observational studies with pregnant women exposed to Pb during pregnancy were included, without gender or ethnicity restrictions. The MEDLINE, Cochrane Library, EMBASE, Scopus, Web of Science, and LILACS databases were searched. The reading of titles and abstracts was conducted, followed by reading in full format and data extraction, that were performed independently by two reviewers. The included studies were evaluated by Downs and Black tool and qualitatively synthesized. Certainty of evidence was assessed by Grading of Recommendations Assessment, Development, and Evaluations (GRADE). The study protocol was registered with the Prospective Registry of Systematic Reviews (PROSPERO; CRD42022296750). Among twenty-one studies included, sixteen were classified as prospective cohort, two case-control, one nested case-control, one cohort, and one longitudinal study. No study that evaluated child mortality associated with gestational Pb exposure was found. There is a very low certainty of evidence in the association of gestational Pb exposure and neurobehavioral deficits or miscarriages. This systematic review reflects the poor evidence and the challenges of human toxicology studies, since it was not possible to associate gestational Pb exposure to neurobehavioral deficits, miscarriages, and child mortality.