Impact of environmental pollutants on pediatric brain tumor incidence in New Jersey.

OBJECTIVE: The relationship between environmental contaminants and brain tumor incidence in adults has been thoroughly explored but research into how these contaminants affect pediatric brain tumor (PBT) incidence has not been explored. Children, typically having more limited geographical movement and thus more consistent environmental contaminant exposure, might offer more reliable insights into which environmental contaminants affect the incidence of brain tumors. The present study is the first to focus on exploring whether a possible association exists between the incidence of PBTs and exposure to environmental pollutants in New Jersey (NJ). METHODS: Linear regressions were run between PBT incidence and the concentration of air quality pollutants such as Ozone (O3), Particulate Matter 2.5 (PM2.5), Particulate Matter 10 (PM10), and Carbon Monoxide (CO). Similarly, linear regressions were run between PBT incidence and Elevated Blood Lead Levels (BLL). RESULTS: The study observed a significant positive relationship between O3 and PBT incidence (ß = 0.34, p = 0.028). However, the relationship between PBT incidence, and environmental pollutants such as CO (ß = 0.0047, p = 0.098), PM2.5 (ß = -0.2624, p = 0.74), and PM10 (ß = -0.7353, p = 0.073) were found to be nonsignificant. For elevated BLL, nonsignificant relationships with PBT incidence were observed at 10-14 µg/dL (ß = -39.38, p = 0.30), 15-19 µg/dL (ß = -67.00, p = 0.21), and 20-44 µg/dL (ß = -201.98, p = 0.12). CONCLUSIONS: The results indicate a possible impact of O3 on the incidence of PBTs in NJ. In contrast to the significant links found in prior studies of adult brain tumors, the associations between PBT occurrence and particulate matter were not significant. These findings highlight the importance of further investigating how environmental factors, especially O3, relate to PBTs.

Analysis of Concussions Reported in American Professional Football Injury Reports in the 2019 Through 2023 Regular Seasons.

OBJECTIVE: The National Football League (NFL) has seen increasing scrutiny regarding its management of concussions, especially following an on-field incident involving the Miami Dolphins' quarterback Tua Tagovailoa in the 2022 season. We hope to elucidate the recent trends in the diagnosis and management of concussions during the course of 5 NFL seasons from 2019 to 2023. METHODS: We queried the NFL injury reports from the 2019 through 2023 database recording players listed with concussions. The weeks missed were calculated using the NFL game logs. Players' concussions that did not occur in the games, those complicated by other injuries, and those affected by roster status were excluded. RESULTS: Searches of the NFL injury reports resulted in the identification of 664 of 692 concussions (96%) that occurred in regular season games across the 2019-2023 seasons. During the course of these 5 seasons, 31% of the players returned without missing a game, 39% of the players missed 1 game, and 30% of the players missed ≥2 games. No significant difference in the number of concussions per game or weeks missed was observed across the seasons observed. Players with concussions on teams that made the playoffs saw fewer weeks missed than those on non-playoff teams (0.86 vs. 1.37; P = 0.002). CONCLUSIONS: Since the start of the 2021 NFL season, an increasing incidence of concussions has been noted; however, there was no change observed in the number of weeks missed after the concussions. Trends in the rates of concussions across the seasons remain largely stable, despite increased scrutiny over concussions in the sport.

Can Artificial Intelligence Mitigate Missed Diagnoses by Generating Differential Diagnoses for Neurosurgeons?

BACKGROUND/OBJECTIVE: Neurosurgery emphasizes the criticality of accurate differential diagnoses, with diagnostic delays posing significant health and economic challenges. As large language models (LLMs) emerge as transformative tools in healthcare, this study seeks to elucidate their role in assisting neurosurgeons with the differential diagnosis process, especially during preliminary consultations. METHODS: This study employed 3 chat-based LLMs, ChatGPT (versions 3.5 and 4.0), Perplexity AI, and Bard AI, to evaluate their diagnostic accuracy. Each LLM was prompted using clinical vignettes, and their responses were recorded to generate differential diagnoses for 20 common and uncommon neurosurgical disorders. Disease-specific prompts were crafted using Dynamed, a clinical reference tool. The accuracy of the LLMs was determined based on their ability to identify the target disease within their top differential diagnoses correctly. RESULTS: For the initial differential, ChatGPT 3.5 achieved an accuracy of 52.63%, while ChatGPT 4.0 performed slightly better at 53.68%. Perplexity AI and Bard AI demonstrated 40.00% and 29.47% accuracy, respectively. As the number of considered differentials increased from 2 to 5, ChatGPT 3.5 reached its peak accuracy of 77.89% for the top 5 differentials. Bard AI and Perplexity AI had varied performances, with Bard AI improving in the top 5 differentials at 62.11%. On a disease-specific note, the LLMs excelled in diagnosing conditions like epilepsy and cervical spine stenosis but faced challenges with more complex diseases such as Moyamoya disease and amyotrophic lateral sclerosis. CONCLUSIONS: LLMs showcase the potential to enhance diagnostic accuracy and decrease the incidence of missed diagnoses in neurosurgery.

A scoping review of neuropsychological assessment for Asian Indians in the United States - research and clinical recommendations.

Objective: There is an increasing focus on understanding health disparities among various cultural groups in the United States. The need for heterogeneity in norms and test stimuli across ethnically diverse individuals are being increasingly recognized. However, to date it remains unknown whether and to what extent differences in cognitive norms and tests exist in Asian Indians, a fast-growing population in the U.S. It is essential to understand these differences to improve diagnostic accuracy and provide timely and appropriate clinical care. Method: In this study, we conducted a scoping review of available cognitive tests that were normed, developed, or adapted for Asian Indians living in the U.S. Results: The results suggested a paucity of norms and tests specifically examining cognition in this community. Conclusions: Based on the findings, we provide suggestions for research directions focusing on the development of culturally sensitive neuropsychological tools, normative data representative of this demographic, and interventions addressing healthcare access barriers. Overall, this review provides readers with relevant clinical information to immediately enhance patient care as well as provide actionable items in research to improve the future utility of neuropsychology for Asian Indians in the United States.

Can Publicly Available Artificial Intelligence Successfully Identify Current Procedural Terminology Codes for Common Procedures in Neurosurgery?

OBJECTIVE: Coding for neurosurgical procedures is a complex process that is dynamically changing year to year, through the annual introduction and removal of codes and modifiers. The authors hoped to elucidate if publicly available artificial intelligence (AI) could offer solutions for neurosurgeons with regard to coding. METHODS: Multiple publicly available AI platforms were asked to provide Current Procedural Terminology (CPT) codes and Revenue Value Units (RVU) values for common neurosurgical procedures of the brain and spine with a given indication for the procedure. The responses of platforms were recorded and compared to the currently valid CPT codes used for the procedure and the amount of RVUs that would be gained. RESULTS: Six platforms and Google were asked for the appropriate CPT codes for 10 endovascular, spinal, and cranial procedures each. The highest performing platforms were as follows: Perplexity.AI identified 70% of endovascular, BingAI identified 55% of spinal, and ChatGPT 4.0 with Bing identified 75% of cranial CPT codes. With regard to RVUs, the top performer gained 78% of endovascular, 42% of spinal, and 70% of cranial possible RVUs. With regard to accuracy, AI platforms on average outperformed Google (45% vs. 25%, P = 0.04236). CONCLUSIONS: The ability of publicly available AIs to successfully code for neurosurgical procedures holds great promise in the future. Future development of AI should focus on improving accuracy with regard to CPT codes and providing supporting documentation for its decisions. Improvement on the existing capabilities of AI platforms can allow for increased operational efficiency and cost savings for practices.

A narrative review of the biopsychosocial and health characteristics of Asian Indians in the United States: Clinical and research implications for neuropsychological functioning.

Objective: The prevailing scientific literature aggregates Asians living in America into one omnibus category and thus can problematically result in a subpar and at times inaccurate understanding of health, social and cultural factors necessary for competent and informed medical care. Method: A literature search was conducted by cultural experts familiar with Asian Indian culture with a focus on immigrants from this community living in the US. Database using search engines was sought in the following domains: immigration patterns, prevalence for key medical and neurological conditions commonly associated with cognitive dysfunction, psychiatric/psychological needs in the community, some preliminary neuropsychological testing considerations while working with this community, and treatment considerations that could affect adherence and efficacy of outcomes. Articles were selected from 2000 to the most recent date, with emphasis on compiling information from review papers and meta-analysis from the past decade. Conclusions: Asian Indians living in the US are distinct from the larger Asian American community. Immigration trends underscore that Asian Indians have a bimodal distribution of wealth. Regarding medical conditions, a key and highly concerning finding is the higher prevalence of cardiovascular risk factors, especially in young males. The lack of non-existent cognitive data in this community is glaring and should serve as an impetus for conducting high-priority research in this community. Preliminary neuropsychological testing considerations are discussed from a practical perspective with emphasis on multilingualism and region of origin. Finally, treatment considerations include understanding attitudes and beliefs regarding traditional medicine.

Language and Acculturation: Neuropsychological Sequalae of COVID-19 in Indian Americans.

Coronavirus 2019 (SARS-CoV-2; COVID-19) has significant mental health and neuropsychological consequences, but data are insufficient on these specific implications of COVID-19, especially for Indian American patients. Few studies have critically explored risk factors and neuropsychological assessment considerations from a cultural and linguistic perspective, including how they impact the evaluation process for Indian Americans. The present paper focuses on cultural and linguistic considerations for case conceptualization, ethical challenges for best practices, and a specific example with a middle-aged Indian American woman. The need for a greater contextual understanding is emphasized as a step forward in establishing methodological and procedural guidelines for working with patients of Indian descent in the United States.

Third Window Syndrome: Surgical Management of Cochlea-Facial Nerve Dehiscence.

Objective: This communication is the first assessment of outcomes after surgical repair of cochlea-facial nerve dehiscence (CFD) in a series of patients. Pre- and post-operative quantitative measurement of validated survey instruments, symptoms, diagnostic findings and anonymous video descriptions of symptoms in a cohort of 16 patients with CFD and third window syndrome (TWS) symptoms were systematically studied. Study design: Observational analytic case-control study. Setting: Quaternary referral center. Patients: Group 1 had 8 patients (5 children and 3 adults) with CFD and TWS who underwent surgical management using a previously described round window reinforcement technique. Group 2 had 8 patients (2 children and 6 adults) with CFD who did not have surgical intervention. Interventions: The Dizziness Handicap Inventory (DHI) and Headache Impact Test (HIT-6) were administered pre-operatively and post-operatively. In addition, diagnostic findings of comprehensive audiometry, cervical vestibular evoked myogenic potential (cVEMP) thresholds and electrocochleography (ECoG) were studied. Symptoms before and after surgical intervention were compared. Main outcome measures: Pre- vs. post-operative DHI, HIT-6, and audiometric data were compared statistically. The thresholds and amplitudes for cVEMP in symptomatic ears, ears with cochlea-facial nerve dehiscence and ears without CFD were compared statistically. Results: There was a highly significant improvement in DHI and HIT-6 at pre- vs. post-operative (p < 0.0001 and p < 0.001, respectively). The age range was 12.8-52.9 years at the time of surgery (mean = 24.7 years). There were 6 females and 2 males. All 8 had a history of trauma before the onset of their symptoms. The mean cVEMP threshold was 75 dB nHL (SD 3.8) for the operated ear and 85.7 dB (SD 10.6) for the unoperated ear. In contrast to superior semicircular canal dehiscence, where most ears have abnormal ECoG findings suggestive of endolymphatic hydrops, only 1 of 8 operated CFD ears (1 of 16 ears) had an abnormal ECoG study. Conclusions: Overall there was a marked improvement in DHI, HIT-6 and symptoms post-operatively. Statistically significant reduction in cVEMP thresholds was observed in patients with radiographic evidence of CFD. Surgical management with round window reinforcement in patients with CFD was associated with improved symptoms and outcomes measures.

Integrative rehabilitation of elderly stroke survivors: the design and evaluation of the BrightArm™.

PURPOSE: To describe the development of the BrightArm upper extremity rehabilitation system, and to determine its clinical feasibility with older hemiplegic patients. METHOD: The BrightArm adjusted arm gravity loading through table tilting. Patients wore an arm support that sensed grasp strength and communicated wirelessly with a personal computer. Games were written to improve cognitive, psychosocial and the upper extremity motor function and adapted automatically to each patient. The system underwent feasibility trials spanning 6 weeks. Participants were evaluated pre-therapy, post-therapy, and at 6 weeks follow-up using standardized clinical measures. Computerized measures of supported arm reach and game performance were stored on a remote server. RESULTS: Five participants had clinically significant improvements in their active range of shoulder movement, shoulder strength, grasp strength, and their ability to focus. Several participants demonstrated substantially higher arm function (measured with the Fugl-Meyer test) and two were less-depressed (measured with the Becks Depression Inventory, Second Edition). The BrightArm technology was well-accepted by the participants, who gave it an overall subjective rating of 4.1 on a 5 point Likert scale. CONCLUSIONS: Given these preliminary findings, it will be beneficial to evaluate the BrightArm through controlled clinical trials and to investigate its application to other clinical populations.

Clinical validity of the children's category test-level 2 in a mixed sample of school-aged children.

The Children's Category Test (CCT) is a widely used measure of problem solving with adequate psychometric properties. Yet, Shriver and Vacc (n.d.) were fairly critical of the CCT in The Mental Measurement Yearbook and highlighted its limitations. Thus, to explore the clinical validity of the widely used CCT-Level 2 (CCT-2) version, results of that test were analyzed post hoc in a sample of 265 children with mixed etiology referred for neuropsychological testing at a private outpatient laboratory. Overall, the CCT-2 correctly classified 57.7% of the sample, with 72.2% accuracy in classifying the Neuropsychologically Normal Clinical Comparison group but only 54% for the Brain Injured group. Predictive power was further reduced when the Brain Injury group was subdivided. Predictive power fell to 27.2%, with the best predictions coming for the Mental Retardation (MR) group (58.3%) and the lowest for the Learning Disorder NOS group (2.5%). The current findings suggest that the CCT's clinical application should be used with caution.