Anti-Black Racism Resource (Grades 4-6)

Anti-Black Racism Resource (Grades 4-6

Comparative Analysis of LLMs in Dry Eye Syndrome Healthcare Information

Background/Objective: Dry eye syndrome affects 16 million Americans with USD 52 billion in annual healthcare costs. With large language models (LLMs) increasingly used for healthcare information, understanding their performance in delivering equitable dry eye guidance across diverse populations is critical. This study aims to evaluate and compare five major LLMs (Grok, ChatGPT, Gemini, Claude.ai, and Meta AI) regarding dry eye syndrome information delivery across different demographic groups. Methods: LLMs were queried using standardized prompts simulating a 62-year-old patient with dry eye symptoms across four demographic categories (White, Black, East Asian, and Hispanic males and females). Responses were analyzed for word count, readability, cultural sensitivity scores (0–3 scale), keyword coverage, and response times. Results: Significant variations existed across LLMs. Word counts ranged from 32 to 346 words, with Gemini being the most comprehensive (653.8 ± 96.2 words) and Claude.ai being the most concise (207.6 ± 10.8 words). Cultural sensitivity scores revealed Grok demonstrated highest awareness for minority populations (scoring 3 for Black and Hispanic demographics), while Meta AI showed minimal cultural tailoring (0.5 ± 0.5). All models recommended specialist consultation, but medical term coverage varied significantly. Response times ranged from 7.41 s (Meta AI) to 25.32 s (Gemini). Conclusions: While all LLMs provided appropriate referral recommendations, substantial disparities exist in cultural sensitivity, content depth, and information delivery across demographic groups. No LLM consistently addressed the full spectrum of dry eye causes across all demographics. These findings underscore the importance for physician oversight and standardization in AI-generated healthcare information to ensure equitable access and prevent care delays

LINC-19. Epidemiological Profile And Management Trends in Pediatric Brain Tumour Patients – 15 Year Experience From a Tertiary Neuro-Oncology Centre In South Asia

Abstract INTRODUCTION: Brain tumour in pediatric age group are the most common solid tumour. Commonly occurring tumours include astrocytomas, medulloblastoma and ependymoma. Astrocytoma and medulloblastoma are common in Europe as compared to the Asian countries. AIM: To study the epidemiological profile and trends in management of pediatric brain tumor patients treated at a tertiary Neuro-oncology center. MATERIALS AND METHODS: This a retrospective audit of a prospectively maintained neurosurgical database from January 2007 to December 2021. All pediatric cases (&amp;lt; 18 years) operated by the neurosurgical oncology unit during the study period were included for analysis. CSF diversions and non oncologic surgical procedures were excluded. Demography, referral pattern, surgical and pathological variables of these patients was analyzed from the database and electronic medical records. Patients with missing data were excluded from analysis. RESULTS: 668 patients underwent oncologic surgical procedures. There was a male preponderance (60%) and 35% of children were in the age group of 5-11 years. Hospital received maximum referral from the parent city and state (46%) followed by north india (21%). Supratentorial tumours (52 %) were seen more commonly as compared to infratentorial tumours (39 %). Astrocytoma (31 %) and embryonal tumours( 25 %) were the common histological types. On subset analysis, both astrocytic (70%) and embryonal tumours (57%) were more common in children more than five years. Intraoperative neuromonitoring, intraoperative ultrasound and navigation were used during the surgical procedures as necessary. CONCLUSION: This study is one of the largest single institution analysis of pediatric brain tumours demonstrating trends in the demographic, surgical and pathological variables over 15 years and the observed pattern is similar to published literature from Indian subcontinent.</jats:p

Psychoactive drug prescribing by Dutch child and adolescent psychiatrists

Aim: To gain more insight into the prescribing of psychoactive drugs by Dutch child psychiatrists. Methods: A questionnaire was sent to all child psychiatrists in the Netherlands. Questions were asked about the prescribing of antidepressants, antipsychotics, anxiolytics and psychostimulants for psychiatric disorders in children. Results: The preference of specific antidepressants, antipsychotics and anxiolytics depends on the disorder. For different disorders, off-label prescribing varies from 19 to 71%. Conclusion: Preferences differ widely. Off-label drug prescribing is high. More studies on the efficacy and safety of psychoactive drugs in children are therefore required