Primary spindle cell sarcomas of the palatine tonsil are exceedingly rare malignant neoplasms. Due to their overlapping histopathological features with spindle cell variants of epithelial and other mesenchymal tumours, diagnosis is challenging and requires careful clinicopathological correlation with immunohistochemistry. Furthermore, the rarity of head and neck sarcomas results in poorly defined management protocols. A 65-year-old man presented with a foreign body sensation in the throat and odynophagia lasting for two months. An examination revealed a 4 cm × 3 cm lobulated, firm mass occupying the left tonsillar fossa and crossing the midline. Contrast-enhanced CT scans demonstrated a well-defined enhancing lesion confined to the left lateral oropharyngeal wall, with no involvement of the base of the tongue or the epiglottis. No cervical lymphadenopathy or distant metastasis was identified on staging evaluation. Fine needle aspiration indicated malignant spindle cells. The patient underwent coblation-assisted transoral excision with adequate margins. Histopathology revealed spindle cells arranged in short fascicles, exhibiting moderate eosinophilic cytoplasm, nuclear hyperchromasia, and occasional mitotic figures. No squamous differentiation was identified. Immunohistochemistry demonstrated vimentin positivity and negativity for pan-cytokeratin, p63, EMA, S100, desmin, CD99, and CD34, supporting the diagnosis of spindle cell sarcoma. The postoperative recovery was uneventful. The patient remains disease-free after three years of follow-up. Primary tonsillar spindle cell sarcoma is a rare diagnostic entity that requires a broad immunohistochemical panel and careful histopathological evaluation. Complete surgical excision remains the cornerstone of management for localised disease, and long term follow up is essential. Reporting such rare presentations aids in improving the understanding of disease behaviour and guiding future treatment strategies.
The epidemiology of lipid diseases in India raises serious public health concerns. The increasing prevalence of lipid abnormalities is caused by a number of factors, including dietary practices, a sedentary lifestyle, genetic susceptibility and socioeconomic status. In comparison to rural settings, metropolitan areas have a much greater prevalence of hypercholesterolaemia and hypertriglyceridaemia. Furthermore, lipid problems are more common in men than in women, indicating a gender gap. To combat the risk of cardiovascular illnesses, including lipid disorders, the study emphasises the critical need for focused interventions, such as public health campaigns, lifestyle changes and enhanced access to healthcare services.
Introduction Diarrheal dehydration is well known with specific guidelines. However, non-diarrheal dehydration is often unreported. To date, there has not been a single study to report the prevalence of dehydration due to non-diarrheal conditions in pediatric patients. Materials and methods Electronic medical record (EMR) data from January 2017 to March 2023 for patients with non-diarrheal illnesses meeting inclusion and exclusion criteria were retrieved and analyzed to understand the prevalence of dehydration due to non-diarrheal conditions in Pediatric patients. Further, the associated conditions for these patients with dehydration were also evaluated. Results Of the total, 18,89,680 pediatric patients, merely 1,888 patients (0.09%) had dehydration-related complaints recorded in the prescription. The percentage was strikingly less than the expectations from real-world data. Respiratory tract infections (RTIs) and fever were observed to be the most common associated non-diarrheal conditions for patients with dehydration. Conclusion There is a need to bridge the reporting gap by creating awareness among pediatricians and physicians to manage dehydration in non-diarrheal illnesses appropriately for better patient outcomes.
Serious adverse events (SAEs) remain a critical concern in oncology clinical trials, directly impacting patient safety and the development of new therapies. With the growing use of targeted treatments and immunotherapies, treatment-related toxicities have become more complex and less predictable than with conventional chemotherapy. Traditional reactive approaches are increasingly inadequate, necessitating proactive strategies for early identification and management of SAEs. Advances in artificial intelligence (AI) and predictive analytics have enabled the early detection of adverse events and the identification of high-risk patients (6,7,20). Additionally, decentralized trials and wearable technologies now allow continuous, real-world patient monitoring (16). Despite these innovations, challenges such as data quality, algorithm transparency, and evolving regulatory frameworks limit their widespread adoption. This review synthesizes current knowledge on SAE risk factors, discusses monitoring and management strategies, and highlights emerging technologies aimed at enhancing patient safety in oncology trials.
Artificial intelligence (AI) and digital health technologies are increasingly reshaping neurological clinical research by enabling more precise diagnostics, continuous patient monitoring, and data-driven therapeutic strategies. Applications such as machine learning–based neuroimaging analysis, wearable neurological sensors, remote electroencephalography (EEG) monitoring, brain–computer interfaces, and digital biomarkers are now widely explored in disorders including Alzheimer’s disease, Parkinson’s disease, epilepsy, stroke, and multiple sclerosis. Although these innovations have improved research efficiency and expanded opportunities for personalized neurology, they also introduce complex ethical and regulatory concerns that remain insufficiently addressed within existing research governance frameworks. This critical review examines the major ethical challenges associated with AI-enabled neurological research, with particular emphasis on informed consent in cognitively vulnerable populations, neurodata privacy and security, algorithmic bias, explainability of AI systems, digital inequities, and regulatory oversight. Unlike conventional healthcare datasets, neurological data may reveal highly sensitive information related to cognition, behavior, emotional processing, and personal identity, thereby raising unique neuroethical concerns regarding autonomy and mental privacy. Drawing on recent literature published between 2021 and 2026, this review critically evaluates emerging ethical tensions in decentralized and AI-assisted neurology research while discussing practical approaches for responsible implementation. The paper argues that the future integration of AI into neurological clinical research will depend not only on technological advancement but also on the development of ethically resilient governance frameworks capable of protecting patient rights, ensuring transparency, minimizing bias, and maintaining public trust in increasingly data-intensive neurological ecosystems.
