Dharmsinh Desai University

Background: Otitis media with effusion (OME) is among the most prevalent childhood conditions, characterized by the accumulation of fluid within the middle ear cleft in the absence of acute infectious signs. The resultant conductive hearing loss, though often transient, may compromise speech, language, and cognitive development during critical developmental periods. Ventilation tube (grommet) insertion remains the most widely performed surgical intervention for persistent OME associated with hearing impairment; however, the magnitude and durability of audiometric improvement following grommet placement across different age groups and OME laterality patterns warrant further prospective evaluation. Methods: This prospective interventional study enrolled 180 children (312 ears) aged 2–12 years with bilateral or unilateral OME persisting for ≥3 months, who underwent grommet insertion at a tertiary otolaryngology center from February 2022 to January 2024. Pure-tone audiometry and tympanometry were performed preoperatively and at 2 weeks, 3 months, 6 months, and 12 months postoperatively. The primary outcome was change in pure-tone average (PTA) hearing threshold. Results: The mean preoperative PTA was 34.82 ± 8.47 dB HL, which improved significantly to 16.43 ± 5.21 dB HL at 2 weeks (p < 0.001), 14.87 ± 4.96 dB HL at 3 months (p < 0.001), 15.52 ± 5.38 dB HL at 6 months (p < 0.001), and 18.74 ± 6.83 dB HL at 12 months (p < 0.001). Hearing returned to normal thresholds (≤20 dB HL) in 82.4% of ears at 3 months. Younger age (<5 years), bilateral OME, and mucoid effusion type were associated with slightly less favorable audiometric recovery at 12 months. Tympanosclerosis was observed in 28.2% of operated ears, and post-tube otorrhea occurred in 11.5%. Conclusion: Grommet insertion produces a significant and rapid hearing improvement in children with chronic OME, with maximum benefit observed within the first 3 months. Audiometric gains diminish gradually by 12 months, paralleling natural tube extrusion. Younger children and those with bilateral mucoid effusion warrant close audiological follow-up.

Introduction: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder associated with significant morbidity through micro- and macrovascular complications. Serum uric acid (SUA) has emerged as a potential biomarker linked to glycaemic dysregulation, dyslipidaemia, and early renal impairment. Despite its clinical relevance, SUA levels in T2DM patients remain understudied in the Indian context, particularly in Gujarat. Materials and Methods: A cross-sectional study was conducted at a tertiary care hospital, Pramukh Swami Medical College, Karamsad, and enrolling 200 participants: 100 T2DM patients and 100 age-sex–matched healthy controls. Biochemical parameters including fasting plasma glucose (FPG), HbA1c, serum uric acid, lipid profile, serum creatinine, and urine albumin-to-creatinine ratio (UACR) were measured. Statistical analysis was performed using Epi info version 7. Results: Serum uric acid was significantly elevated in T2DM patients (6.43 ± 1.19 mg/dL) compared to controls (4.84 ± 0.99 mg/dL; p<0.001). Hyperuricaemia was present in 34% of diabetic patients versus 8% of controls. SUA correlated positively with triglycerides (r=0.46), FPG (r=0.34), HbA1c (r=0.29), and UACR, and negatively with HDL-C (r=−0.31). ROC analysis revealed SUA >6.2 mg/dL as the optimal cut-off for predicting albuminuria (AUC=0.76; sensitivity 72%, specificity 68%). Conclusion: Serum uric acid is significantly elevated in T2DM patients and independently correlates with atherogenic dyslipidaemia and early renal damage. Routine SUA monitoring may serve as an accessible and costeffective biomarker for cardiorenal risk stratification in diabetic populations.

Coronary artery disease is the leading cause of mortality worldwide and presents with disproportionately severe patterns in the South Asian population. Coronary artery bypass grafting remains the most durable revascularization modality. Yet, its evolution in India has been inconsistent, perhaps in part due to the absence of a dedicated scientific body focused exclusively on coronary surgery. Following the successful completion of the PROMOTE Patency Trial, the first multicenter randomized clinical trial in Indian cardiac surgery, a motivated group of surgeons recognized the need for sustained collaboration, research, and subspecialty-driven progress. This realization led to the formation of the Society of Coronary Surgeons in December 2020 under the leadership of its Founder President, L. R. Sajja, during the unprecedented disruptions of the COVID-19 pandemic. The society’s creation marks a pivotal advance in India’s effort to cultivate indigenous coronary research, data collection, standardized training, and region-specific guidelines. This perspective outlines the origins of the Society of Coronary Surgeons, the evolution of coronary surgery, the need for a coronary subspecialty society in India, and the importance of establishing a national coronary surgery database tailored to Indian patient characteristics. The Society of Coronary Surgeons represents both a scientific necessity and a transformative opportunity for the future of coronary surgery in India.

This study investigates the issue of a country’s cybersecurity evolving into a justification for amending the scope of or terminating an international commercial contract. Therefore, the hypothesis is grounded in the neglect of cybersecurity-related issues during the negotiation of certain types of international commercial contracts, as well as in the drafting of their clauses. This underscores the need for an analytical approach to trace the emergence of such risks. The identification of these risks by the public authority responsible for overseeing cybersecurity may result in the suspension of the performance of the international commercial contract. This measure affects the national public or private party that has contracted with a foreign supplier providing services remotely via the internet. The suspension remains in effect until a decision is made to amend the contract’s scope by removing provisions that pose a cybersecurity threat, or to terminate the contract if such amendments are not feasible. This study reveals that the failure to include provisions addressing cybersecurity risks during the negotiation and drafting stages of an international commercial contract often initiates the rationale for its amendment or termination. Conversely, the inclusion of such provisions during the performance phase serves as the true reflection of these effects. To adequately address this type of risk, it is essential to focus on three interrelated levels: the first pertains to the contractual arrangements for managing risks associated with the country’s cybersecurity; the second concerns legislative and institutional regulation; and the third is characterized by the technical and technological infrastructure that the concerned country must establish.

Warthin’s tumor is the second most common tumor of parotid gland consisting of lymphoid and epithelial components. It is seen in the elderly population and is more common in males. It is a benign tumor and has strong association with smoking. Malignant transformation is very rare in Warthin’s tumor and can involve both the lymphoid, as well as epithelial components. Here we present a rare case of malignant transformation in Warthin’s tumor in a female patient. She presented with an infra-auricular swelling on right side for 1 year with rapid increase in size of the swelling since last 3 months. Imaging studies showed possibility of a benign parotid tumor. Fine needle aspiration cytology showed features of Warthin’s tumor. Histopathology and Immunohistochemistry confirmed the diagnosis of malignant transformation of Warthin’s tumor to adenocarcinoma.

Early diagnosis of oral and systemic diseases remains a major challenge due to limitations in conventional invasive procedures. This review addresses the critical need for non-invasive, accessible diagnostics by examining the potential of saliva as an alternative diagnostic fluid. The main objective is to synthesize current knowledge on salivary biomarkers and technological innovations that enhance early detection capabilities. Methodologically, the review integrates evidence from proteomic, genomic, and metabolomic studies, as well as recent advances in microfluidic point-of-care devices. Key findings highlight that saliva contains a rich array of biomarkers, including cytokines, microRNAs, and extracellular vesicles, that can accurately reflect both local oral pathologies, such as dental caries and oral cancer, and systemic conditions, including diabetes, cardiovascular diseases, autoimmune disorders, and neurodegenerative diseases. The analysis further emphasizes that portable biosensors and lab-on-chip platforms are rapidly improving diagnostic sensitivity and enabling decentralized testing. Notwithstanding these encouraging advancements, issues with biological variability, standardization, and regulatory validation still exist. This review underscores the significance of interdisciplinary collaboration to overcome these barriers and fully integrate salivary diagnostics into routine healthcare. The implications are profound: widespread adoption could transform preventive medicine by providing patient-friendly, real-time monitoring tools that improve health outcomes globally.

Surgical intervention triggers a complex physiological cascade, also known as the surgical stress response, which entails well-coordinated immunological, metabolic, and neuroendocrine processes. This systematic review summarizes the existing evidence from 11 studies published between 2015 and 2025, investigating the underlying mechanisms, regulatory interactions, and clinical implications of this multifactorial response. Central stress pathway activation triggers immediate hormonal increase, stabilizing circulation and energy reserves, but chronic endocrine stimulation has the potential to increase metabolic and immune imbalances and results in a delayed recovery. The ensuing immune dynamics display an initial inflammatory phase followed by transient suppression, collectively influencing tissue repair and infection susceptibility. Parallel metabolic adaptations enhance energy production but often induce insulin resistance and protein catabolism, contributing to postoperative fatigue and functional decline. These interdependent mechanisms form a unified neuroendocrine-immune-metabolic network that can shift from adaptive to maladaptive under persistent stress. New evidence indicates that biomarkers such as cortisol, IL-6, glucose, and albumin serve as predictors of postoperative complications, including infection, impaired wound healing, and increased morbidity. Various perioperative interventions, such as the Enhanced Recovery After Surgery programs, immunonutrition, and metabolic administration, exhibit the possibility of maximizing such responses. The review combines both mechanistic and clinical perspectives to promote precision-based perioperative tactics to enhance surgical and recovery outcomes.

The most common kind of crack, and one that happens rather often, is a wrist fracture. Even though X-ray medical imaging is useful for identifying wrist fractures, the depiction of these breaks may sometimes provide problems. These days, there's a lot of hope that artificial intelligence (AI) might help orthopaedic X-ray interpreters make better, faster fracture diagnoses. The purpose of this investigation is to use “deep learning” (DL) to assist physicians, particularly those who work in emergency departments, in diagnosing wrist X-ray fractures. To build a reliable and effective system that classifies wrist X-ray abnormalities, this study used a MURA (XR_WRIST) dataset from the Stanford Machine Learning Group website. To obtain higher accuracy, the data was preprocessed using various key steps, initially resizing the images and converting them to greyscale; CLAHE was implemented. To mitigate minor noise, Gaussian blur is implemented, and the "haar" wavelet is employed in the discrete wavelet transform (DWT) at level 1 to further reduce noise by zeroing high-frequency coefficients. The model's robustness is ensured by using a 3-fold cross-validation strategy. For classification purposes, the VGG19_AlexNet_AdaptiveHybrid_CNN model is subsequently implemented. Model performance has been assessed using metrics such as the confusion matrix, “Cohen's kappa”(CK), “F1-score”(f-measure), “sensitivity”(Sn), “specificity”(Sp), “recall”(recl), “accuracy”(acc), “precision”(prec), and ROC-AUC. The comparative results of existing and proposed DL models demonstrate thatproposed VGG19_AlexNet_AdaptiveHybrid_CNN model has the highest accuracy99.81%, precision99.9%, recall99.81% and f1-score99.86%. These outcomes show that a proposed model is highly reliable in wrist X-ray abnormalities detection.