Agrawal PK, Mehta KK, Raha A
… +17 more, Agarwal R, Varshney A, Biswas A, Shah KS, Jagadeesha A, Dariya SS, Saboo B, Gokhale PD, Suri S, Chandra KP, Gautam A, Kumar B H, Lamba S, Chawla P, Pursnani N, Mohanty S, Garg R
J Assoc Physicians India
· 2026 Jan · PMID 41818037
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BACKGROUND: Metformin has been the cornerstone of type 2 diabetes mellitus (T2D) pharmacologic management, but gastrointestinal (GI) intolerance limits its use in a significant subset of patients. In India, alternative t...BACKGROUND: Metformin has been the cornerstone of type 2 diabetes mellitus (T2D) pharmacologic management, but gastrointestinal (GI) intolerance limits its use in a significant subset of patients. In India, alternative therapies for metformin-intolerant subjects are needed given the high diabetes burden and early disease onset. Imeglimin, a novel oral antidiabetic agent with a distinct mitochondrial mechanism of action, has shown efficacy and tolerability but lacks large real-world evidence in Indian subjects unable to tolerate metformin. MATERIALS AND METHODS: This 6-month, prospective, multicenter, observational study was conducted across 19 clinical sites in India to evaluate the effectiveness and safety of imeglimin in a real-world setting. The study population comprised adult patients with T2D who were identified as intolerant to metformin. Following enrollment, subjects were initiated on treatment with imeglimin, administered either as monotherapy or as add-on therapy to existing regimens. The primary effectiveness endpoint was the change from baseline in glycated hemoglobin (HbA1c) at 6 months and the assessment of safety and tolerability. RESULTS: Among the 722 analyzed subjects, the mean age was 53.1 years, and the mean baseline HbA1c was 8.5%. Imeglimin therapy produced sustained improvements: Mean HbA1c decreased by 1.26% at 6 months ( < 0.001). Imeglimin performed well as both monotherapy (reduction of 0.77% at 6 months, < 0.001) and combination therapy [with two oral antidiabetic drugs (OADs), a reduction of 1.15%, < 0.001; and with three or more OADs, a reduction of 1.86%, < 0.001]. The treatment was well tolerated, with no serious adverse events reported. Overall, 29.7% of participants experienced side effects, most commonly GI symptoms (15.3%), followed by urinary or genital tract infections (5.0%), nausea or vomiting (5.1%), headache (7.1%), and hypoglycemia (1.1%). CONCLUSION: Imeglimin demonstrates clinically meaningful glycemic efficacy in a real-world setting among metformin-intolerant patients. Its high efficacy, even in complex combination regimens, combined with a favorable safety profile and a low risk of hypoglycemia, establishes imeglimin as a highly valuable and effective alternative for patients who cannot tolerate metformin.
J Assoc Physicians India
· 2025 Dec · PMID 41391094
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A 65-year-old man was admitted with left lower-limb cellulitis and an impending abscess. He was a known case of type 2 diabetes mellitus, with hemoglobin A1c (HbA1c) 7.6%, and was started on intravenous piperacillin-tazo...A 65-year-old man was admitted with left lower-limb cellulitis and an impending abscess. He was a known case of type 2 diabetes mellitus, with hemoglobin A1c (HbA1c) 7.6%, and was started on intravenous piperacillin-tazobactam. Wound debridement was carried out under local anesthesia. At admission, he had stage 1 acute kidney injury as per Kidney Disease: Improving Global Outcomes (KDIGO) criteria, which improved with supportive measures. On the 6th day of therapy, his relatives noticed a black discoloration over his tongue (Fig. 1). Examination revealed a dark coating confined to the dorsal surface of the tongue, with sparing of the tip and lateral borders. There was no associated pain or burning sensation. A diagnosis of black hairy tongue (BHT) was considered, possibly related to piperacillin-tazobactam. The antibiotic was discontinued, and the patient was advised to maintain good oral hygiene and to brush the tongue gently. The discoloration resolved completely within 1 week of these measures.
J Assoc Physicians India
· 2025 Dec · PMID 41391093
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Artificial intelligence (AI) is universally adopted in our day-to-day life, including medical science, and transforming healthcare in various ways, like scientific discovery, collecting and interpreting large data, and g...Artificial intelligence (AI) is universally adopted in our day-to-day life, including medical science, and transforming healthcare in various ways, like scientific discovery, collecting and interpreting large data, and gaining insights that might not have been possible by traditional scientific tools. AI also helps learning by geometric understanding, leveraging knowledge, enhanced accuracy and efficiency in diagnostics, imaging, clinical decisions, predictive analysis, drug discovery, virtual assistance, administrative automation, telemedicine, and precision medicine. However, AI lacks emotional consciousness, moral understanding, spiritual insight, and human psychology. AI is a tool to help us and not a human being. Humanity, sociality, spirituality, and emotions are difficult to define. Human emotions are internal, subjective experiences such as happiness, sadness, anger, fear, love, empathy, and sympathy, deeply rooted in our biological systems, memories, and personal experiences, and AI can simulate these emotions but cannot feel or experience them, while spirituality involves meaning, purpose, and belief in something more than oneself (e.g., God or supreme power). AI has no soul or belief and spiritual practices. However, concerns persist, including biases ingrained in AI algorithms, lack of transparency in decision-making, potential compromises of patient data, privacy, and safety of AI implementation in clinical settings. Artificial intelligence has enormous potential in choosing complex regimes, faster calculations, streamlining workflows, and expanding access to healthcare. Nevertheless, AI cannot experience emotions, exercise moral reasoning, or offer genuine spiritual companionship, and successful integration requires AI to function strictly as an assistant to healthcare professionals (HCPs). "AI has vast potential, but it cannot be human, social, emotional, and spiritual."
J Assoc Physicians India
· 2025 Dec · PMID 41391092
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BACKGROUND AND AIM: Abdominal tuberculosis (ATB) poses significant diagnostic challenges due to its varied clinical manifestations and its ability to mimic other diseases. Histopathology is a promising diagnostic tool to...BACKGROUND AND AIM: Abdominal tuberculosis (ATB) poses significant diagnostic challenges due to its varied clinical manifestations and its ability to mimic other diseases. Histopathology is a promising diagnostic tool to diagnose ATB. This narrative review aims to synthesize evidence on the evolving role of histopathology in diagnosing ATB, highlighting its integration with molecular and microbiological diagnostics, and discussing its limitations and emerging technologies. METHODOLOGY: A structured search of databases including PubMed, Scopus, Web of Science, and Google Scholar was performed, focusing on literature published from January 2002. The review includes peer-reviewed original articles on the diagnosis of ATB using histopathology and integrated diagnostic modalities. RESULTS: Histopathology remains crucial for diagnosing ATB, especially in resource-limited settings, due to its ability to visualize granulomatous inflammation and other cellular features. The integration of histopathology with molecular diagnostics like GeneXpert /rifampicin (MTB/RIF) and tuberculosis polymerase chain reaction (TB-PCR) has improved diagnostic accuracy. However, limitations include diagnostic overlap with other conditions and the impact of prior treatment on tissue samples. Emerging technologies such as digital pathology and artificial intelligence (AI)-driven image analysis are poised to enhance diagnostic precision. CONCLUSION: The review underscores the importance of a multimodal diagnostic approach, combining histopathology with other techniques to improve sensitivity and specificity. As ATB continues to be a global health concern, advancements in histopathological techniques and interdisciplinary collaboration are essential for timely and accurate diagnosis.
J Assoc Physicians India
· 2025 Dec · PMID 41391091
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Lyme disease (LD) is a multisystem inflammatory zoonosis affecting the skin, heart, nervous system, and joints, transmitted by ticks and caused by infection with species of the () complex. It is the most common emerging...Lyme disease (LD) is a multisystem inflammatory zoonosis affecting the skin, heart, nervous system, and joints, transmitted by ticks and caused by infection with species of the () complex. It is the most common emerging vector-borne disease in the United States. The Centers for Disease Control and Prevention (CDC) estimated the annual occurrence of 3,29,000 cases of LD in the United States during 2005-2010, and it increased to 4,76,000 during 2010-2018. The incidence of various clinical manifestations of LD differs among countries or regions based on the prevalent genospecies of the complex responsible for infection. Ticks of spp. are the main vectors involved in the transmission of LD, which occurs mainly during the spring season. However, in North America and Europe, there is a rise in temperature due to global warming, leading to the extension of tick habitats toward northern areas. These ticks now stay active for an extended period of the year, increasing the chances of transmission to humans, and it is postulated to be one of the reasons responsible for the rising cases of LD. Early diagnosis and treatment with appropriate antibiotics can resolve the early manifestations of LD and prevent subsequent complications, which are known to occur if not treated appropriately. The disease is most common in rural areas and is difficult to differentiate clinically from other tropical infections such as rickettsial infections. The literature on LD in India is limited; however, LD has been reported from at least 12 states of India. A recently concluded study by the Indian Council of Medical Research (ICMR) has documented the seroprevalence of this disease in eight sites situated in areas of North (Himachal Pradesh and Haryana) and Northeast India (Meghalaya, Assam, Mizoram, and Tripura). LD remains grossly underdiagnosed in India. The lack of awareness among clinicians regarding the prevalence of LD and the limited availability of diagnostic investigations may have contributed toward it. LD should no longer be confined to textbooks, but it should find a place in the list of differential diagnoses in clinical practice. This review is an endeavor to sensitize physicians regarding LD and its impending rise worldwide due to global warming.
Taneja D, Fotedar S, Dash P
… +4 more, Pandey A, Taneja S, Desai AA, Goyal V
J Assoc Physicians India
· 2025 Dec · PMID 41391090
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Accurate prediction of patient outcomes in intensive care units (ICUs) is crucial for enhancing clinical decision-making, patient care, and resource allocation. Traditional scoring systems like Acute Physiology and Chron...Accurate prediction of patient outcomes in intensive care units (ICUs) is crucial for enhancing clinical decision-making, patient care, and resource allocation. Traditional scoring systems like Acute Physiology and Chronic Health Evaluation (APACHE), Simplified Acute Physiology Score (SAPS), and Sequential Organ Failure Assessment (SOFA), while valuable, fall short of fully capturing the complexities of critically ill patients. Advances in machine learning (ML) enable the analysis of high-dimensional data, including electronic health records (EHRs), physiological parameters, and genomic information, providing a more comprehensive approach to outcome prediction. This review aims to assess the impact of ML techniques, including deep learning (DL), ensemble machine learning (EML), and reinforcement learning (RL), in improving ICU outcome predictions, particularly in identifying high-risk patients and enabling proactive interventions. Machine learning models have shown superiority over traditional systems, enabling more accurate identification of critical patients. However, implementing ML in ICU settings comes with challenges, including data quality, model interpretability, ethical concerns, and workflow integration. Collaborative efforts between clinicians, data scientists, and multidisciplinary teams, supported by shared databases like Medical Information Mart for Intensive Care (MIMIC), are essential for developing generalizable ML models that work across diverse healthcare environments. Future research should focus on improving real-time prediction using wearable technology and personalized risk assessments to further individualize ICU care. Ethical considerations, particularly data privacy and model transparency, must be addressed as ML becomes more integrated into critical care.
J Assoc Physicians India
· 2025 Dec · PMID 41391089
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Cardiac rehabilitation (CR) is a critical component of secondary prevention in cardiovascular disease (CVD) management. In India, where CVD prevalence is rising rapidly, CR remains severely underutilized due to multiple...Cardiac rehabilitation (CR) is a critical component of secondary prevention in cardiovascular disease (CVD) management. In India, where CVD prevalence is rising rapidly, CR remains severely underutilized due to multiple systemic barriers. These include limited infrastructure, insufficient funding, low awareness, and inequitable access across urban and rural regions. This review assesses the current CR landscape in India, contrasts it with global benchmarks, and highlights key implementation gaps. It further explores scalable solutions such as telerehabilitation, community-based programs, and integrated multidisciplinary models. The paper emphasizes the need for robust policy frameworks, sustainable funding, infrastructure strengthening, and comprehensive workforce development. Achieving universal access to CR in India demands a multisectoral, collaborative approach involving government agencies, healthcare providers, academic institutions, nongovernmental organizations (NGOs), and private stakeholders. Enhancing CR services is not only a clinical necessity but also a national public health priority.
Saboo B, Samajdar SS, Shukla R
… +6 more, Sarda A, Ramchandani GD, Hasnani D, Mohit M, Saiyed M, Joshi S
J Assoc Physicians India
· 2025 Dec · PMID 41391088
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Three decades after the landmark Diabetes Control and Complications Trial (DCCT), type 1 diabetes (T1D) care in India continues to face systemic, socioeconomic, and technological challenges. Despite a relatively lower in...Three decades after the landmark Diabetes Control and Complications Trial (DCCT), type 1 diabetes (T1D) care in India continues to face systemic, socioeconomic, and technological challenges. Despite a relatively lower incidence compared to high-income countries, India bears a disproportionate burden of T1D-related morbidity and premature mortality due to late diagnoses, fragmented care, limited access to insulin, and underutilization of glucose-monitoring technologies. This editorial explores the current landscape of T1D management in India through the lens of the T1D Index, highlighting critical disparities in care quality, life expectancy, and health-adjusted life years lost. We reflect on the need for a national T1D registry, improved access to advanced therapies such as continuous glucose monitoring (CGM) and automated insulin delivery (AID) systems, and the establishment of multidisciplinary pediatric diabetes centers. The manuscript emphasizes systemic reforms, including public-private partnerships, indigenous manufacturing of diabetes technologies, and expanded education and psychosocial support frameworks. By integrating global best practices with localized solutions, India can bridge the care gap and redefine T1D outcomes for future generations.