Indian Journal of Medical Research最新文献

{"title":"Role of dietary patterns and inter-meal intervals in hypopharyngeal cancer: A case-control study from Assam, India.","authors":"Rajashree Dey, Lipi B Mahanta, Tashnin Rahman, Manigreeva Krishnatreya","doi":"10.25259/IJMR_2866_2025","DOIUrl":"10.25259/IJMR_2866_2025","url":null,"abstract":"<p><p>Background and objectives Despite a high incidence of hypopharyngeal cancer in northeast India, the role of dietary patterns and meal timing remains poorly understood. This study examined the association between inter-meal intervals, dietary patterns, and the risk of hypopharyngeal cancer in northeastern India. Methods A hospital-based case-control study was conducted at a tertiary cancer centre in northeastern India, enrolling 300 histologically confirmed cases with hypopharyngeal cancer and 300 frequency-matched controls between May 2023 and August 2024. Dietary intake and inter-meal intervals were assessed using a semi-quantitative food frequency questionnaire. Multivariable logistic regression calculated odds ratios and 95% confidence intervals, adjusting for demographics, socioeconomic status, alcohol consumption, smoking, and tobacco use, including areca nut consumption. Results Prolonged inter-meal intervals (≥5 h) conferred a nearly three-fold increased risk of hypopharyngeal cancer compared to intervals <4 h [adjusted odds ratio (OR) 2.69, 95% confidence interval (CI): 1.56-4.69]. Strong protective effects emerged for citrus fruits (highest tertile OR 0.13, 95% CI: 0.05-0.32) and leafy green vegetables (highest tertile OR 0.21, 95% CI: 0.09-0.49). Coffee consumption was inversely associated with the risk of hypopharyngeal cancer (OR 0.54, 95% CI: 0.30-0.94), while higher milk intake increased the risk of hypopharyngeal cancer (OR 2.06, 95% CI: 1.22-3.52). Interpretation and conclusions We provide epidemiological evidence linking prolonged inter-meal intervals to the risk of hypopharyngeal carcinoma in an Indian population. Meal timing patterns may be as important as dietary composition for cancer prevention, with implications for public health interventions in high-risk populations.</p>","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 3","pages":"387-398"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13126524/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147769769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extensively drug-resistant gram-negative sepsis in a neonatal intensive care unit from western India: A retrospective cohort study.","authors":"Bharti Yadav, Neeraj Gupta, Rohit Sasidharan, Vibhor Tak, Anuradha Sharma, Vijaya Lakshmi Nag, Arun K Singh","doi":"10.25259/IJMR_2625_2025","DOIUrl":"10.25259/IJMR_2625_2025","url":null,"abstract":"<p><p>Background and objectives Extensively drug-resistant (XDR) Gram-negative bacterial sepsis is an emerging threat in neonatal intensive care units (NICU). We aimed to determine the epidemiology, pathogen profile, and outcome of neonates with XDR Gram-negative sepsis. Methods This retrospective cohort study was conducted in a newly established NICU in Western India. Data of all neonates admitted between July 2016 and June 2021 were analysed. Standard CDC definitions were used to classify antimicrobial resistance. Results Among 1230 neonates, 31.4% (n=387) had clinically suspected sepsis and 11.5% (n=141) had culture-positive sepsis, accounting for 194 sepsis episodes. Gram-negative sepsis occurred in 117 neonates, of whom 38.4% (45/117) had XDR Gram-negative sepsis. One-third of these isolates were XDR, predominantly Klebsiella (n=21,44%), Acinetobacter (n=18,37%), and Escherichia species (n=6, 13%). Nearly 60% (28/48) of XDR Gram-negative isolates were obtained from outborn neonates, and 60% (n=17) were isolated within 48 h of admission. Mortality was significantly higher in neonates with XDR sepsis (21/45, 46.7%) compared with multidrug-resistant (13/41, 31.7%) and drug-sensitive Gram-negative sepsis (4/31, 12.9%) (P=0.009). Interpretation and conclusions The high burden of extensively drug-resistant Gram-negative sepsis and its association with increased mortality underscore the urgent need for strengthened antimicrobial stewardship and surveillance in neonatal intensive care units.</p>","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 3","pages":"379-386"},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13126536/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147770447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying research priorities for gestational weight gain in India: A national exercise.","authors":"Subhanwita Manna, Sudipto Pallab Roy, Tanica Lyngdoh, Ranadip Chowdhury, Shweta Khandelwal, Ramachandran Thiruvengadam, Yashdeep Gupta, Manisha Nair, K Aparna Sharma, A G Radhika, Aparna Mukherjee, Bharati Kulkarni, Nomita Chandhiok, Shinjini Bhatnagar, C S Yajnik, Reema Mukherjee","doi":"10.25259/IJMR_2976_2025","DOIUrl":"10.25259/IJMR_2976_2025","url":null,"abstract":"<p><p>Background and objectives Gestational weight gain is an important indicator of maternal and neonatal health, yet research on this topic in the Indian context remains limited. We conducted a research-setting exercise to identify priority research questions related to gestational weight gain in the Indian context, aiming to guide researchers and policymakers. Methods We used a hybrid approach combining Child Health and Nutrition research Initiative (CHNRI) and a modified James Lind Alliance- Priority Setting Partnership (JLA-PSP). The four CHNRI steps produced an interim priority list, which was refined through the modified JLA-PSP to finalise the priorities Result Sixty researchers participated in the online survey, yielding 54 questions (response rate:30%). These were consolidated into 12 questions across three domains- (a) development of standards and guidelines, (b) Epidemiology and determinants and (c) Evaluation of interventions and strategies for gestational weight gain. We calculated research priority scores, and average expert agreement. The expert group determined four priority questions, emphasising gestational weight gain cut-offs related to short- and long-term feto-maternal outcomes, determinants of gestational weight gain, and effective interventions. Interpretation and conclusion These priorities provide a roadmap for researchers and funders for targeted research in the area of gestational weight gain to improve maternal and child health outcomes in India.</p>","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 2","pages":"215-219"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13104739/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147633310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real time public display dashboards: Reframing road traffic accidents in India.","authors":"Sushila Tiwari, Rahul M Jindal, Dileep Mavalankar","doi":"10.25259/IJMR_2525_2025","DOIUrl":"10.25259/IJMR_2525_2025","url":null,"abstract":"<p><p>India's escalating number of road traffic accidents, demands systemic transformation beyond traditional enforcement measures. This viewpoint proposes the establishment of a public, real-time Trauma Dashboard to transform fragmented, delayed reporting into an open, evidence-based system of accountability. The dashboard would integrate cross-verified datasets from police, hospitals, and insurance companies through interoperable digital platforms such as Open Data Kit (OTK), and Talend Open Studio, or similar platform hosted on the Government of India's MeghRaj Cloud. Automated cross-verified data flows would provide dynamic insights into crash patterns, high-risk zones, and temporal trends. Drawing on successful precedents such as the Central Pollution Control Board (CPCB) Air Quality Index and trauma registries - UK Trauma Audit and Research Network (TARN), US National Trauma Data Bank (NTDB) and India's National Organ and Tissue Transplant Organization (NOTTO), this project proposes to facilitate continuous monitoring, policy responsiveness, and public awareness.</p>","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 2","pages":"203-206"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13104748/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147633396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of diabetes mellitus in cancer.","authors":"Hadrian Noel Alexander F, Sandeep Muzumder, Silpa Johnson, Nirmala Srikantia, Avinash H Udayashankara, R Jayalekshmi","doi":"10.25259/IJMR_1911_2025","DOIUrl":"10.25259/IJMR_1911_2025","url":null,"abstract":"<p><p>Diabetes mellitus and cancer are growing global health concerns with a rising prevalence and substantial associated mortality. The study aims to find impact of diabetes mellitus in cancer. A narrative review was conducted by analysing evidence from various sources, including meta-analyses, systematic reviews, retrospective studies, database analyses, and cohort studies. The review explored the complex interplay between Diabetes Mellitus and cancer, like cancer incidence, oncology outcome i.e., acute and late toxicities, treatment compliance, overall survival (OS), and quality of life (QoL). Diabetes mellitus increases the risk of developing cancer by 10%. Diabetic patients had higher infection rates [2.6%-52%, odds ratio (OR) 1.38-1.57], increased haematologic toxicity (13%-65.7%, P=0.004), and greater hospital admissions (17.2%-74.5%, OR 2.1, P< 0.001). They received significantly lower cisplatin doses (18%-33% reduction), experienced more surgical delays [adjusted OR 1.16, 95% confidence interval (CI) 1.05-1.27], higher risk of flap failure (RR=1.83, 95% CI 1.18-2.85, P=0.007) and were less likely to undergo breast reconstruction (adjusted OR 0.48-0.54, 95% CI 0.24-1.00). Diabetes mellitus decreases local control by 10-20%, increases mortality by 27-98%, and decreases OS by 18-50% across various cancers. It increases late toxicity and negatively impacts QOL with a 1.3-2.7 times higher risk of grade ≥2 genitourinary and gastrointestinal toxicity in prostate cancer, a twofold increase in grade ≥3 radiation pneumonitis in lung cancer, and a 50% higher incidence of severe peripheral neuropathy in breast cancer, leading to delayed recovery and long-term morbidity. In patients receiving cancer directed therapy, diabetes mellitus increases acute and late toxicities, decreased local control and overall survival, and have poor quality of life.</p>","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 2","pages":"221-230"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13104742/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147633315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence (AI)-driven ensemble model for comprehensive chest X-ray abnormality detection and deployment.","authors":"Agraj Abhishek, Manjeet Singh Chalga, Reetika Malik Yadav, Kshitij Agarwal, Vikram Vohra, Atul Tayade, Amber Kumar, Mandira Varma-Basil, Parul Mrigpuri, Hirva Manek, Padma Vikram Badhe, Sarika Gupta, Shuchi Bhatt, Anjan Das, Dhruvendra Pandey, C Ponnuraja, Sanghamitra Pati, Jyotirmayee Turuk, Pratibha Narang, Amita Athavale, Ira Shah, S S Mohanty, Arun George, Rashmi Rodrigues, Sushant Satish Mane, Anant Mohan, C R Chaudhary, Manoranjan Pattnaik, Radha Munje, Bhavna Dhingra, Anurag Singh, Rajesh Kumar Meena, Kirti Chaturvedy, Dhruva Chaudhary, Pavan Kumar Singh, Jeetendra Kumar Patra, Abhishek Sharma, Manika Sharma, Manjula Singh","doi":"10.25259/IJMR_1854_2025","DOIUrl":"10.25259/IJMR_1854_2025","url":null,"abstract":"<p><p>Background and objectives Chest X-rays (CXR) are widely used for screening of thoracic abnormalities, particularly for tuberculosis (TB) in public health settings. However, the lack of trained radiologists in peripheral areas limits timely interpretation. This study presents the development and validation of DeepCXR v1.1, an artificial intelligence (AI)-powered tool designed to identify radiological chest abnormalities without relying on metadata or clinical inputs, making it ideal for large-scale screening programmes. Methods In present multicentric study, AI tool was trained on over 282,000 annotated data points from 54,000 CXR images (36,500 abnormal and 17,500 normal) collected from children and adults from 18 centres across 11 States in India. The tool employs a multi-model ensemble architecture including lung segmentation and lesion-specific models to classify images as normal or abnormal. The tool was validated on multiple datasets, and the final independent validation was done on 13927 CXR images collected prospectively from patients coming to the outpatient clinics of the departments of Medicine and Chest of participating centres. Results The tool demonstrated strong generalisability across training and validation datasets, achieving sensitivity of 92.2% [95% confidence interval (CI) 91.6, 92.7] and specificity of 77.4% (95% CI 76.1, 78.6) in a blind prospective validation. Its performance was independently validated by expert committees and health technology assessment panels. Advanced post-processing modules were integrated to enhance detection accuracy, particularly for complex anatomical regions such as the heart and diaphragm. Interpretation and conclusions DeepCXR v1.1, an indigenously developed AI tool for detecting abnormalities in chest X-rays offers a scalable, interpretable, and robust solution for augmenting radiological screening and improving early disease detection. The tool's ability to function offline on basic hardware further supports its use in resource-limited settings.</p>","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 2","pages":"174-181"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13104747/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147633386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methodological considerations in keratinophilic fungal infections study.","authors":"Hanan Nur","doi":"10.25259/IJMR_2925_2025","DOIUrl":"10.25259/IJMR_2925_2025","url":null,"abstract":"","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 2","pages":"261"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13104750/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147633327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretations on time to move beyond P value.","authors":"Ilker Sengul, Demet Sengul","doi":"10.25259/IJMR_3682_2025","DOIUrl":"10.25259/IJMR_3682_2025","url":null,"abstract":"","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 2","pages":"260"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13104746/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147633347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Childhood cancer in India: Progress achieved, persisting gaps, challenges, and the road ahead.","authors":"Swetha Palla, Deepak Bansal","doi":"10.25259/IJMR_531_2026","DOIUrl":"10.25259/IJMR_531_2026","url":null,"abstract":"","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 2","pages":"131-133"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13104738/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147633366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experiences from inborn errors of immunity registry of India: A preliminary report.","authors":"Reetika Malik Yadav, Deepti Suri, Surjit Singh, Vignesh Pandiarajan, C Satheesh, Prajnya Ranganath, Reena Gulati, Ratna Dua Puri, Lavina Temkar, Persis Khalkho, Almas, Liza Rajasekhar, Revathy Raj, Amlin Shukla, Amit Rawat, Manisha Madkaikar","doi":"10.25259/IJMR_1850_2025","DOIUrl":"10.25259/IJMR_1850_2025","url":null,"abstract":"<p><p>Background and objectives Global estimates identify about 7,000 rare diseases affecting 6-8% of the population, with 80% being genetic. India lacks comprehensive data on their prevalence, distribution, and natural history. Inborn errors of immunity (IEI) registry was developed by Indian Council of Medical Research (ICMR) as part of a comprehensive multi-centric 'National Registry for Rare and Other Inherited Disorders', from centres which expressed interest in contributing to this national database in 2019. This study aims to establish an Indian rare-disease registry to assess disease burden, collect clinical and demographic data, understand natural history, support research on underlying mechanisms, create cohorts for evaluating therapies and orphan products, and strengthen connections among patients, families, and clinicians to improve comprehensive care across the country effectively. Methods After ethics approval from the participating centres, data were collected in a structured format developed jointly by ICMR- National Institute of Immunohaematology, Mumbai and Postgraduate Institute of Medical Education and Research, Chandigarh, identified as nodal centres for inborn errors of immunity (IEI) by ICMR. Cases with molecular confirmation of diagnosis or those satisfying the European Society for Immunodeficiencies (ESID) registry working definition in absence of molecular confirmation were included. The Data were compiled in excel format and analysed using Epi Info v7.2.5.0. Results Data for 676 patients enrolled between January 2019- October 2024 from six participating centres including ICMR-NIIH Mumbai, PGI Chandigarh, Apollo Chennai, JIPMER Pondicherry, Nizams Institute Hyderabad, and Sir Gangaram Hospital Delhi was analysed. Immunodeficiencies affecting cellular and humoral immunity (CID) and CID with associated or syndromic features (n=187,27.6%), predominantly antibody deficiency (n=146,21.6%), congenital defects of phagocyte number or function (n=117,17.3%) were the most frequent IEIs. The median age of presentation was 16 (IQR 4,63) months and diagnostic delay of 16 (IQR 3,55) months. The presenting clinical manifestations comprised of recurrent infections (n=459,67.9%), autoimmunity or auto-inflammation (n=292,43.2%), adverse effect following immunisation (n=38,5.6%), and malignancy (n=5,0.73%). 103/146 (70%) patients with antibody deficiency received IVIG and 90 (13.3%) IEI patients underwent hematopoietic stem cell transplant. On follow up, 118 (17.4%) patients died due to infections by 2024. Interpretation and conclusions The IEI registry developed by ICMR as an attempt to maintain a patient database gives us insights on the demographic, clinical presentation, diagnostic-delay and treatment outcomes of these disorders.</p>","PeriodicalId":13349,"journal":{"name":"Indian Journal of Medical Research","volume":"163 2","pages":"207-214"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13104740/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147633304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}