Sv Madhu
University College of Medical Sciences
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Featured researches published by Sv Madhu.
Indian Journal of Endocrinology and Metabolism | 2017
Nikhil Tandon; Sanjay Kalra; Yatan Pal Singh Balhara; Manash P Baruah; Manoj Chadha; Hemraj B. Chandalia; Km Prasanna Kumar; Sv Madhu; Ambrish Mithal; Rakesh Sahay; Rishi Shukla; Annamalai Sundaram; Ambika Gopalakrishnan Unnikrishnan; Banshi Saboo; Vandita Gupta; Subhankar Chowdhury; Jothydev Kesavadev; Subhash Wangnoo
Health-care professionals in India frequently manage injection or infusion therapies in persons with diabetes (PWD). Patients taking insulin should know the importance of proper needle size, correct injection process, complication avoidance, and all other aspects of injection technique from the first visit onward. To assist health-care practitioners in their clinical practice, Forum for Injection Technique and Therapy Expert Recommendations, India, has updated the practical advice and made it more comprehensive evidence-based best practice information. Adherence to these updated recommendations, learning, and translating them into clinical practice should lead to effective therapies, improved outcomes, and lower costs for PWD.
Indian Journal of Endocrinology and Metabolism | 2013
Sanjay Kalra; Rajeev Chawla; Sv Madhu
The term “Dirty Dozen” was coined at a convention held in Stockholm in 1995 to describe 12 important persistent organic pollutants (POPs), which were thought to be toxic to human (and animal) health. These POPs were characterized by four features: Persistence, bioaccumulation, potential for long‐range environmental impact and toxicity.[1] A later convention ratified this list, adding more to it. However, the term “Dirty Dozen” has struck to the concept of POPs.
Journal of Human Genetics | 2012
Rubina Tabassum; Anubha Mahajan; Om Prakash Dwivedi; Ganesh Chauhan; Charles J. Spurgeon; M.V. Kranthi Kumar; Saurabh Ghosh; Sv Madhu; Sandeep Mathur; Giriraj R. Chandak; Nikhil Tandon; Dwaipayan Bharadwaj
Though multiple studies link chromosomal regions 1q21–q23 and 20q13 with type 2 diabetes, fine mapping of these regions is yet to confirm gene(s) explaining the linkages. These candidate regions remain unexplored in Indians, which is a high-risk population for type 2 diabetes. Hypothesizing regulatory regions to have a more important role in complex disorders, we examined association of 207 common variants in proximal promoter and untranslated regions of genes on 1q21–23 and 20q13 with type 2 diabetes in 2115 North Indians. Further, top signals were replicated in an independent group of 2085 North Indians. Variants-rs11265455-SLAMF1 (odds ratios (OR)=1.32, P=1.1 × 10−3), rs1062827-F11R (OR=1.36, P=1.7 × 10−3) and rs12565932-F11R (OR=1.35, P=1.8 × 10−3) were top signals for association with type 2 diabetes whereas rs1333062-ITLN1 (OR=1.28, P=3.4 × 10−3) showed strongest association in body mass index-stratified analysis. Replication of these four variants confirmed associations of rs11265455-SLAMF1 (OR=1.27, P=9.1 × 10−3) and rs1333062-ITLN1 (OR=1.25, P=1.1 × 10−3) with type 2 diabetes. Meta-analysis further corroborated the association of rs11265455-SLAMF1 (OR random effect=1.29, P random effect=3.9 × 10−5) and rs1333062-ITLN1 (OR random effect=1.19, P random effect=1.8 × 10−4). In conclusion, the study demonstrates that variants of SLAMF1 and ITLN1, both implicated in inflammation, are associated with type 2 diabetes in Indians.
Indian Journal of Endocrinology and Metabolism | 2017
Sv Madhu; Mohammad Aslam; Aj Aiman; Azaz Siddiqui; S Dwivedi
Aim: The present study is carried out to investigate hypogonadism using serum testosterone levels in male Type 2 diabetes mellitus (T2DM) subjects with and without coronary artery disease (CAD). Subjects and Methods: A total of 150 age and body mass index-matched male subjects in the age group of 30–70 years were recruited in three groups; Group A - subjects with normal glucose tolerance, Group B - T2DM subjects without CAD, and Group C - T2DM subjects with CAD (n = 50 each group). Subjects with CAD were diagnosed on the basis of electrocardiogram, treadmill testing, stress echocardiography, or coronary angiography. Total testosterone (TT), free testosterone (FT), bioavailable testosterone, calculated FT and glycemic parameters were measured and compared between all the three study groups. One-way ANOVA followed by post hoc Tukeys test and Pearsons coefficient of correlation tests were used for analysis. Results: Hypogonadism (TT <3 ng/ml) was observed in 40% (20/50) of subjects in Group C and 32% (16/50) of subjects in Group B as compared to only 14% (7/50) of subjects in Group A (Groups A vs. B; P = 0.055, Groups A vs. C; P = 0.006 and Groups B vs. C; P = 0.53). Group C subjects had significantly lower levels of TT (3.55 ± 1.46 ng/ml vs. 4.73 ± 2.17 ng/ml, P = 0.005), calculated FT (0.062 ± 0.0255 pg/ml vs. 0.0951 ± 0.0508 pg/ml, P≤ 0.001), and bioavailable testosterone (1.48 ± 0.65 ng/ml vs. 2.18 ± 1.20 ng/ml, P ≤ 0.001) compared to control Group A subjects. There was no significant difference in any of the testosterone parameters between Groups A and B. Furthermore, an overall positive correlation was found between hypogonadism and CAD (r = 0.177, P = 0.030, n = 150). Conclusion: We observed hypogonadism as indicated by low testosterone levels in a significant proportion of male T2DM subjects with CAD.
Diabetes and Metabolic Syndrome: Clinical Research and Reviews | 2019
Sv Madhu; Azaz Siddiqui; N.G. Desai; Suman Bala Sharma; A.K. Bansal
AIMSnThe study was conducted to ascertain whether chronic stress and sense of coherence are associated with risk of type 2 diabetes mellitus.nnnMETHODSnStress questionnaires - Presumptive Stressful Life Events Scale (PSLES), Perceived Stress Scale (PSS) and Sense of Coherence (SOC) - were administered to 500 Newly Detected Diabetes Mellitus (NDDM) cases and 500 Normal Glucose Tolerance (NGT) controls recruited following 75u202fg OGTT. Assessment of stress was completed before the diagnosis of diabetes was revealed to them.nnnRESULTSnPSLES and PSS scores were significantly higher and SOC score was significantly lower in NDDM subjects compared to those with NGT. PSLES and PSS correlated positively with anthropometric parameters (waist circumference, BMI), glycemic parameters (FPG, 2u202fhPG, A1C) and HOMA-IR and inversely with HOMA-β whereas SOC correlated inversely with glycemic parameters (FPG, 2u202fhPG, A1C) and HOMA-IR and positively with HOMA-β. In stepwise logistic regression analysis, SOC emerged as the strongest independent predictor of diabetes (OR: 0.774) after HOMA-IR (OR: 1.621) and BMI (OR: 1.288). Other significant predictors included PSS (OR:1.153), PSLES-LT (OR: 1.005) and HOMA-β (OR: 0.894).nnnCONCLUSIONnChronic stress and low sense of coherence are associated with a higher risk of type 2 diabetes mellitus.
International Journal of Diabetes in Developing Countries | 2018
B. K. Mishra; M. Velmurugan; J. K. Gambhir; Sv Madhu
We compared postprandial triglyceride (PPTg) responses to fat challenge between risk allele and wild-type variant of two common TCF7L2 gene polymorphisms to ascertain if the risk of T2DM associated with this gene is related to its effects on PPTg metabolism. Postprandial triglyceride levels were evaluated in 71 NGT subjects with at least one first-degree relative with T2DM. Restriction fragment length polymorphism was performed for genotyping of SNP rs7903146 C/T and SNP rs12255372 G/T of TCF7L2 gene, and the PPTg levels were compared in the risk allele and wild-type variant of both these SNPs. Postprandial triglyceride responses were similar in wild and risk allele groups for both the SNPs. There was no significant difference in Tg-AUC (2027.04u2009±u20091313.54 vs 1853.58u2009±u2009712.00, pu2009=u20090.472) and Peak Tg levels (343.95u2009±u2009225.08xa0mg/dl vs 320.60u2009±u2009137.49xa0mg/dl, pu2009=u20090.591) between CC and CT + TT of SNP rs7903146. Also, no significant difference was observed between Tg-AUC (1936.41u2009±u20091120.77 vs 1891.38u2009±u2009812.69, pu2009=u20090.845) and peak Tg levels (324.89u2009±u2009186.99xa0mg/dl vs 330.42u2009±u2009158.64xa0mg/dl, pu2009=u20090.894) between GG and GT + TT of SNP rs12255372. The present study did not find any significant difference in PPTg responses between the risk allele and wild type of rs7903146(C/T) and rs12255372 (G/T) SNPs of TCF7L2 gene.
International Journal of Diabetes in Developing Countries | 2018
Sarita Bajaj; Anuj Maheshwari; Banshi Saboo; B. M. Makkar; C. R. Anand Moses; Ch Vasanth Kumar; J. Jayaprakashsai; Jayant Panda; K. R. Narasimha Setty; Pradyumna Rao; Rajeev Chawla; Rakesh Sahay; Samar Banerjee; Sanjay Agarwal; Sanjay Kalra; S.R. Aravind; Sujoy Ghosh; Sunil Kumar Gupta; Sv Madhu; Vijay Panikar; Vijay Viswanathan
The aim of this erratum is to acknowledge that the original version of this article contained a mistake in the author group. The names of the numerous authors got missed, and instead were added as members of the steering committee.
International Journal of Diabetes in Developing Countries | 2018
Pradyumna Rao; B. M. Makkar; Ajay Kumar; Ashok Kumar Das; A. K. Singh; Ambrish Mithal; Anil Bhansali; Anoop Misra; Anuj Maheshwari; Arvind Gupta; Ashu Rustogi; Banshi Saboo; C. H. Vasanth Kumar; C. R. Anand Moses; Hemant Thacker; Jayant Panda; Jayaprakashsai Jana; Jothydev Kesavdev; K. R. Narasimha Setty; Manoj Chawla; Neeta Deshpande; Nikhil Tandon; Rajeev Chawla; Rajeev Kovil; Rakesh Sahay; Sv Madhu; Samar Banerjee; Sanjay Kumar Agarwal; Sanjay Kalra; Sarita Bajaj
Maintaining a good glycemic control is crucial in the management of diabetes mellitus (DM) as it is associated with the reduction in both macro and microvascular complications of the disease. Self-monitoring of blood glucose (SMBG), which provides the day-to-day blood glucose levels, is a simple and practical tool for maintaining a good glycemic control. Although SMBG is widely practiced in other countries, its use in India is very limited. Even when used, it is not carried out is a structured manner. There seems to be a lack of education about the purpose of SMBG and the correct process and schedule to be followed. This highlights the unmet need for country-specific SMBG recommendations. In order to fulfil this need, a panel of expert endocrinologists/ diabetologists came together under the aegis of Research Society for the Study of Diabetes in India (RSSDI). They reviewed the current literature, combined the evidences with their clinical knowledge and expertise, and developed consensus recommendations for SMBG practice in India. This document provides a comprehensive review of the current literature on SMBG and presents the recommendations made by the expert panel.
International Journal of Diabetes in Developing Countries | 2018
Sv Madhu
Gestational diabetes mellitus (GDM) is a public health priority in our country due to its high prevalence as well as its immense potential for diabetes prevention. The realization that diabetes in pregnancy is a significant contributor to the growing epidemic of type 2 diabetes mellitus (T2DM) has also helped focus our attention on the pregnant woman as a critical target for diabetes prevention strategies. Diabetes in pregnancy has serious consequences for the mother as well as the baby. The HAPO study found increasing incidence of these complications with rising maternal glucose [1]. In the mother, complications include still birth and a greater need for cesarean section and in the babies, it can cause large babies and congenital malformations. These can affect outcome of pregnancy and it is essential that diabetes is detected early and managed appropriately so that these consequences can be prevented. The clinical issues that follow GDM in pregnancy are well appreciated. However, the transformation of GDM as a major public health issue is because it may play a crucial role in the increasing prevalence of diabetes and obesity [2]. In fact, GDM is believed to be a stage in the evolution of type 2 DM [3]. Hyperglycemia in pregnancy has its highest prevalence in South-East Asia, where one in four pregnancies is affected. Asians develop GDM at a lower BMI and type 2 DMoccurs at a much younger age. With urbanization, GDM prevalence is becoming an epidemic [4]. In India, the prevalence of GDM varies from 3.8 to 21% in different parts of the country [5]. Approximately 7% of all pregnancies are complicated by GDM, resulting in more than 200,000 cases annually [6]. Indian women have 11-fold increased risk of developing glucose intolerance during pregnancy compared to Caucasian women [7]. GDM is also a known risk factor for T2DM [8] besides its known adverse impact on pregnancy outcome. Women with GDM have a seven fold higher risk of developing T2DM. This risk increases steeply 5 years after delivery [9, 10]. Women with a history of GDM also have a higher prevalence of metabolic syndrome and increased risk of cardiovascular disease (CVD) [11]. Children of GDM mothers are at a higher risk of developing T2DM later in life [21 vs 4%] compared with children of non GDM mothers [12]. Babies born to mothers with gestational diabetes also have a higher lifetime risk of obesity and developing type 2 diabetes. GDMmay be responsible for 19– 30% of diabetes in some populations [13]. About one third of children born of diabetes pregnancies develop glucose intolerance before the age of 17 years [14]. Direct evidence of the benefits of interventions in the prevention of future of T2DM in the context of GDM also exists. Postpartum lifestyle intervention prevents type 2DM and cardiovascular disease in women with GDM. Intensive lifestyle and metformin are highly effective in delaying or preventing diabetes in women with IGT and a history of GDM [15, 16]. More importantly, the pregnant mother with diabetes is a very effective starting point for a diabetes prevention strategy as she is highly motivated and carries the message to the family effectively. The pregnant diabetic mother provides a critical link for transgenerational transmission of diabetes which sets off a self-perpetuating cycle of rising diabetes in the community. The hyperglycemia associated with GDM results in fetal overnutrition and a higher risk of obesity and diabetes in the offspring through a variety of mechanisms. These include epigenetic changes in the exposed offspring [17].When postnatal overnutrition gets added to this scenario, there is higher childhood and adolescent obesity and early onset adult type 2 diabetes. This in turn increases the prevalence of GDM and sets off a vicious cycle of GDM and T2DM in the community [18]. Epigenetic changes in various genes may increase the lifelong metabolic disease susceptibility and, thus, the likelihood for a new generation of mothers with GDM and/or obesity thus feeding the vicious cycle [17]. Preventive measures against * S. V. Madhu [email protected]
International Journal of Diabetes in Developing Countries | 2018
Sv Madhu
Both diabetes and psychiatric disorders are common, and it is also known that each condition may worsen the other. Since they also frequently coexist, it is important to recognize the adverse impacts that each has on the other in order that both these conditions can be managed effectively and successfully. It is important to understand this two-way link between stress and psychological comorbidity on the one hand and diabetes on the other. Management of diabetes will always be incomplete and difficult without addressing the associated anxiety, depression, and diabetic distress. The prevalence of depression and anxiety in diabetes is much higher than in normal population [1] and has been reported to be in the range of 12 and 28% in some studies. Prevalence of anxiety and depression among patients with type 2 diabetes was found to be 58 and 45% respectively from Pakistan. Another study reported major depression in 11% [2] and clinically important depressive symptoms in 31% of people with diabetes. Depression symptoms mimic diabetes symptoms and may sometimes make diagnosis difficult [3]. The risk factors for depression among diabetic patients include female sex, long duration of diabetes, presence of complications, poor glycemic control, family history of depression, and lower education levels. Depression may also be related to the complexities in management of diabetes particularly type 1 diabetes or may be secondary to diabetes-related distress. It is important that depression and its causative factors are identified early and eliminated in people with diabetes as those can lead to a far more effective control of their glycemia. While the association of depression and diabetes is well recognized and deservedly so, the study from Pakistan and a recent study from India [4] highlight the fact that anxiety disorders may bemore common in diabetic patients. The prevalence rate of generalized anxiety disorder (GAD) is three times higher than that reported in the general population Anxiety was reported in 58% of diabetic patients from Pakistan, while the study fromNewDelhi reported that among diabetic women from India, anxiety (23–40%) appears more prevalent than depression (18%) [4], especially during the first 2 years after diagnosis. Anxiety disorders and hypoglycemic episodes share clinical features such as sweating, anxiety, tremor, tachycardia, and confusion, and they can sometimes cause difficulties in diagnosis [3]. It can also lead to a failure on the part of the patient to perceive the initial warning signs of hypoglycemia or to confuse these with anxiety. Anxiety disorders should receive more attention as a potential source of comorbidity with diabetes, and screening for anxiety among people with diabetes should be carried out regularly. The current issue includes four studies which have reported on the association of various psychosocial factors including anxiety disorders and depression and their determinants in patients with diabetes. The study by Nawaz et al. [5] from Pakistan found a high percentage of type 2 diabetic patients with associated anxiety. While 66.5% of these patients were diagnosed with mild anxiety, about 21.1% were reported suffering frommoderate to severe anxiety based on the Hamilton Anxiety Rating Scale. Poor glycemic control, female gender especially if they were housewives, lower education levels, higher levels of physical activity, and presence of a diabetic patient in the family were associated with anxiety among type 2 diabetic subjects. In another study being published in this issue, Atif et al. [6] from Pakistan also report high levels of depression and mild cognitive impairment among elderly diabetic subjects. Depression is reported as the most important predictor of mild cognitive impairment in these patients, reinforcing the view that it is important to recognize and treat depression in diabetic patients. Emre et al. [7] also report a high prevalence of anxiety and depression in diabetic patients who also had hypertension in their primary care settings which * S. V. Madhu [email protected]
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Post Graduate Institute of Medical Education and Research
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