Browsing by Author "Guha, Sharmila"
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Item Effect of chitosan on lipid levels when administered concurrently with atorvastatin--a placebo controlled study.(2005-08-21) Guha, S; Pal, S K; Chatterjee, N; Sarkar, G; Pal, S; Guha, Sharmila; Basu, A K; Banerjee, RIn a placebo controlled trialthe lipid lowering effects of chitosan, a unique dietary fibre, was assessed when given along with atorvastatin 10 mg in patients with chronic coronary heart disease. Altogether 100 patients were studied. They were randomly allocated in two groups of 50 patients each. Patients of group A received atorvastatin 10 mg before dinner plus 2 g/day chitosan in two divided doses. The groupB patients received atorvastatin 10 mg plus placebo. Patients were followed up for a period of 6 weeks. There was significant reduction in mean body weight in group A patients (3.14% versus 1,29% of body weight, p<0.05). There was also a significant rise in HDL cholesterol value (3.8% versus 1.07%, p=0.02) in group A patients. However, there was no significant reduction in the mean values of total cholesterol, LDL cholesterol and triglyceride in the two groups, although group A patients showed marginally lower values.Item How predictive is the Framingham's risk prediction algorithm in Indian perspective? A retrospective case-control study from Kolkata.(2008-07-27) Guha, Santanu; Pal, Subrata Kr; Chatterjee, N; Guha, Sharmila; Ghosh, Arnab; Deb, P KOBJECTIVE: In this retrospective case-control study, an attempt was made to assess the predictive efficacy of Framingham's risk prediction algorithm in Indian perspective. METHODS: A total of 350 patients and 293 age- and sex-matched controls were considered in the study. Those patients, who were presenting for the first time with acute coronary syndrome (ACS) and who did not have any prior manifestation of coronary heart disease (CHD) formed the patient group. The risk prediction algorithm was applied to obtain the risk score and the corresponding 10-year risk in each patient and control. They were divided into two groups: diabetic and nondiabetic. Depending on the 10-year risk, they were further grouped into high risk (10-year risk > 20%), moderately high risk (10-year risk between 10% to 20%), and low risk (10-year risk < 10%). The results were compared and statistically analyzed. RESULTS: In the diabetic patients with ACS, 14.29% qualified as high risk, 32.79% as moderately high risk, and 52.94% as low risk. The corresponding figures for diabetic subjects without ACS were 3.26%, 54.35%, and 42.39%, respectively. In nondiabetic patients with ACS, 19.91% were in the high-risk group, 38.96% in moderately high risk, and 41.13% in the low-risk group; while among the controls, the corresponding figures were 9.95%, 21.89%, and 68.16%, respectively. In nondiabetic subjects, the mean risk was significantly higher for patients compared to controls (14.13 vs. 8.61, p < 0.01). However, in diabetic subjects, there was no significant difference in the mean projected risk between those with ACS and those without ACS (11.37 vs. 10.41, p = NS). CONCLUSION: In the Indian perspective, Framingham's risk prediction protocol has a fair amount of predictive efficacy since the difference of mean risk score between the patients and controls was statistically significant. However, it fails to identify a large proportion of high-risk nondiabetic patients. Hence, a better protocol for the Indian perspective is badly needed.Item Predictive efficacy of Framingham's risk score in Indian scenario--a retrospective case-control study.(2004-10-13) Guha, S; Basu, A K; Pal, S K; Chatterjee, N; Guha, Sharmila; Deb, P KTo assess the predictive ability of Framingham's risk score in primary prevention in our population, 252 cases and 212 age and sex matched controls were taken up for study. Those patients, who were presenting for the first time with acute coronarysyndrome (ACS) and who did not have any prior manifestations of coronary artery disease (CAD) and whose medical records were available formed the patient group. Framingham's risk score was calculated and the corresponding 10 years risk was assessed in each of them. The patients and controls were divided into two groups--diabetic and non-diabetic. Depending on the 10 years risk, they were further grouped into high risk (10 years risk > 20%), moderately high risk (10 years risk 10 to 20%) and low risk (10 years risk less than 10%). Results were compared and statistically analysed. In the diabetic patients with ACS 14% would have qualified as high risk, 33% as moderately high risk and 53% as low risk whereas in diabetic patients without any manifestation of CAD the distribution was 4% in the high risk, 54% in the moderately high risk and 42% in the low risk. In the non-diabetic subjects, amongst the patients of ACS, 20% would have been in high risk, 39% in moderately high risk and 41% in the low risk. The corresponding figures in the non-diabetic control subjects were 10% in high risk, 22% in the moderately high risk and 68% in the low risk. In the non-diabetic subjects, the mean risk was significantly more in patients than in controls (14.15% versus 8.61%, p <0.01). However, in the diabetic patients there was no significant difference in the mean projected risk between patients with ACS and patients without any manifestation of CAD (11.37% versus 10.41%, p>0.05).Item Risk factors for coronary heart disease in Indians: a case-control study from Eastern India.(2005-11-09) Guha, Santanu; Ghosh, Arnab; Chatterjee, Niloy; Pal, Subrata; Guha, Sharmila; Chatterjee, Sourangshu; Deb, Pradip Kumar; Dawn, BuddhadebWe conducted a hospital-based case-control investigation (150 cases and 176 controls) to examine the putative role of conventional risk factors in subjects with and without coronary heart disease from Eastern India. Multivariate binary logistic regression revealed the following as significant risk factors for coronary heart disease: male sex (OR = 4.6, p = 0.001), elevated total cholesterol/high-density lipoprotein ratio (OR = 4.0, p = 0.001), systolic blood pressure (OR = 3.0, p = 0.004), diastolic blood pressure (OR = 3.6, p = 0.002), fasting plasma glucose (OR = 3.0, p = 0.05), post-pondrial plasma glucose (OR = 3.2, p = 0.005), Impaired fasting glucose (OR = 3.7, p = 0.002), elevated triglyceride (OR = 3.1, p = 0.018), increased total cholesterol (OR = 3.0, p = 0.029), low-density lipoprotein (OR = 3.1, p = 0.001), low-density lipoprotein/high-density lipoprotein ratio (OR = 3.4, p = 0.004), central obesity (OR = 3.0, p = 0.006), smoking (OR = 3.7, p = 0.001) and urban residence (OR = 3.1, p = 0.003). In this study, the discriminant analysis showed that 77.2% of all entry for cases and 72.6% of all entry for controls were correctly classified using conventional risk factors and warrant early intervention for conventional risk factors.