A study of platelet aggregation in patients with acute myocardial infarction at presentation and after 48 hrs of initiating standard anti platelet therapy.

AIMS & OBJECTIVES: Platelet aggregation is a key factor behind coronary artery disease. Various complications after an attack of acute coronary syndrome are often related to the platelet hyperactivity in the early hours following the event. There is a growing concern regarding aspirin & clopidogrel resistance, which has put the time-tested therapies under scrutiny. Time has come to address the issue of platelet hyperactivity in the early hours & whether to individualize therapy and drug doses in different patients. MATERIALS & METHODS: We prospectively enrolled 41 patients with a diagnosis of acute myocardial infarction (AMI) between July 2009 and July 2010 admitted to the cardiology ward and ICCU of Medical College, Kolkata, after fulfillment of inclusion & exclusion criteria. The study was reviewed and approved by the Institutional Ethical Committee. Platelet Aggregation (PA) with 10 microM epinephrine, 2 microg/ml collagen and 10 microM ADP was performed with light transmittance aggregometry in all patients according to the standard protocol. Tests were done within 3 hours of sampling with platelet-rich plasma (PRP) by the turbidometric method in a 2-channel aggregometer (Chrono-Log 490 Model, Chrono-Log Corp, Havertown, Pa). Aspirin & clopidogrel resistance were defined as per ACC/AHA guidelines. Platelet aggregation studies were done at presentation (zero hour) and 48 hours after instituting dual antiplatelet therapy in standard doses. RESULTS: Patients with first attack of AMI showed a high mean platelet aggregation at 0 hours of 77.4% +/- 18.8% with ADP, 77.5% +/- 26% with Epinephrine & 73.5% +/- 24.9% with Collagen. With all three agonists, the initial hyperactivity of platelets at 0 hours was significantly higher among diabetics & obese. Though reduced, significant platelet hyperactivity remained at 48 hours after initiating standard antiplatelet therapy; 50.3% +/- 14.3% with ADP, 56.5% +/- 21.6% with epinephrine & 38.4% +/- 22% with collagen. CONCLUSION: In the early hours after AMI there is a fairly high degree of platelet aggregation. Even after 48 hours of standard antiplatelet therapy the platelet aggregation though reduced, still remains significantly high. Since recurrent ischemic episodes frequently occur in this vulnerable period, time has come to assess platelet aggregation status in high risk groups, if not in all patients of acute coronary syndrome during this period so that therapy may be individualized. Further researches are required in this area.

How predictive is the Framingham's risk prediction algorithm in Indian perspective? A retrospective case-control study from Kolkata.

OBJECTIVE: 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.

Effect of chitosan on lipid levels when administered concurrently with atorvastatin--a placebo controlled study.

In 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.

Risk factors for coronary heart disease in Indians: a case-control study from Eastern India.

We 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.

Predictive efficacy of Framingham's risk score in Indian scenario--a retrospective case-control study.

To 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).