scholarly journals Risk Factor Profile, Clinical and Vascular Territory Involved in Patients of Stroke Presenting to a Tertiary Care Hospital in India Over 1 Year

2019 ◽  
Vol 2 (2) ◽  
pp. 54-57
Author(s):  
Niket Verma ◽  
Amit Sreen ◽  
Prafull Sharma ◽  
Vivek Guleria
Keyword(s):  
Risk Factor ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Care Hospital ◽  
Vascular Territory ◽  
Risk Factor Profile

scholarly journals Risk factors for ventricular tachycardia in acute ST-elevated myocardial infarction patients of a tertiary care hospital of Peshawar

2021 ◽  
Vol 6 (4) ◽  
pp. 12-15
Author(s):  
Inam Ullah ◽  
Ashfaq Ahmad Shah Bukhari ◽  
Mehwish Durrani ◽  
Zulfania Khan ◽  
Saman Tauqir ◽  
...  
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Risk Factor ◽  
Ventricular Tachycardia ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Anterior Wall ◽  
Care Hospital ◽  
Common Risk Factor ◽  
Common Location

Introduction: Ventricular arrhythmias are the most common cause of death in various ST-Elevated Myocardial Infarction (STEMI) patients and can be prevented if diagnosed and managed in time. Objectives: To document the occurrence of ventricular tachycardia in patients with acute ST-segment elevated myocardial infarction (STEMI) admitted to a tertiary care hospital of Peshawar and to identify associated risk factors. Materials & Methods: A descriptive cross-sectional study consisting of 252 MI patients of 51-60 years of age, were observed for the presence of ventricular tachycardia at Lady Reading Hospital, Peshawar from September 2017 to January 2018. Results: Hypertension was found to be the most common risk factor for ventricular tachycardia observed in 180 patients. Diabetes mellitus was the 2nd most common risk factor present in 104 patients while smoking was found in 56 patients. The most common location of ST-Elevation MI was anterior wall myocardial infarction (30.2%) occurring in 76 patients. Conclusion: Ventricular tachycardia occurred in a quarter of the patients presenting with acute ST-elevated myocardial infarction, and was more common in anterior wall MI followed by extensive anterior wall MI.  

scholarly journals Prevalence of gestational diabetes mellitus and its relationship with various risk factors in a tertiary care hospital in West Bengal with special reference to tribal population, India

2019 ◽  
Vol 7 (4) ◽  
pp. 1098
Author(s):  
Narenrda Kumar Sharma ◽  
Subodh Kumar Mahto ◽  
Rahul Sharma ◽  
Ankita Sheoran ◽  
Sumit Kumar Suman ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Risk Factor ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
West Bengal ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Care Hospital ◽  
Tribal Population

Background: Gestational diabetes mellitus (GDM) is the most common medical complication and metabolic disorder of pregnancy. The aim and objective of this study was to determine the prevalence of GDM and its relationship with various risk factors with special reference to tribal population.Methods: The study was done in 200 patients between 24 and 28 weeks of gestation, attending antenatal outdoor in a tertiary care hospital of West Bengal.  These patients were given 75gm oral glucose irrespective of the last meal and their plasma glucose was estimated at 2hours. Patients with plasma glucose values ≥140 mg/dl were labelled as GDM. Patients who were diabetic before pregnancy or whose pre pregnancy body mass index was not known or was in labour or had chronic disease, were not included in the study.Results: Prevalence of GDM was 11% in whole population while it was 14.63% and 10.06% in tribal and non-tribal population respectively.  Prevalence of GDM and its correlation with most of risk factors in previous pregnancies was found to be significant in both non-tribal and tribal population. Family history of diabetes mellitus was the most prevalent risk factor in both non-tribal (9.4%) and tribal population (14.63%). There was no single most common risk factor among GDM patients found as there were multiple risk factors present with same frequency in both tribal and non-tribal population.Conclusions: The prevalence of GDM is 14.63% in the tribal population and 10.06% in non-tribal population which is not statically significant (P<0.407). The relation between the prevalence of GDM and risk factors was found to be significant for most of the risk factors.

scholarly journals Study on Risk Factor Evaluation of Ischaemic Stroke Patients Admitted in a Tertiary Care Hospital: 100 Cases

2020 ◽  
Vol 8 (6) ◽  
pp. 225
Author(s):  
Tazin Afrose Shah ◽  
Farhan Matin ◽  
Anarul Islam ◽  
Mahabubur Rahman ◽  
Mohiduzzaman Tony ◽  
...  
Keyword(s):  
Risk Factor ◽  
Ischaemic Stroke ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Care Hospital ◽  
Stroke Patients ◽  
Factor Evaluation

scholarly journals Evaluating the Accuracy of the Risk Assessment Tools in Predicting CVD Events in Tertiary Care Hospital, Bangalore, India

2021 ◽  
Vol 15 (5) ◽  
pp. 1460-1464
Author(s):  
Elnaz Golabgir ◽  
Raju Koneri
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Risk Score ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Assessment Tools ◽  
Risk Scores ◽  
Care Hospital ◽  
Risk Assessment Tools ◽  
Ascvd Risk

Aim: To evaluate the accuracy of the risk assessment tools in predicting CVD events in tertiary care hospital, Bangalore, India. Methodology: A Prospective observational study conducted in medicine wards of a tertiary-care hospital for eight months. We collected all the details like inpatient number, age, sex, social status, laboratory data, weight, height, Blood Pressure (BP), family history, and therapeutic management. Then introduced the data to FRS and ASCVD risk score calculators and determined the risk for development of CVD in each patient and observed risk score for each risk factor in the study sample. Results: FRS and ASCVD predicted the risk factor for developing CHD; BMI values, tobacco use, alcohol consumption, diabetes, Total Cholesterol. FRS and ASCVD risk scores were used to classify individuals according to Low, Moderate and High-risk factor, the percentage was respectively (70%, 22%, 8%) for ASCVD and (61%,21%, 18%) for FRS. Using FRS and ASCVD, we observed that patients with high BMI values, smokers, alcoholics, diabetics, and patients with high TC, LDL, and TG levels with Low HDL levels were more likely to have a high risk of developing CVDs. Conclusion: The Risk Scores helped in investigating the status of cardiovascular patients and predicting the incidence of CVD events by determining risk factors. This study emphasizes the importance of good planning and predicting of CVDs in advance as a way to prevent the disease or lower its risk in individuals by studying the risk factors and calculating the risk using Framingham Risk Score and AHA/ACC risk score (ASCVD). Keywords: Atherosclerosis Cardiovascular Disease (ASCVD), Risk Factors, cardiovascular disease

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