Publications by authors named "Prashant Kumar Panda"

Background: Coronavirus disease 2019 (COVID-19) pandemic unmasked the huge deficit in healthcare resources worldwide. It highlighted the need for efficient risk stratification in management of cardiovascular emergencies.

Aim: To study the applicability of the old, available and affordable nonconventional biomarkers: albumin and fibrinogen in their ability to predict angiographic severity and clinical outcomes in patients with acute coronary syndrome (ACS).

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Objective: Several studies have demonstrated a shift in the spectrum of infective endocarditis (IE) in the developed world. We aimed to investigate whether demographic and microbiologic characteristics of IE have changed in India.

Design: A retrospective analysis of patients with in north India between 2010 and 2020.

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Rheumatic heart disease is an important cause of mortality and morbidity in developing countries, and is the leading cause of triple valve replacement. Myocardial infarction (MI) in such cases can be due to the coronary embolism from the prosthetic valves or due to atherosclerotic vascular disease. Intravascular imaging helps in delineating the cause.

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Isolated right-sided valvular disease is a much less recognised entity when compared with left-sided valvular heart disease. Almost all the cases of combined pulmonary valve with tricuspid valve involvement are a consequence of underlying carcinoid heart disease. Moreover, severe calcification of tricuspid valve is an extremely unusual finding.

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Article Synopsis
  • Abnormal glucose metabolic status upon admission is a significant predictor of future cardiovascular issues and mortality in acute coronary syndrome (ACS) patients, regardless of known diabetes status.
  • A study of 250 non-diabetic ACS patients revealed that 38% had normal glucose metabolism, 38% had impaired glucose metabolism, and 24% had diabetes at the time of admission, with a notable portion being undiagnosed.
  • The 75-g oral glucose tolerance test (OGTT) proved to be the most effective method for diagnosing diabetes, while the A1C test was most reliable for identifying stress hyperglycemia.
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