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Management of Diabetic Ketoacidosis in Hospitalized Patients
The management of diabetic ketoacidosis (DKA) in hospitalized patients is a time-sensitive process that aims to correct dehydration and electrolyte imbalances, reverse the ketoacidosis, and identify and treat the underlying cause.Fluid resuscitation is the cornerstone of treatment, typically done with normal saline (0.9% sodium chloride) at a rate of 1-2 liters per hour. Once the patient is clinically stable, fluids can be switched to half-normal saline (0.45% sodium chloride) or dextrose 5% in water.Electrolyte replacement is also essential, with the most important electrolytes to replace being sodium, potassium, and phosphate. Sodium is replaced with normal saline or half-normal saline, potassium with potassium chloride, and phosphate with potassium phosphate or sodium phosphate.Insulin therapy is used to reverse the ketoacidosis, typically initiated with a bolus dose of regular insulin, followed by a continuous infusion of regular insulin. The dose of insulin is adjusted based on the patient's blood glucose levels.
About the Speaker
Dr. Yogesh Rathod
Director & Consultant Critical Care Physician Aadhar Superspeciality Pvt. Ltd and Aadhar Critical Care
Dr. Yogesh Bhimrao Rathod is a consultant critical care physician with over 10 years of experience. He is currently the director and chairman of Aadhar Superspeciality Pvt. Ltd. and Aadhar Critical Care, both located in Solapur, Maharashtra, India.Dr. Rathod has a wealth of experience in all aspects of critical care, including critical care nephrology, cardiology, neurology, and gastroenterology. He is also proficient in anesthesiology, anesthesia procedures, pain management, interventionist intensive care, internal medicine, bronchoscopy, and thoracoscopy
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Technology Integration with Healthcare
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Prehospital Emergency Medicine
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Approach to Coronary Artery Diseases
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Hemodialysis: Overview
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Tailoring Treatment: AI as a Partner in Care
AI plays an important role in dose optimization and adverse medication event prediction, providing major improvements to patient safety and treatment outcomes. Healthcare providers can use AI algorithms to adjust prescription dosages for specific patients and forecast potential adverse drug events, lowering risks and enhancing patient care.