Chapter 12: Treatment Algorithms for Medical Emergencies

Authors

Synopsis

Author

Mrs. Sunitha Panthagada,

Associate Professor, Department of Pharmaceutical Analysis, Koringa College of Pharmacy, Korangi, Tallarevu, Andhra Pradesh, India

Abstract

The management of medical emergencies is dictated by time-sensitive algorithms designed to rapidly stabilize physiology and reverse life-threatening pathology. The Acute Coronary Syndrome (ACS) algorithm bifurcates based on the initial EKG; STEMI requires an immediate reperfusion algorithm, prioritizing primary PCI, while NSTEMI management is guided by risk stratification. The acute stroke algorithm is similarly time-dependent, centered on an immediate non-contrast CT scan to differentiate ischemic from hemorrhagic stroke. Ischemic stroke management is an algorithm of reperfusion, using IV thrombolysis (alteplase) within a 4.5-hour window and mechanical thrombectomy for large vessel occlusion up to 24 hours. The sepsis algorithm is a bundled protocol ("Hour-1 Bundle") mandating lactate measurement, blood cultures, rapid broad-spectrum antibiotic administration, 30 ml/kg crystalloid resuscitation for hypotension, and vasopressors to maintain mean arterial pressure. The anaphylaxis algorithm is linear and prioritized: immediate intramuscular epinephrine is the first-line and life-saving intervention, followed by adjunctive treatments like antihistamines and corticosteroids. The DKA/HHS algorithm is a multi-pronged metabolic resuscitation, balancing three components: aggressive intravenous fluid repletion, continuous insulin infusion (after confirming potassium levels), and vigilant electrolyte (especially potassium) monitoring and replacement.

Keywords: Sepsis, Stroke, Acute Coronary Syndrome, Anaphylaxis, Diabetic Ketoacidosis, Emergency Medicine

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Forthcoming

27 October 2025

How to Cite

Chapter 12: Treatment Algorithms for Medical Emergencies. (2025). In Handbook of Treatment Algorithms for Medical and Pharmacy Students (pp. 391-431). ThinkPlus Pharma Publications. https://doi.org/10.69613/7zsx9t45