The purpose of Decision Making in Anesthesiology: An Algorithmic Approach is to present the process of anesthetic management during the perioperative period in a decision tree format. This format encourages the reader to think systematically and to follow a logical sequence through preoperative evaluation and preparation, intraoperative management, and postoperative considerations. This book comprised of 25 sections that include principles of anesthesia, preanesthesia assessment, preoperative problems: pulmonary and thoracic disorders, preoperative cardiovascular problems, preoperative neurologic and neuromuscular problems, preoperative endocrine problems, preoperative gastrointestinal problems, preoperative hematologic functions, preoperative renal problems, specialty anesthesia and cardiothoracic and vascular anesthesia, neuroanesthesia, pediatric anesthesia, obstetric and gynecologic anesthesia, anesthesia for general surgery, urologic anesthesia, anesthesia and transplantation, anesthesia for endoscopy and head and neck surgery, ophthalmologic anesthesia, anesthesia for spinal and orthopedic procedures, trauma anesthesia, postoperative management, perioperative emergencies, and administrative issues, which are further divided into 243 chapters. Decision Making in Anesthesiology: An Algorithmic Approach provides an abundant resource for anesthesia care providers (ACPs) to review and refresh their knowledge on a broad range of vital topics, many of which are infrequently encountered clinically and thus more challenging. Large, complicated topics have been condensed to the most essential facts. Thus, each chapter is short but intense—each is packed with information which can be used in real time.