The purpose of Decision Making in Anesthesiology: An Algorithmic Approach, 5th Edition, 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. The goal is to construct decision trees that are easy to follow, demonstrate decision points clearly, and are simple but not simplistic. The comments are keyed to designated decision points for further information, supported by references. This format, employed consistently throughout the prior four editions, continues to be most interesting to reformulate and in some cases reorganize clinical knowledge and experiences in order to construct these algorithms. Key Features This textbook has been fully updated and expanded to provide anesthesiology practitioners and anesthesiologists in training with answers for nearly 250 anesthetic management problems. For each chapter, a step-by-step decision-making algorithm is included along with explanatory text and supplemental tables. All the chapters are thoroughly revised, and the editors have completely reconceptualized the entire edition, deleting many chapters, reorganizing the content into 25 sections, and adding topics to reflect the state-of-the-art in contemporary anesthesiology practice. General principles in anesthesia care are discussed along with detailed examinations of preoperative problems, an in-depth look at anesthesia in surgical specialty areas and postoperative management, perioperative management, and administrative issues. Each chapter is authored by faculty members from leading US medical schools.