The Reconstructive Matrix: A New Paradigm in Reconstructive Plastic Surgery
Raj M. Vyas, M.D.1, Paolo Erba, M.D.2, Rei Ogawa2, Dennis P. Orgill, M.D., Ph.D2.
1Harvard University Plastic Surgery Integrated Program, Boston, MA, USA, 2Brigham and Women's Hospital, Boston, MA, USA.
BACKGROUND: Since the "Edwin Smith Papyrus," treatment paradigms have facilitated decision-making in reconstructive surgery. Mathes and Nahai's "reconstructive ladder" underscores utilizing the simplest strategy to obtain successful wound closure while Gottlieb and Krieger's "reconstructive elevator" instead emphasizes form and function. Nevertheless, today's countless reconstructive options are not well-incorporated by existing models. We propose the concept of the reconstructive matrix (RM) to provide plastic surgeons a new model that better accounts for today's evolving technological, medical, and social environments.
METHODS: Although the complexity of matrices seems limitless, their logical structure permits them to be solved by simple algebraic calculations. The RM (Figure) is a cubic form with three axes representing "technological sophistication (x)," "patient-surgical risk (y)," and "surgical complexity (z)." In this virtual three-dimensional space exist infinite points which, through dynamic interactions between the axes of the RM, represent an ever-expanding array of existing and novel solutions to reconstructive surgery. Surgeons must assess the many potential strategies to choose the "optimal" reconstruction as determined by available resources and social influences within their reconstructive environment. This delicate trade-off is represented by a three-dimensional hyperbola within the RM, described by the equation x*y*z = optimal outcome (Figure). The surface of the hyperbola represents the infinite combinations of x, y, and z that lead to an optimal outcome. An optimal outcome is one that maximizes patient benefit (e.g., form and functional recovery) while minimizing patient morbidity (e.g., complications and donor site defect). The optimal outcomes hyperbolic curve shifts with each unique reconstructive environment as access to technology, surgical training, and patient populations vary.
RESULTS: Here we objectively define each axis of the RM and provide case studies in common reconstructive challenges (open tibia-fibula defect reconstruction, burn reconstruction, and breast reconstruction) to illustrate scenarios in which the three-dimensional hyperbola within the RM can be simplified into two dimensions by holding constant one axis of the matrix. These simplified models illustrate how trade-offs must be navigated among the various axes of the RM as surgeons and patients work together to decide when "less is more" versus "more is more" in choosing technology and surgery to aid reconstruction for a patient with a particular surgical risk.
DISCUSSION: In reconstructive surgery, "optimal" strategies maximize form and function, minimize morbidity, and obtain desired results in the least resource-intense manner. The three-dimensional hyperbolic representation of the RM demonstrates how multiple optimal solutions exist for a given reconstructive challenge and provides a framework for discussion among surgeons, patients, and policy makers about trade-offs when specific technologies and reconstructive procedures are utilized. The RM also serves as a tool to retrospectively and prospectively evaluate outcomes by studying simplified two-dimensional models and expanding findings into the three dimensions of the RM to help clarify optimal solutions for specific challenges in an evidence-based, best-practice manner. The surface shifts as practices evolve, economic conditions change, and new technologies arise.
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