Abstract
Cardiac surgery has been quantitative from its onset. As the field progressed, surgeons encountered questions that required going beyond existing and traditional methods, fostering both adoption of analytic methods from non-medical fields (communication, industrial sciences, and physics, for example) and development of new ones. These were underpinned by specific philosophies of science about uncertainty, causes of surgical failure as a result of human error on the one hand and lack of scientific progress on the other, and how to express effectiveness and appropriateness to inform the timing of surgery and its indications. Included were traditional methods such as confidence limits and P-values, but also appreciation of why human error takes limited forms, as studied by human factors and cognitive researchers. The “incremental risk factor concept” reinterpreted variables associated with outcomes, initially in the context of congenital heart disease. New methods were either developed within the discipline or introduced, including those for survival analysis and competing risks that accounted for non-proportional hazards by temporal decomposition and separate risk factors for different time frames of follow-up. More recently, longitudinal methods to examine binary, ordinal, and continuous outcomes were developed. Propensity-score–based methods for comparative effectiveness studies, particularly in light of the limited ability to randomize treatments, enabled identifying complementary rather than competing techniques. However, just as the evolution of surgery has not stopped, neither has the quest for better methods to answer surgeons’ questions. Increasingly, these require advanced algorithmic data analytic methods, such as those developing in the field of genomic informatics.
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Blackstone, E.H. (2015). Introduction: The History of Statistics in Medicine and Surgery. In: Barach, P., Jacobs, J., Lipshultz, S., Laussen, P. (eds) Pediatric and Congenital Cardiac Care. Springer, London. https://doi.org/10.1007/978-1-4471-6587-3_2
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