Searching through the literature to identify potential causes and treatments of postoperative acute kidney injury (AKI) can be mind-boggling, frustrating, and more difficult than Indiana Jones searching for the holy grail. Predictors of postoperative AKI are abundant. Examples include, but are by no means limited to, serum biomarkers, 1,2 urinary biomarkers, 3,4 potentially modifiable clinical factors, 5 and dynamic predictive scores that rely on the time of sampling before or after operation. 6 A notably lacking source of predictors of AKI is an intraoperative marker that may predict early postoperative AKI. Many published reports of risk factors for AKI focus on postoperative variables, which may not provide actionable information to reduce AKI risk. In Mukaida and colleagues' article 7 in this issue of the Journal, their exploration of AKI after cardiac operations provides intraoperative measures that may be early indicators of AKI. Perhaps more importantly, these early measures of AKI may trigger interventions for cardiac surgeons. who have been searching for the holy grail to reduce AKI associated with cardiopulmonary bypass for more than 40 years. 8 They offer a possible predictive measure of AKI that can be obtained during cardiopulmonary bypass (CPB). There are at least 15 different literature reports that provide predictive algorithms for determining AKI after cardiac operations. 9 These literature reports suggest that anywhere between 7 and 15 variables may be multivariate predictors of postoperative AKI. The predictive models for AKI requiring dialysis are the most robust, and most of these predictive models have external validation. Dialysis events after cardiac operations are rare (1%-2%), however, and the delayed occurrence after operation limits the benefit of application of predictive scoring systems. A critical assessment of these prediction models suggests that models with a more sensitive definition of AKI suffer from differing definitions of AKI, small cohorts, lack of intraoperative variables, and the lack of external validation. 9 The take-home message from a literature