A Monitoring System Based on the Multifactorial Dynamic Perfusion Index to Predict and Prevent the Onset of Postoperative Acute Kidney Injury After Cardiac Surgery, Based on a Dynamic Collection of Hemodynamic and Clinical Parameters During Cardiopulmonary Bypass

Plain-language summary

This project is based on a predictive alghorithm (Multifactorial Dynamic Perfusion Index-MDPI) already published and covered by a patent. The MDPI is based on a dynamic collection of 7 different variables during cardiopulmonary bypass (CPB) and provides a probability index for postoperative acute kidney injury. The study design is a multicenter observational prospective trial developed through 3 work packages, addressing (1) external validation of the MDPI in a series of 800 adult cardiac surgery patients collected in 2 Institutions (2) development of a novel MDPI to be applied in infants \< 20 kg undergoing cardiac surgery (200 patients) and (3) verification of of other possible outcomes that may be predicted by the MDPI. Since many of the predictive variables are modifiable by the perfusionist/anesthesiologist during CPB, it is a tool that allows therapeutic manouvres. Ultimately, the MDPI will be incorporated in a dedicated monitor to provide an on-line "flight control" during CPB. Work package 1 will be performed at Units 1 and 2; the parameters composing the MDPI will be collected using the existing CPB monitors that routinely measure the hematocrit, the oxygen delivery, the time of exposure to a pre-defined critical oxygen delivery, the mean arterial pressure, and the CPB duration. Blood lactates and transfusions will be manually inputed. The MDPI will be calculated off-line and tested for association and predictivity (discrimination and calibration) with respect to postoperative AKI defined according to the K-DIGO classification. Workpackage 2 is dedicated to infants, with the purpose of developing an MDPI dedicated to low-weight infants (I-MDPI). This will be develop in Unit 1 that performs congenital heart surgery. The same variables of the MDPI will be collected, plus additional variables specific for infants (blood to prime the oxygenator, plasma for the same purpose; venous oxygen saturation, and others). The variables being independently associated with AKI will enter a logistic regression equation that will be the basis for the I-MDPI. Workpackage 3 considers that AKI is associated with a prolonged mechanical ventilation time, prolonged stay in the intensive care unit and in the hospital; and mortality. Therefore, the MDPI may be predictive of other postoperative complications, apart from AKI, and even of mortality. Some of the factors included in the MDPI may directly (low hematocrit) or indirectly (prolonged CPB duration, excessive hemodilution, low mean arterial pressure) affect the hemostatic system and/or trigger packed red cells transfusions. Additionally, CPB itself is a determinant of a coagulophatic state with associated postoperative bleeding which, in turns, increases the mortality. The specific aim 3 is to confirm the hypothesis that the MDPI may be predictive of one or more of this non-AKI postoperative complications and of 30-days mortality. In the same series of work package and aim 1, these complications will be collected and the MDPI tested for predictive ability of each one of these complications and 30-days mortality. At present, the MDPI can only be calculated off-line, and this greatly limits its applicability. The last step of the aim 3 is based on the involvement of software experts and partnership with companies interested in including the MDPI into their existing monitors; as such, the MDPI patent would be given under licence of the existing patent owned by the IRCCS Policlinico San Donato.

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