Clinical trial NCT06786416: 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
Official title: 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
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Cardiac Diseases
Cardio-pulmonary Bypass
Acute Kidney Injury
Adult Cardiac Surgery
Infants Cardiac Surgery
Extracorporeal Circulation; Complications
Perfusion; Complications
Keywords: cardiopulmonary bypass
acute kidney injury
cardiac surgery
Lead sponsor: IRCCS Policlinico S. Donato
Sponsor class: OTHER
First posted: 2025-01-22
Enrollment: 800
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients hospitalized in our Institution for a scheduled cardiac surgery with cardiopulmonary bypass

Brief 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.

Detailed description: 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. 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. Cardiac surgery associated acute kidney injury (CSA-AKI) is one of the most common postoperative complications, associated with an increased mortality risk. Several risk scores for CSA-AKI exist. They are based on preoperative risk factors and severity of the procedure. They define a static risk (SR) based on non-modifiable risk factors. As so, they do not consider intraoperative variables, that include potentially modifiable risk factors (dynamic risk, DR). In a previous study we have developed a new model for prediction of CSA-AKI that is inclusive of the SR and the DR, producing the Multifactorial Dynamic Perfusion Index (MDPI). The MDPI is based on 7 factors collected during cardiopulmonary bypass (CPB): oxygen delivery time spent on a low oxygen delivery, hematocrit, time on CPB, mean arterial pressure, transfusions and lactate values. The MDPI showed a better discrimination (AUC 0.769) than the other existing models, and a good calibration until a risk of 60%. Of notice 5 out of the 7 predictors composing the MDPI are modifiable risk factors and therefore can be considered as a ¿flight control¿, on-line measure of the quality of perfusion, to prompt interventions by the perfusionist and the anesthesiologist. The MDPI is covered by an Italian patent (n. 102022000012893) owned by the IRCCS Policlinico San Donato with Marco Ranucci as inventor. The patent covers the inclusion of the MDPI into a dedicated monitor collecting the variables on CPB and producing the MDPI. The activities are separated into 3 work-packages (WP).

WP 1: The MDPI has been developed in a single Institution. Additionally, its validation was performed on the same development series using a bootstrap technique. To make this algorithm exportable in different Institutions, a different new series of patients is required (internal validation) and a new series collected in an external Institution (external validation). Additionally, it cannot be excluded that additional risk factors may be identified and included in the MDPI algorithm; moreover, there is the hypothesis that other outcome measures of morbidity and even mortality may be predicted by the MDPI. WP 1 includes the operative Units 1 and 2 and is based on the collection of a new series of consecutive adult patients requiring cardiac surgery with CPB. The study protocol has been already submitted to the Ethics Committee (166/int/2022) and Clinical Trial. Gov for the internal validation at the operative unit 1 and includes 400 patients. An additional amount of 400 patients will be collected at the operative unit 2. In this series, the MDPI parameters will be collected and assessed for discrimination and calibration properties in predicting CSA-AKI (defined as AKI of any kind, AKI stage and AKI stage 2 or greater). Appropriate tools will be applied to define discrimination (ROC analysis) and calibration (calibration plot using LOWESS) properties of the MDPI. This WP is essentially a validation of the existing MDPI as patented by IRCCS Policlinico San Donato WP2: The MDPI has been develop in the adult patient population. There is little information available in the literature about the CSA-AKI risk factors in infants and newborns weighing \< 20 kgs. However, CSA-AKI in this segment of population is present at a rate that is equal or even higher than in the adults. It can be hypothesized that above 20 kgs, the patient is probably comparable to the adult patient, whereas there is a gap in knowledge in infants and newborns. WP2 is intended to cover this gap in knowledge by addressing a series of 200 patients weighing \< 20 kgs and receiving cardiac surgery with CPB for palliation or correction of congenital heart defects, producing an MDPI for infants (I MDPI). This WP will be totally performed at the operative unit 2, that is the largest congenital heart center in Italy. A new patent on the I-MDPI is anticipated.

WP3: This WP is based on the same patient population of WP 1, but has a complementary aim. It is in fact possible that (a) other factors apart from the seven included in the MDPI may be associated with CSA-AKI, therefore deserving to be included in the model (MDPI 2.0) and (b) other outcomes, and namely 30-days mortality may be predicted by the MDPI. Once defined these aims, this WP (that includes the 2 operative units) includes the preliminary steps for the implementation of the MDPI into existing or newly developed monitoring systems for CPB. Dedicated patents are anticipated for MDPI 2.0.

Eligibility criteria: Inclusion Criteria:

* patients undergoing cardiac surgery with cardiopulmonary bypass
* patients \>18 years for WP1 and WP3; patients \<6 years and weight \<20 kg for WP2
* willingness to participate and sign the informed consent

Exclusion Criteria:

* chronic renal failure on dyalisis for WP1 and WP3
* emergency surgery for all WP
* refusal to partecipate

Primary outcomes:
measure: Number of patients with postoperative acute kidney injury
timeFrame: First 48 postoperative hours
Secondary outcomes:
measure: Number of patients with postoperative low cardiac output
timeFrame: First 48 postoperative hours
measure: Number of patients experiencing postoperative major morbidity
timeFrame: First 48 postoperative hours
measure: Number of patients who needed prolonged ICU stay
timeFrame: First 4 postoperative days
measure: Number of deceased patients
timeFrame: 30 days after surgery
Other outcomes:
Locations:
city: San Donato Milanese
country: Italy
facility: IRCCS Policlinico San Donato
state: Milano
Study officials:
References:
citation: Brown JK, Shaw AD, Mythen MG, Guzzi L, Reddy VS, Crisafi C, Engelman DT; PeriOperative Quality Initiative and the Enhanced Recovery After Surgery Cardiac Workgroup. Adult Cardiac Surgery-Associated Acute Kidney Injury: Joint Consensus Report. J Cardiothorac Vasc Anesth. 2023 Sep;37(9):1579-1590. doi: 10.1053/j.jvca.2023.05.032. Epub 2023 May 23.
citation: Karkouti K, Wijeysundera DN, Yau TM, Beattie WS, Abdelnaem E, McCluskey SA, Ghannam M, Yeo E, Djaiani G, Karski J. The independent association of massive blood loss with mortality in cardiac surgery. Transfusion. 2004 Oct;44(10):1453-62. doi: 10.1111/j.1537-2995.2004.04144.x.
citation: Bartoszko J, Karkouti K. Managing the coagulopathy associated with cardiopulmonary bypass. J Thromb Haemost. 2021 Mar;19(3):617-632. doi: 10.1111/jth.15195. Epub 2020 Dec 17.
citation: Sanaiha Y, Hadaya J, Verma A, Shemin RJ, Madani M, Young N, Deuse T, Sun J, Benharash P; University of California Cardiac Surgery Consortium. Morbidity and Mortality Associated With Blood Transfusions in Elective Adult Cardiac Surgery. J Cardiothorac Vasc Anesth. 2023 Sep;37(9):1591-1598. doi: 10.1053/j.jvca.2022.11.012. Epub 2022 Nov 17.
citation: Lee JH, Jung JY, Park SW, Song IK, Kim EH, Kim HS, Kim JT. Risk factors of acute kidney injury in children after cardiac surgery. Acta Anaesthesiol Scand. 2018 Nov;62(10):1374-1382. doi: 10.1111/aas.13210. Epub 2018 Jul 11.
citation: Zhang Y, Wang B, Zhou XJ, Guo LJ, Zhou RH. Nadir Oxygen Delivery During Pediatric Bypass as a Predictor of Acute Kidney Injury. Ann Thorac Surg. 2022 Feb;113(2):647-653. doi: 10.1016/j.athoracsur.2021.01.026. Epub 2021 Jan 29.
citation: Puzanov A, Tkachuk V, Maksymenko A. Acute kidney injury after arterial switch operation: incidence, risk factors, clinical impact - a retrospective single-center study. Ren Fail. 2023 Dec;45(1):2167661. doi: 10.1080/0886022X.2023.2167661.
citation: Levey AS, Levin A, Kellum JA. Definition and classification of kidney diseases. Am J Kidney Dis. 2013 May;61(5):686-8. doi: 10.1053/j.ajkd.2013.03.003. No abstract available.
citation: Ranucci M, Di Dedda U, Cotza M, Zamalloa Moreano K. The multifactorial dynamic perfusion index: A predictive tool of cardiac surgery associated acute kidney injury. Perfusion. 2024 Jan;39(1):201-209. doi: 10.1177/02676591221137033. Epub 2022 Oct 28.
citation: Rasmussen SR, Kandler K, Nielsen RV, Cornelius Jakobsen P, Knudsen NN, Ranucci M, Christian Nilsson J, Ravn HB. Duration of critically low oxygen delivery is associated with acute kidney injury after cardiac surgery. Acta Anaesthesiol Scand. 2019 Nov;63(10):1290-1297. doi: 10.1111/aas.13457. Epub 2019 Sep 10.
citation: Ranucci M, Romitti F, Isgro G, Cotza M, Brozzi S, Boncilli A, Ditta A. Oxygen delivery during cardiopulmonary bypass and acute renal failure after coronary operations. Ann Thorac Surg. 2005 Dec;80(6):2213-20. doi: 10.1016/j.athoracsur.2005.05.069.
citation: Fang WC, Helm RE, Krieger KH, Rosengart TK, DuBois WJ, Sason C, Lesser ML, Isom OW, Gold JP. Impact of minimum hematocrit during cardiopulmonary bypass on mortality in patients undergoing coronary artery surgery. Circulation. 1997 Nov 4;96(9 Suppl):II-194-9.
citation: Ranucci M, Pavesi M, Mazza E, Bertucci C, Frigiola A, Menicanti L, Ditta A, Boncilli A, Conti D. Risk factors for renal dysfunction after coronary surgery: the role of cardiopulmonary bypass technique. Perfusion. 1994;9(5):319-26. doi: 10.1177/026765919400900503.
citation: Thakar CV, Arrigain S, Worley S, Yared JP, Paganini EP. A clinical score to predict acute renal failure after cardiac surgery. J Am Soc Nephrol. 2005 Jan;16(1):162-8. doi: 10.1681/ASN.2004040331. Epub 2004 Nov 24.
citation: Chertow GM, Levy EM, Hammermeister KE, Grover F, Daley J. Independent association between acute renal failure and mortality following cardiac surgery. Am J Med. 1998 Apr;104(4):343-8. doi: 10.1016/s0002-9343(98)00058-8.
citation: Pickering JW, James MT, Palmer SC. Acute kidney injury and prognosis after cardiopulmonary bypass: a meta-analysis of cohort studies. Am J Kidney Dis. 2015 Feb;65(2):283-93. doi: 10.1053/j.ajkd.2014.09.008. Epub 2014 Nov 5.