xml: <clinical_study>
    <!-- This xml conforms to an XML Schema at:
      https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
    <required_header>
      <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
      <link_text>Link to the current ClinicalTrials.gov record.</link_text>
      <url>https://clinicaltrials.gov/ct2/show/NCT06019546</url>
    </required_header>
    <id_info>
      <org_study_id>PEQUOD</org_study_id>
      <nct_id>NCT06019546</nct_id>
    </id_info>
    <brief_title>PErfusion QUality ODds</brief_title>
    <acronym>PEQUOD</acronym>
    <official_title>Perfusion Quality Odds</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>IRCCS Policlinico S. Donato</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>IRCCS Policlinico S. Donato</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        Cardiac surgery-associated acute kidney injury (CSA-AKI) is a frequent complication after&#xD;
        cardiac operations with cardiopulmonary bypass (CPB) use. Its frequency varies depending on&#xD;
        the severity grade. There are different &quot;static&quot; predictive scores for the CSA-AKI based on&#xD;
        the patient and surgery-associated parameters.&#xD;
  &#xD;
        Recently, in our Institution was developed a predictive algorithm for CSA-AKI that starts&#xD;
        with a static model and then integrated with 7 CPB-associated parameters: HCT, DO2, time of&#xD;
        exposure to a critical DO2, systemic pressure, CPB duration time, lactate value, transfusion&#xD;
        of red blood cells (RBC), that together build a dynamic perfusion risk (DPR) associated to&#xD;
        the CPB. Combining the static and dynamic models produces the Multifactorial Dynamic&#xD;
        Perfusion Index (MDPI).&#xD;
  &#xD;
        The present study validates MDPI in a new prospective series of patients undergoing cardiac&#xD;
        surgery with CPB.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        Cardiac surgery-associated acute kidney injury (CSA-AKI) is a frequent complication after&#xD;
        cardiac operations with cardiopulmonary bypass (CPB) use. Its frequency varies depending on&#xD;
        the severity grade which for the present study follows the AKIN criteria.&#xD;
  &#xD;
        There are different predictive scores for the CSA-AKI based on the patient and&#xD;
        surgery-associated parameters. These models could be defined as &quot;static&quot;.&#xD;
  &#xD;
        It's known that a number of CPB-associated parameters could influence CSA-AKI, as well. These&#xD;
        include hematocrit (HCT), oxygen delivery (DO2), time of exposure to a critical DO2, and&#xD;
        perfusion pressure. These parameters, taken separately, are associated with CSA-AKI&#xD;
        development.&#xD;
  &#xD;
        Recently, our Institution has developed a predictive algorithm for CSA-AKI that starts with a&#xD;
        static model and then integrated with 7 CPB-associated parameters: HCT, DO2, time of exposure&#xD;
        to a critical DO2, systemic pressure, CPB duration time, lactate value, transfusion of red&#xD;
        blood cells (RBC), that together build a dynamic perfusion risk (DPR) associated to the CPB.&#xD;
        Combining the static and dynamic models produces the Multifactorial Dynamic Perfusion Index&#xD;
        (MDPI).&#xD;
  &#xD;
        MDPI has higher discrimination power when compared to the static scores, in the original&#xD;
        series and in the internal validation with the Bootstrap technique.&#xD;
  &#xD;
        The present study validates MDPI in a new prospective series of patients undergoing cardiac&#xD;
        surgery with CPB. An enrollment of 400 patients is anticipated with a stopping rule for&#xD;
        efficacy at interim analysis (for primary endpoint) at 50% enrollment (200 patients) if the&#xD;
        c-statistics for any stage of CSA-AKI reaches at least 0.75. Futility is defined as an AUC of&#xD;
        0.6 or lower.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Recruiting</overall_status>
    <start_date type="Actual">January 23, 2023</start_date>
    <completion_date type="Anticipated">December 31, 2023</completion_date>
    <primary_completion_date type="Anticipated">December 31, 2023</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Cohort</observational_model>
      <time_perspective>Prospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>Acute kidney injury</measure>
      <time_frame>First 48 postoperative hours</time_frame>
      <description>Occurence of any stage acute kidney injury as defined by the AKIN criteria</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Respiratory insufficiency</measure>
      <time_frame>First 48 postoperative hours</time_frame>
      <description>P/F ratio &gt; 200 with radiographic evidence of pulmonary distress, if compared to the baseline by an independent radiologist</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Low cardiac output</measure>
      <time_frame>First 48 postoperative hours</time_frame>
      <description>Use of inotrope drugs for more than 48 hours and/or mechanical support</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Major morbidity</measure>
      <time_frame>First 48 postoperative hours</time_frame>
      <description>As defined by STS criteria as one or more of the following items: AKI stage 2, stroke, mechanical ventilation duration &gt; 48 hours, sepsis, surgical re-exploration</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Prolonged ICU stay</measure>
      <time_frame>First 4 postoperative days</time_frame>
      <description>ICu stay duration &gt; 4 days</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Mortality</measure>
      <time_frame>30 days after surgery</time_frame>
      <description>Dead or alive status</description>
    </secondary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Anticipated">400</enrollment>
    <condition>Cardiac Disease</condition>
    <condition>Extracorporeal Circulation; Complications</condition>
    <condition>Perfusion; Complications</condition>
    <condition>Acute Kidney Injury</condition>
    <arm_group>
      <arm_group_label>PEQUOD</arm_group_label>
      <description>Patients undergoing cardiac surgery with cardiopulmonary bypass whose parameters of interest will be registered during cardiopulmonary bypass by the Livanova BE-CAPTA monitor.</description>
    </arm_group>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>PEQUOD</intervention_name>
      <description>During cardiopulmonary bypass registration of the parameters of interest by the Livanova BE-CAPTA monitor. After surgery, registration of creatinine values up to 48 postoperative hours.</description>
      <arm_group_label>PEQUOD</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          Patients hospitalized in our Institution for a scheduled cardiac surgery with&#xD;
          cardiopulmonary bypass&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  patients undergoing cardiac surgery with cardiopulmonary bypass&#xD;
  &#xD;
            -  age of 18 years and higher&#xD;
  &#xD;
            -  willingness to participate and sign the informed consent&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
          - patients requiring preoperative dialysis&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Marco Ranucci, MD</last_name>
      <role>Principal Investigator</role>
      <affiliation>IRCCS Policlinico S. Donato</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Marco Ranucci, MD</last_name>
      <phone>0252774754</phone>
      <phone_ext>+39</phone_ext>
      <email>marco.ranucci@grupposandonato.it</email>
    </overall_contact>
    <location>
      <facility>
        <name>IRCCS Policlinico San Donato</name>
        <address>
          <city>San Donato Milanese</city>
          <state>MI</state>
          <zip>20097</zip>
          <country>Italy</country>
        </address>
      </facility>
      <status>Recruiting</status>
      <contact>
        <last_name>Valeria Pistuddi</last_name>
        <phone>0252774754</phone>
        <phone_ext>+39</phone_ext>
        <email>valeria.pistuddi@grupposandonato.it</email>
      </contact>
    </location>
    <location_countries>
      <country>Italy</country>
    </location_countries>
    <reference>
      <citation>Ranucci M, Aloisio T, Cazzaniga A, Di Dedda U, Gallazzi C, Pistuddi V. Validation of renal-risk models for the prediction of non-renal replacement therapy cardiac surgery-associated acute kidney injury. Int J Cardiol. 2018 Dec 1;272:49-53. doi: 10.1016/j.ijcard.2018.07.114. Epub 2018 Jul 24.</citation>
      <PMID>30078648</PMID>
    </reference>
    <reference>
      <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>
      <PMID>15563569</PMID>
    </reference>
    <reference>
      <citation>Mehta RH, Grab JD, O'Brien SM, Bridges CR, Gammie JS, Haan CK, Ferguson TB, Peterson ED; Society of Thoracic Surgeons National Cardiac Surgery Database Investigators. Bedside tool for predicting the risk of postoperative dialysis in patients undergoing cardiac surgery. Circulation. 2006 Nov 21;114(21):2208-16; quiz 2208. doi: 10.1161/CIRCULATIONAHA.106.635573. Epub 2006 Nov 6.</citation>
      <PMID>17088458</PMID>
    </reference>
    <reference>
      <citation>Wijeysundera DN, Karkouti K, Dupuis JY, Rao V, Chan CT, Granton JT, Beattie WS. Derivation and validation of a simplified predictive index for renal replacement therapy after cardiac surgery. JAMA. 2007 Apr 25;297(16):1801-9. doi: 10.1001/jama.297.16.1801.</citation>
      <PMID>17456822</PMID>
    </reference>
    <reference>
      <citation>Swaminathan M, Phillips-Bute BG, Conlon PJ, Smith PK, Newman MF, Stafford-Smith M. The association of lowest hematocrit during cardiopulmonary bypass with acute renal injury after coronary artery bypass surgery. Ann Thorac Surg. 2003 Sep;76(3):784-91; discussion 792. doi: 10.1016/s0003-4975(03)00558-7.</citation>
      <PMID>12963200</PMID>
    </reference>
    <reference>
      <citation>Habib RH, Zacharias A, Schwann TA, Riordan CJ, Durham SJ, Shah A. Adverse effects of low hematocrit during cardiopulmonary bypass in the adult: should current practice be changed? J Thorac Cardiovasc Surg. 2003 Jun;125(6):1438-50. doi: 10.1016/s0022-5223(02)73291-1.</citation>
      <PMID>12830066</PMID>
    </reference>
    <reference>
      <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>
      <PMID>16305874</PMID>
    </reference>
    <reference>
      <citation>Ranucci M, Johnson I, Willcox T, Baker RA, Boer C, Baumann A, Justison GA, de Somer F, Exton P, Agarwal S, Parke R, Newland RF, Haumann RG, Buchwald D, Weitzel N, Venkateswaran R, Ambrogi F, Pistuddi V. Goal-directed perfusion to reduce acute kidney injury: A randomized trial. J Thorac Cardiovasc Surg. 2018 Nov;156(5):1918-1927.e2. doi: 10.1016/j.jtcvs.2018.04.045. Epub 2018 Apr 18.</citation>
      <PMID>29778331</PMID>
    </reference>
    <reference>
      <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>
      <PMID>31436307</PMID>
    </reference>
    <reference>
      <citation>de la Hoz MA, Rangasamy V, Bastos AB, Xu X, Novack V, Saugel B, Subramaniam B. Intraoperative Hypotension and Acute Kidney Injury, Stroke, and Mortality during and outside Cardiopulmonary Bypass: A Retrospective Observational Cohort Study. Anesthesiology. 2022 Jun 1;136(6):927-939. doi: 10.1097/ALN.0000000000004175.</citation>
      <PMID>35188970</PMID>
    </reference>
    <reference>
      <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. 2022 Oct 28:2676591221137033. doi: 10.1177/02676591221137033. Online ahead of print.</citation>
      <PMID>36305847</PMID>
    </reference>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>August 25, 2023</study_first_submitted>
    <study_first_submitted_qc>August 25, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 31, 2023</study_first_posted>
    <last_update_submitted>August 25, 2023</last_update_submitted>
    <last_update_submitted_qc>August 25, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 31, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Principal Investigator</responsible_party_type>
      <investigator_affiliation>IRCCS Policlinico S. Donato</investigator_affiliation>
      <investigator_full_name>Marco Ranucci</investigator_full_name>
      <investigator_title>Director of the Cardiovascular Anesthesia and Intensive Care Department</investigator_title>
    </responsible_party>
    <keyword>acute kidney injury</keyword>
    <keyword>cardiopulmonary bypass</keyword>
    <keyword>cardiac surgery</keyword>
    <keyword>risk score</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Acute Kidney Injury</mesh_term>
      <mesh_term>Heart Diseases</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
      <ipd_description>The original dataset supporting the findings of this study will be deposited in the public repository Zenodo after the publication of the work and accessible upon a reasonable request. The requests should be addressed to the Principal Investigator of the study.</ipd_description>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: download date: ClinicalTrials.gov processed this data on September 20, 2023
  link text: Link to the current ClinicalTrials.gov record.
  url: https://clinicaltrials.gov/ct2/show/NCT06019546
  org study id: PEQUOD
  nct id: NCT06019546
  lead sponsor: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  Cardiac surgery-associated acute kidney injury (CSA-AKI) is a frequent complication after
        cardiac operations with cardiopulmonary bypass (CPB) use. Its frequency varies depending on
        the severity grade. There are different "static" predictive scores for the CSA-AKI based on
        the patient and surgery-associated parameters.
  
        Recently, in our Institution was developed a predictive algorithm for CSA-AKI that starts
        with a static model and then integrated with 7 CPB-associated parameters: HCT, DO2, time of
        exposure to a critical DO2, systemic pressure, CPB duration time, lactate value, transfusion
        of red blood cells (RBC), that together build a dynamic perfusion risk (DPR) associated to
        the CPB. Combining the static and dynamic models produces the Multifactorial Dynamic
        Perfusion Index (MDPI).
  
        The present study validates MDPI in a new prospective series of patients undergoing cardiac
        surgery with CPB.
  Cardiac surgery-associated acute kidney injury (CSA-AKI) is a frequent complication after
        cardiac operations with cardiopulmonary bypass (CPB) use. Its frequency varies depending on
        the severity grade which for the present study follows the AKIN criteria.
  
        There are different predictive scores for the CSA-AKI based on the patient and
        surgery-associated parameters. These models could be defined as "static".
  
        It's known that a number of CPB-associated parameters could influence CSA-AKI, as well. These
        include hematocrit (HCT), oxygen delivery (DO2), time of exposure to a critical DO2, and
        perfusion pressure. These parameters, taken separately, are associated with CSA-AKI
        development.
  
        Recently, our Institution has developed a predictive algorithm for CSA-AKI that starts with a
        static model and then integrated with 7 CPB-associated parameters: HCT, DO2, time of exposure
        to a critical DO2, systemic pressure, CPB duration time, lactate value, transfusion of red
        blood cells (RBC), that together build a dynamic perfusion risk (DPR) associated to the CPB.
        Combining the static and dynamic models produces the Multifactorial Dynamic Perfusion Index
        (MDPI).
  
        MDPI has higher discrimination power when compared to the static scores, in the original
        series and in the internal validation with the Bootstrap technique.
  
        The present study validates MDPI in a new prospective series of patients undergoing cardiac
        surgery with CPB. An enrollment of 400 patients is anticipated with a stopping rule for
        efficacy at interim analysis (for primary endpoint) at 50% enrollment (200 patients) if the
        c-statistics for any stage of CSA-AKI reaches at least 0.75. Futility is defined as an AUC of
        0.6 or lower.
  observational model: Cohort
  time perspective: Prospective
  measure: Acute kidney injury
  time frame: First 48 postoperative hours
  description: Occurence of any stage acute kidney injury as defined by the AKIN criteria
  measure: Respiratory insufficiency
  time frame: First 48 postoperative hours
  description: P/F ratio > 200 with radiographic evidence of pulmonary distress, if compared to the baseline by an independent radiologist
  measure: Low cardiac output
  time frame: First 48 postoperative hours
  description: Use of inotrope drugs for more than 48 hours and/or mechanical support
  measure: Major morbidity
  time frame: First 48 postoperative hours
  description: As defined by STS criteria as one or more of the following items: AKI stage 2, stroke, mechanical ventilation duration > 48 hours, sepsis, surgical re-exploration
  measure: Prolonged ICU stay
  time frame: First 4 postoperative days
  description: ICu stay duration > 4 days
  measure: Mortality
  time frame: 30 days after surgery
  description: Dead or alive status
  arm group label: PEQUOD
  description: Patients undergoing cardiac surgery with cardiopulmonary bypass whose parameters of interest will be registered during cardiopulmonary bypass by the Livanova BE-CAPTA monitor.
  intervention type: Other
  intervention name: PEQUOD
  description: During cardiopulmonary bypass registration of the parameters of interest by the Livanova BE-CAPTA monitor. After surgery, registration of creatinine values up to 48 postoperative hours.
  arm group label: PEQUOD
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: No
  last name: Marco Ranucci, MD
  role: Principal Investigator
  affiliation: IRCCS Policlinico S. Donato
  last name: Marco Ranucci, MD
  phone: 0252774754
  phone ext: +39
  email: marco.ranucci@grupposandonato.it
  facility: 
  status: Recruiting
  contact: 
  country: Italy
  citation: Ranucci M, Aloisio T, Cazzaniga A, Di Dedda U, Gallazzi C, Pistuddi V. Validation of renal-risk models for the prediction of non-renal replacement therapy cardiac surgery-associated acute kidney injury. Int J Cardiol. 2018 Dec 1;272:49-53. doi: 10.1016/j.ijcard.2018.07.114. Epub 2018 Jul 24.
  PMID: 30078648
  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.
  PMID: 15563569
  citation: Mehta RH, Grab JD, O'Brien SM, Bridges CR, Gammie JS, Haan CK, Ferguson TB, Peterson ED; Society of Thoracic Surgeons National Cardiac Surgery Database Investigators. Bedside tool for predicting the risk of postoperative dialysis in patients undergoing cardiac surgery. Circulation. 2006 Nov 21;114(21):2208-16; quiz 2208. doi: 10.1161/CIRCULATIONAHA.106.635573. Epub 2006 Nov 6.
  PMID: 17088458
  citation: Wijeysundera DN, Karkouti K, Dupuis JY, Rao V, Chan CT, Granton JT, Beattie WS. Derivation and validation of a simplified predictive index for renal replacement therapy after cardiac surgery. JAMA. 2007 Apr 25;297(16):1801-9. doi: 10.1001/jama.297.16.1801.
  PMID: 17456822
  citation: Swaminathan M, Phillips-Bute BG, Conlon PJ, Smith PK, Newman MF, Stafford-Smith M. The association of lowest hematocrit during cardiopulmonary bypass with acute renal injury after coronary artery bypass surgery. Ann Thorac Surg. 2003 Sep;76(3):784-91; discussion 792. doi: 10.1016/s0003-4975(03)00558-7.
  PMID: 12963200
  citation: Habib RH, Zacharias A, Schwann TA, Riordan CJ, Durham SJ, Shah A. Adverse effects of low hematocrit during cardiopulmonary bypass in the adult: should current practice be changed? J Thorac Cardiovasc Surg. 2003 Jun;125(6):1438-50. doi: 10.1016/s0022-5223(02)73291-1.
  PMID: 12830066
  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.
  PMID: 16305874
  citation: Ranucci M, Johnson I, Willcox T, Baker RA, Boer C, Baumann A, Justison GA, de Somer F, Exton P, Agarwal S, Parke R, Newland RF, Haumann RG, Buchwald D, Weitzel N, Venkateswaran R, Ambrogi F, Pistuddi V. Goal-directed perfusion to reduce acute kidney injury: A randomized trial. J Thorac Cardiovasc Surg. 2018 Nov;156(5):1918-1927.e2. doi: 10.1016/j.jtcvs.2018.04.045. Epub 2018 Apr 18.
  PMID: 29778331
  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.
  PMID: 31436307
  citation: de la Hoz MA, Rangasamy V, Bastos AB, Xu X, Novack V, Saugel B, Subramaniam B. Intraoperative Hypotension and Acute Kidney Injury, Stroke, and Mortality during and outside Cardiopulmonary Bypass: A Retrospective Observational Cohort Study. Anesthesiology. 2022 Jun 1;136(6):927-939. doi: 10.1097/ALN.0000000000004175.
  PMID: 35188970
  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. 2022 Oct 28:2676591221137033. doi: 10.1177/02676591221137033. Online ahead of print.
  PMID: 36305847
  responsible party type: Principal Investigator
  investigator affiliation: IRCCS Policlinico S. Donato
  investigator full name: Marco Ranucci
  investigator title: Director of the Cardiovascular Anesthesia and Intensive Care Department
  mesh term: Acute Kidney Injury
  mesh term: Heart Diseases
  sharing ipd: No
  ipd description: The original dataset supporting the findings of this study will be deposited in the public repository Zenodo after the publication of the work and accessible upon a reasonable request. The requests should be addressed to the Principal Investigator of the study.