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| ID | Type | Description | Link |
|---|---|---|---|
| K23GM151611-03 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute of General Medical Sciences (NIGMS) | NIH |
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This investigator-initiated, pragmatic trial evaluates whether displaying a machine learning (ML)- derived perioperative AKI risk score-alone or paired with an interruptive Best/Our Practice Advisory (BPA/OPA)-improves kidney-protective care and reduces kidney injury after non-obstetric surgery at UCSF. Approximately 75-100 attending anesthesiologists (clusters) are randomized 1:1:1 to: (a) Control (risk score hidden), (b) Score Only (visible preoperative AKI risk probability with passive KDIGO bundle recommendation), or (c) Score + BPA (visible risk plus interruptive KDIGO prompt for high-risk patients). CRNAs/residents follow their attending' s assignment. Adult inpatients (age ≥18) with expected overnight stay and eGFR ≥15 mL/min/1.73 m² are included; obstetrics, chronic dialysis, and kidney transplant patients are excluded. The underlying preoperative model was prospectively validated at UCSF and outperforms anesthesiologist risk estimation reported in the literature. The model was reviewed and approved by the AI Oversight Committee at UCSF. Primary endpoint is the continuous change in serum creatinine (mg/dL) from baseline to POD 1-2. Secondary outcomes include KDIGO-defined AKI, adherence to bundle elements (hemodynamics, balanced fluids, nephrotoxin avoidance, glycemic control), intraoperative hypotension time, fluid volumes, nephrotoxin exposure, perioperative hyperglycemia, length of stay, unplanned ICU transfer, readmission, dialysis, and in-hospital mortality. Data are obtained from the EHR; analysts are blinded. No direct subject interaction is planned; the investigators will request a waiver of patient consent. The study aims to demonstrate that ML-enabled, workflow-embedded decision support can safely and feasibly improve guideline concordant care and decrease early postoperative kidney injury.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control Arm | No Intervention | Participants receive usual perioperative care with a placeholder blank display without the machine learning-derived acute kidney injury (AKI) risk score. The clinical decision support tool remains hidden in the electronic health record, and no alerts or recommendations related to the study are shown. | |
| Acute Kidney Injury Risk Score Only | Experimental | A machine learning-derived preoperative AKI risk score is displayed within the electronic health record for high-risk patients. A passive recommendation indicating that the patient may benefit from a KDIGO-based kidney-protective bundle is provided. The information is advisory only, and no interruptive alerts are used. |
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| Acute Kidney Injury Risk Score with Best Practice Advisory | Experimental | The machine learning-derived AKI risk score is displayed within the electronic health record for high-risk patients, accompanied by an interruptive Best Practice Advisory (BPA) that notifies providers that the patient may benefit from a KDIGO-based kidney-protective bundle. The alert is advisory only and does not mandate clinical actions. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| EHR-Embedded AKI Risk Score | Device | A non-adaptive, machine learning-based clinical decision support tool integrated into the electronic health record that generates a preoperative probability of acute kidney injury (AKI) using routinely collected patient data. For patients identified as high risk, the tool displays the risk estimate to anesthesia providers without an accompanying Best Practice Advisory (BPA) recommending consideration of a KDIGO-based kidney-protective bundle. The intervention is advisory only, does not mandate clinical actions, and is designed to support provider decision-making within the existing clinical workflow. |
| Measure | Description | Time Frame |
|---|---|---|
| Post-operative Change in Creatinine | Maximum continuous change in serum creatinine (mg/dL) from baseline to post-operative day 1-2 | From pre-operative baseline to 1-2 days post-operative level |
| Measure | Description | Time Frame |
|---|---|---|
| Acute Kidney Injury | Acute Kidney Injury as defined by KDIGO | Operation to Post-operative Day 7 |
| KDIGO Bundle Adherence | Measurement of provider adherence to KDIGO components |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Andrew Bishara, MD | Contact | 415-502-5880 | andrew.bishara@ucsf.edu |
| Name | Affiliation | Role |
|---|---|---|
| Andrew Bishara, MD | University of California, San Francisco | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of California, San Francisco | San Francisco | California | 94158 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 39430177 | Background | James MT, Dixon E, Tan Z, Mathura P, Datta I, Lall RN, Landry J, Minty EP, Samis GA, Winkelaar GB, Pannu N. Stepped-Wedge Trial of Decision Support for Acute Kidney Injury on Surgical Units. Kidney Int Rep. 2024 Jul 31;9(10):2996-3005. doi: 10.1016/j.ekir.2024.07.025. eCollection 2024 Oct. | |
| 33684086 | Background | Zarbock A, Kullmar M, Ostermann M, Lucchese G, Baig K, Cennamo A, Rajani R, McCorkell S, Arndt C, Wulf H, Irqsusi M, Monaco F, Di Prima AL, Garcia Alvarez M, Italiano S, Miralles Bagan J, Kunst G, Nair S, L'Acqua C, Hoste E, Vandenberghe W, Honore PM, Kellum JA, Forni LG, Grieshaber P, Massoth C, Weiss R, Gerss J, Wempe C, Meersch M. Prevention of Cardiac Surgery-Associated Acute Kidney Injury by Implementing the KDIGO Guidelines in High-Risk Patients Identified by Biomarkers: The PrevAKI-Multicenter Randomized Controlled Trial. Anesth Analg. 2021 Aug 1;133(2):292-302. doi: 10.1213/ANE.0000000000005458. |
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| ID | Term |
|---|---|
| D058186 | Acute Kidney Injury |
| ID | Term |
|---|---|
| D051437 | Renal Insufficiency |
| D007674 | Kidney Diseases |
| D014570 | Urologic Diseases |
| D052776 | Female Urogenital Diseases |
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This is a pragmatic, single-center, three-arm, parallel-group, cluster-randomized controlled trial. Attending anesthesiologists are the unit of randomization and are assigned in a 1:1:1 ratio to one of three groups: (1) control (AKI risk score not displayed), (2) score only (visible preoperative machine learning-derived AKI risk score with passive KDIGO bundle recommendation), or (3) score plus Best Practice Advisory (visible risk score with an interruptive KDIGO-based alert for high-risk patients). All eligible surgical cases managed by a given attending anesthesiologist inherit that provider's assigned study arm. Trainees and nurse anesthetists follow the assignment of the supervising attending. The intervention is delivered within the electronic health record at the point of care. The clinical decision support tools are advisory only and do not mandate any clinical actions. There is no crossover between groups, and allocation remains fixed for the duration of the study.
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| EHR-Embedded AKI Risk Score with Best Practice Advisory | Device | A non-adaptive, machine learning-based clinical decision support tool integrated into the electronic health record that generates a preoperative probability of acute kidney injury (AKI) using routinely collected patient data. For patients identified as high risk, the tool displays the risk estimate to anesthesia providers with an accompanying Best Practice Advisory (BPA) recommending consideration of a KDIGO-based kidney-protective bundle. The intervention is advisory only, does not mandate clinical actions, and is designed to support provider decision-making within the existing clinical workflow. |
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| Intra-operative |
| Intra-Operative Time and Severity of Hypotension | Intra-Operative Time and Severity (meaning how far below the threshold) where patient is in hypotension, defined as systolic blood pressure <90 mmHg and mean arterial pressure <65 mmHg during surgery | Intra-operative |
| Total intra-operative intravenous fluid volume administered (mL) | Provider administration of intravenous fluids during the intra-operative period, measured in milliliters (mL). Intravenous fluids include normal saline, lactated Ringer's, Plasma-Lyte, other balanced crystalloids, and colloid solutions such as albumin. | Intra-operative |
| Length of Stay | Duration of patient admission in hospital in days | Operation to Post-operative Day 180 |
| Intra-operative Hyperglycemic Events | Number of intra-operative hyperglycemic events, defined as the number of recorded blood glucose measurements exceeding 180 mg/dL. | Intra-operative |
| Intra-operative Nephrotoxin Exposure | Number of nephrotoxic medications administered intra-operatively and duration of intra-operative exposure | Intra-operative |
| In-Hospital Mortality | Patient death while admitted in the hospital | Operation to Post-operative Day 180 |
| ICU Transfer and total time in the ICU | Any transfers to the ICU while admitted and the total time the patient spends in the ICU | Postoperative |
| Hospital Readmission | Readmission back to a UCSF hospital following operation | Operation to Post-operative Day 180 |
| Dialysis Requirement | Patients requiring dialysis following surgery | Operation to Post-operative Day 180 |
| Dilution Corrected KDIGO AKI measurement (Stage 1 or higher) | Acute kidney injury (AKI) assessed using KDIGO creatinine criteria applied to dilution-corrected postoperative serum creatinine. Creatinine is corrected for hemodilution from perioperative fluid retention using the formula: Corrected Creatinine (mg/dL) = Measured Creatinine × (1 + Net Fluid Balance / Total Body Water) Where:
| AKI is defined per KDIGO as corrected creatinine increase ≥0.3 mg/dL within 48 hours or ≥1.5× baseline within 7 days. This measure captures "hidden AKI" - kidney injury masked by fluid dilution that would be missed using standard uncorrected creatinine. |
| Total intra-operative packed red blood cells administered (units transfused) | Provider administration of packed red blood cells during the intra-operative period, measured as total units transfused. | intraoperative |
| Total intra-operative fresh frozen plasma administered (units transfused) | Provider administration of fresh frozen plasma during the intra-operative period, measured as total units transfused. | intraoperative |
| Total intra-operative platelets administered (units transfused) | Provider administration of platelets during the intra-operative period, measured as total units transfused. | intraoperative |
| Total intra-operative cryoprecipitate administered (units transfused) | Provider administration of cryoprecipitate during the intra-operative period, measured as total units transfused. | intraoperative |
| 22890468 | Background | Khwaja A. KDIGO clinical practice guidelines for acute kidney injury. Nephron Clin Pract. 2012;120(4):c179-84. doi: 10.1159/000339789. Epub 2012 Aug 7. No abstract available. |
| 23835589 | Background | Walsh M, Devereaux PJ, Garg AX, Kurz A, Turan A, Rodseth RN, Cywinski J, Thabane L, Sessler DI. Relationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac surgery: toward an empirical definition of hypotension. Anesthesiology. 2013 Sep;119(3):507-15. doi: 10.1097/ALN.0b013e3182a10e26. |
| 26181335 | Background | Sun LY, Wijeysundera DN, Tait GA, Beattie WS. Association of intraoperative hypotension with acute kidney injury after elective noncardiac surgery. Anesthesiology. 2015 Sep;123(3):515-23. doi: 10.1097/ALN.0000000000000765. |
| 26492475 | Background | Kork F, Balzer F, Spies CD, Wernecke KD, Ginde AA, Jankowski J, Eltzschig HK. Minor Postoperative Increases of Creatinine Are Associated with Higher Mortality and Longer Hospital Length of Stay in Surgical Patients. Anesthesiology. 2015 Dec;123(6):1301-11. doi: 10.1097/ALN.0000000000000891. |
| 38050260 | Background | Fujii T, Takakura M, Taniguchi T, Tamura T, Nishiwaki K. Intraoperative hypotension affects postoperative acute kidney injury depending on the invasiveness of abdominal surgery: A retrospective cohort study. Medicine (Baltimore). 2023 Dec 1;102(48):e36465. doi: 10.1097/MD.0000000000036465. |
| D005261 |
| Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D052801 | Male Urogenital Diseases |