Real-Time Acute Kidney Injury Perioperative Prediction Clinical Trial (ML-AKI)
2026년 5월 19일 업데이트: University of California, San Francisco
Prediction of Acute Kidney Injury (AKI) After Surgery: A Pragmatic Three-Arm Cluster-Randomized Trial
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.
연구 개요
상태
상태
아직 모집하지 않음
정황
정황
개입 / 치료
개입 / 치료
연구 유형
연구 유형
중재적
등록 (추정된)
등록
25518
단계
단계
- 해당 없음
연락처 및 위치
이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.
연구 연락처
연구 연락처
- 이름: Andrew Bishara, MD
- 전화번호: 415-502-5880
- 이메일: andrew.bishara@ucsf.edu
연구 장소
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California
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San Francisco, California, 미국, 94158
- University of California, San Francisco
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참여기준
연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.
자격 기준
자격 기준
공부할 수 있는 나이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
예
설명
Inclusion Criteria:
- Adults ≥18 years undergoing non-obstetric surgery at UCSF.
- Inpatient cases with expected overnight stay.
- Baseline eGFR ≥15 mL/min/1.73 m².
- Managed by an attending anesthesiologist randomized to one of three arms (CRNAs/residents follow attending).
- Data available in the UCSF EHR for risk scoring and outcomes.
Exclusion Criteria:
- Obstetric procedures.
- Chronic dialysis patients.
- Kidney transplant recipients.
- Cases without baseline creatinine/eGFR or missing essential EHR elements needed for scoring/outcomes (operational exclusions).
- Outpatient procedures without expected overnight stay.
공부 계획
이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 상영
- 할당: 무작위
- 중재 모델: 병렬 할당
- 마스킹: 없음(오픈 라벨)
팔의 수
3
무기와 개입
참가자 그룹 / 팔참가자 그룹 / 팔 |
개입 / 치료개입 / 치료 |
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간섭 없음: Control Arm
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.
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실험적: Acute Kidney Injury Risk Score Only
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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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.
다른 이름들:
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실험적: Acute Kidney Injury Risk Score with Best Practice Advisory
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.
|
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.
다른 이름들:
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연구는 무엇을 측정합니까?
주요 결과 측정
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Post-operative Change in Creatinine
기간: From pre-operative baseline to 1-2 days post-operative level
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Maximum continuous change in serum creatinine (mg/dL) from baseline to post-operative day 1-2
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From pre-operative baseline to 1-2 days post-operative level
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2차 결과 측정
2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Acute Kidney Injury
기간: Operation to Post-operative Day 7
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Acute Kidney Injury as defined by KDIGO
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Operation to Post-operative Day 7
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KDIGO Bundle Adherence
기간: Intra-operative
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Measurement of provider adherence to KDIGO components
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Intra-operative
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Intra-Operative Time and Severity of Hypotension
기간: Intra-operative
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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
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Intra-operative
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Total intra-operative intravenous fluid volume administered (mL)
기간: Intra-operative
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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.
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Intra-operative
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Length of Stay
기간: Operation to Post-operative Day 180
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Duration of patient admission in hospital in days
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Operation to Post-operative Day 180
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Intra-operative Hyperglycemic Events
기간: Intra-operative
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Number of intra-operative hyperglycemic events, defined as the number of recorded blood glucose measurements exceeding 180 mg/dL.
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Intra-operative
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Intra-operative Nephrotoxin Exposure
기간: Intra-operative
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Number of nephrotoxic medications administered intra-operatively and duration of intra-operative exposure
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Intra-operative
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In-Hospital Mortality
기간: Operation to Post-operative Day 180
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Patient death while admitted in the hospital
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Operation to Post-operative Day 180
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ICU Transfer and total time in the ICU
기간: Postoperative
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Any transfers to the ICU while admitted and the total time the patient spends in the ICU
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Postoperative
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Hospital Readmission
기간: Operation to Post-operative Day 180
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Readmission back to a UCSF hospital following operation
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Operation to Post-operative Day 180
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Dialysis Requirement
기간: Operation to Post-operative Day 180
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Patients requiring dialysis following surgery
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Operation to Post-operative Day 180
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Dilution Corrected KDIGO AKI measurement (Stage 1 or higher)
기간: 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.
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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:
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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.
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Total intra-operative packed red blood cells administered (units transfused)
기간: intraoperative
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Provider administration of packed red blood cells during the intra-operative period, measured as total units transfused.
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intraoperative
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Total intra-operative fresh frozen plasma administered (units transfused)
기간: intraoperative
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Provider administration of fresh frozen plasma during the intra-operative period, measured as total units transfused.
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intraoperative
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Total intra-operative platelets administered (units transfused)
기간: intraoperative
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Provider administration of platelets during the intra-operative period, measured as total units transfused.
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intraoperative
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Total intra-operative cryoprecipitate administered (units transfused)
기간: intraoperative
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Provider administration of cryoprecipitate during the intra-operative period, measured as total units transfused.
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intraoperative
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공동 작업자 및 조사자
여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.
협력자
협력자
수사관
수사관
- 수석 연구원: Andrew Bishara, MD, University of California, San Francisco
간행물 및 유용한 링크
연구에 대한 정보 입력을 담당하는 사람이 자발적으로 이러한 간행물을 제공합니다. 이것은 연구와 관련된 모든 것에 관한 것일 수 있습니다.
일반 간행물
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
연구 기록 날짜
이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.
연구 주요 날짜
연구 시작 (추정된)
연구 시작
2026년 10월 15일
기본 완료 (추정된)
기본 완료
2027년 10월 15일
연구 완료 (추정된)
연구 완료
2027년 12월 15일
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추가 정보
이 연구와 관련된 용어
추가 관련 MeSH 약관
기타 연구 ID 번호
기타 연구 ID 번호
- 22-37005
- K23GM151611-03 (미국 NIH 보조금/계약)
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