Acute kidney injury risk prediction score for critically-ill surgical patients

被引:21
|
作者
Trongtrakul, Konlawij [1 ,2 ]
Patumanond, Jayanton [3 ]
Kongsayreepong, Suneerat [4 ]
Morakul, Sunthiti [5 ]
Pipanmekaporn, Tanyong [6 ]
Akaraborworn, Osaree [7 ]
Poopipatpab, Sujaree [8 ]
机构
[1] Navamindradhiraj Univ, Fac Med, Crit Care Div, Internal Med Dept,Varjia Hosp, Bangkok, Thailand
[2] Thammasat Univ, Clin Epidemiol Dept, Fac Med, Pathum Thani, Thailand
[3] Chiang Mai Univ, Ctr Clin Epidemiol & Clin Stat, Fac Med, Chiang Mai, Thailand
[4] Mahidol Univ, Fac Med, Anesthesiol Dept, Siriraj Hosp, Bangkok, Thailand
[5] Mahidol Univ, Fac Med, Anesthesiol Dept, Ramathibodi Hosp, Bangkok, Thailand
[6] Chiang Mai Univ, Anesthesiol Dept, Fac Med, Chiang Mai, Thailand
[7] Prince Songkla Univ, Surg Dept, Fac Med, Hat Yai, Thailand
[8] Navamindradhiraj Univ, Fac Med, Anesthesiol Dept, Vajira Hosp, Bangkok, Thailand
关键词
Acute kidney injury; Risk prediction score; Critically-ill surgical patient; Intensive care unit; ACUTE-RENAL-FAILURE; INTENSIVE-CARE UNITS; THAI-SICU; EPIDEMIOLOGY; DEFINITION; VALIDATION; THERAPY;
D O I
10.1186/s12871-020-01046-2
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
BackgroundThere has been a global increase in the incidence of acute kidney injury (AKI), including among critically-ill surgical patients. AKI prediction score provides an opportunity for early detection of patients who are at risk of AKI; however, most of the AKI prediction scores were derived from cardiothoracic surgery. Therefore, we aimed to develop an AKI prediction score for major non-cardiothoracic surgery patients who were admitted to the intensive care unit (ICU).MethodsThe data of critically-ill patients from non-cardiothoracic operations in the Thai Surgical Intensive Care Unit (THAI-SICU) study were used to develop an AKI prediction score. Independent prognostic factors from regression analysis were included as predictors in the model. The outcome of interest was AKI within 7days after the ICU admission. The AKI diagnosis was made according to the Kidney Disease Improving Global Outcomes (KDIGO)-2012 serum creatinine criteria. Diagnostic function of the model was determined by area under the Receiver Operating Curve (AuROC). Risk scores were categorized into four risk probability levels: low (0-2.5), moderate (3.0-8.5), high (9.0-11.5), and very high (12.0-16.5) risk. Risk of AKI was presented as likelihood ratios of positive (LH+).ResultsA total of 3474 critically-ill surgical patients were included in the model; 333 (9.6%) developed AKI. Using multivariable logistic regression analysis, older age, high Sequential Organ Failure Assessment (SOFA) non-renal score, emergency surgery, large volume of perioperative blood loss, less urine output, and sepsis were identified as independent predictors for AKI. Then AKI prediction score was created from these predictors. The summation of the score was 16.5 and had a discriminative ability for predicting AKI at AuROC=0.839 (95% CI 0.825-0.852). LH+ for AKI were: low risk=0.117 (0.063-0.200); moderate risk=0.927 (0.745-1.148); high risk=5.190 (3.881-6.910); and very high risk=9.892 (6.230-15.695), respectively.ConclusionsThe function of AKI prediction score to predict AKI among critically ill patients who underwent non-cardiothoracic surgery was good. It can aid in early recognition of critically-ill surgical patients who are at risk from ICU admission. The scores could guide decision making for aggressive strategies to prevent AKI during the perioperative period or at ICU admission.Trial registrationTCTR20190408004, registered on April 4, 2019.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Acute kidney injury risk prediction score for critically-ill surgical patients
    Konlawij Trongtrakul
    Jayanton Patumanond
    Suneerat Kongsayreepong
    Sunthiti Morakul
    Tanyong Pipanmekaporn
    Osaree Akaraborworn
    Sujaree Poopipatpab
    [J]. BMC Anesthesiology, 20
  • [2] Risk Stratification for Acute Kidney Injury in Critically-ill Children
    Sidharth Kumar Sethi
    Rupesh Raina
    [J]. Indian Pediatrics, 2019, 56 : 641 - 642
  • [3] Risk Stratification for Acute Kidney Injury in Critically-ill Children
    Sethi, Sidharth Kumar
    Raina, Rupesh
    [J]. INDIAN PEDIATRICS, 2019, 56 (08) : 641 - 642
  • [4] Acute Kidney Injury in Critically-Ill COVID-19 Patients
    Arrestier, Romain
    Gendreau, Segolene
    Mokrani, David
    Bastard, Jean-Philippe
    Fellahi, Soraya
    Bagate, Francois
    Masi, Paul
    D'Humieres, Thomas
    Razazi, Keyvan
    Carteaux, Guillaume
    De Prost, Nicolas
    Audard, Vincent
    Mekontso-Dessap, Armand
    [J]. JOURNAL OF CLINICAL MEDICINE, 2022, 11 (07)
  • [5] A simple risk score for prediction of sepsis associated-acute kidney injury in critically ill patients
    Jiaojiao Zhou
    Yajun Bai
    Xin Wang
    Jia Yang
    Ping Fu
    Dingming Cai
    Lichuan Yang
    [J]. Journal of Nephrology, 2019, 32 : 947 - 956
  • [6] A simple risk score for prediction of sepsis associated-acute kidney injury in critically ill patients
    Zhou, Jiaojiao
    Bai, Yajun
    Wang, Xin
    Yang, Jia
    Fu, Ping
    Cai, Dingming
    Yang, Lichuan
    [J]. JOURNAL OF NEPHROLOGY, 2019, 32 (06) : 947 - 956
  • [7] Fluid accumulation, recognition and staging of acute kidney injury in critically-ill patients
    Etienne Macedo
    Josée Bouchard
    Sharon H Soroko
    Glenn M Chertow
    Jonathan Himmelfarb
    T Alp Ikizler
    Emil P Paganini
    Ravindra L Mehta
    [J]. Critical Care, 14
  • [8] Incidence and Outcome of Early Acute Kidney Injury in Critically-Ill Trauma Patients
    Podoll, Amber S.
    Kozar, Rosemary
    Holcomb, John B.
    Finkel, Kevin W.
    [J]. PLOS ONE, 2013, 8 (10):
  • [9] Acute kidney injury predicts mortality in very elderly critically-ill patients
    Schmidt, Elisa Alba
    De Rosa, Silvia
    Mueller, Jakob
    Huesing, Paul
    Daniels, Rikus
    Theile, Pauline
    Schweingruber, Nils
    Kluge, Stefan
    Huber, Tobias B.
    Roedl, Kevin
    Schmidt-Lauber, Christian
    [J]. EUROPEAN JOURNAL OF INTERNAL MEDICINE, 2024, 127 : 119 - 125
  • [10] Fluid accumulation, recognition and staging of acute kidney injury in critically-ill patients
    Macedo, Etienne
    Bouchard, Josee
    Soroko, Sharon H.
    Chertow, Glenn M.
    Himmelfarb, Jonathan
    Ikizler, T. Alp
    Paganini, Emil P.
    Mehta, Ravindra L.
    [J]. CRITICAL CARE, 2010, 14 (03):