Does Aspartate Aminotransferase to Alanine Aminotransferase Ratio Predict Acute Kidney Injury After Cardiac Surgery?

Background: Aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio (AST/ALT) frequently is used in the diagnosis and prognosis of liver diseases, however it is also used in the diagnosis and prognosis of many other diseases, such as myocardial infarction, acute ischemic stroke, and peripheral artery disease. Acute kidney injury (AKI) is one of the most important complications after cardiac surgery and is one of the main causes of morbidity and mortality. The purpose of the study was to analyze the relationship between AST to ALT and AKI after isolated coronary artery bypass graft surgery (CABG). Methods: We retrospectively reviewed the prospectively collected data of 253 adult patients, who underwent isolated CABG surgery with normal renal function (baseline serum creatinine value <1.4 mg/dL). Preoperative (T0) and postoperative day 1 and day 3 (T1 and T2) serum AST and ALT levels were analyzed, and AST/ALT was calculated. A preoperative AST/ALT of 1.22 was found to be the best cutoff point for predicting postoperative AKI. Kidney injury was interpreted, according to RIFLE classification. The effect of AST to ALT ratio on AKI after CABG was determined using logistic regression analysis, and the results were expressed as odds ratio (OR) with a 95% confidence interval (CI). A P value < .05 was considered statistically significant. Results: Postoperative AKI occurred in 40 patients (15.8%). On logistic regression analysis, higher AST/ALT both preoperatively and postoperatively were associated with an increased incidence of postoperative AKI (T0: OR, 3.983; 95% CI, 1.940-8.180, P < .001, T1: OR, 2.760; 95% CI, 1.381-5.515, P = .004, T2: OR, 2.515; 95% CI, 1.195-5.294, P = .015). Conclusion: Preoperative and postoperative elevated AST to ALT ratio seems to be associated with an increased incidence of AKI after elective isolated CABG surgery.

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The Influence of Metabolic Syndrome on Acute Kidney Injury Occurrence after Coronary Artery Bypass Grafting

The Heart Surgery Forum ◽

10.1532/hsf.1400 ◽

2016 ◽

Vol 19 (3) ◽

pp. 099 ◽

Cited By ~ 1

Author(s):

Atike Tekeli Kunt ◽

Hakan Parlar ◽

Orhan Findik ◽

Cagri Duzyol ◽

Ozgur Baris ◽

...

Keyword(s):

Metabolic Syndrome ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Cardiac Surgery ◽

Artery Bypass ◽

Kidney Injury ◽

Bypass Grafting ◽

Group I ◽

Postoperative Aki

Background: Metabolic syndrome (MetS) is defined as a cluster of systemic abnormalities: hyperglycemia, dyslipidemia, abdominal obesity, and hypertension. Acute kidney injury (AKI) is one of the devastating complications after cardiac surgery. Age, DM, preexisting renal dysfunction, hypertension, impaired left ventricular function, and severe arteriosclerosis of the aorta are the major risk factors for the development of AKI. The purpose of the current study was to analyze the influence of MetS on AKI occurring after coronary artery bypass grafting (CABG).Methods: We retrospectively reviewed the prospectively collected data of 500 adult patients who underwent isolated CABG surgery with normal renal function (baseline serum creatinine value <1.4 mg/dL) from January 2011 to January 2015. The patients were divided into two groups either having the diagnosis of MetS (Group I) or not (Group II). MetS was diagnosed based on International Diabetes Federation definition. Kidney injury was interpreted according to RIFLE classification. The effect of MetS on AKI after CABG was determined using logistic regression analysis and the results were expressed as odds ratio (OR) with a 95% confidence interval (CI). A P value <.05 was considered statistically significant.Results: Metabolic syndrome was diagnosed in 16.4% of all patients. Postoperative AKI occurred in 26 patients (31.7%) in Group I whereas there were 53 patients (12.7%) in Group II. On logistic regression analysis, the presence of MetS was shown to be associated with increased incidence of postoperative AKI (OR, 3.197; 95% CI, 1.850-5.526; P = .000).Conclusion: The presence of MetS seems to be associated with increased incidence of AKI after cardiac surgery. MetS is a modifiable issue; if its components are well controlled its dreadful effects after cardiac surgery might be controlled as well.

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O63: POST-OPERATIVE ACUTE KIDNEY INJURY IN PATIENTS UNDERGOING MAJOR GASTROINTESTINAL SURGERY— AN OBSERVATIONAL COHORT STUDY AND EXTERNAL VALIDATION OF A PROGNOSTIC MODEL

British Journal of Surgery ◽

10.1093/bjs/znab117.063 ◽

2021 ◽

Vol 108 (Supplement_1) ◽

Author(s):

Keyword(s):

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Cox Regression ◽

Gastrointestinal Surgery ◽

Kidney Injury ◽

One Year ◽

Postoperative Aki

Abstract Introduction Acute kidney injury (AKI) is well-recognised as a significant cause of morbidity and mortality. Due to limited evidence on the longer-term implications, this study aimed to explore the association of postoperative AKI one-year survival and renal function in patients undergoing major gastrointestinal and liver surgery. Method Patients undergoing major gastrointestinal surgery in the prospective Outcomes of Kidney Injury after Surgery (OAKS) study across UK and Ireland were followed up at one-year postoperatively. The primary outcome was survival at 1-year and secondary outcomes included the composite “Major Adverse Kidney Events” outcome at day 365 (MAKE-365), with respective multivariable Cox-regression and logistic regression analysis performed. Result Of 62.2% of OAKS patients (n=3,575/5,745) with 1-year follow-up, there were no significant differences compared to those without follow-up. Among the follow-up cohort, 8.0% (n=269) patients died. On univariate analysis, patients experiencing 7-day postoperative AKI had a significantly higher hazard of death between 30 to 365 days postoperatively (HR: 2.10, 95% CI: 1.50-2.94, p<0.001) compared to patients who did not. This persisted on multivariable Cox-regression (HR: 1.67, 95% CI: 1.17-2.40, p=0.005). Furthermore, 9.1% (n=305) patients met the MAKE-365 endpoint. Multilevel logistic regression analysis demonstrated that the MAKE-365 endpoint was independently associated with both stage 1 (OR: 1.78, 95% CI: 1.22-2.61, p=0.003) and stage 2-3 7-day postoperative AKI (OR: 6.13, 95% CI: 3.97-9.45, p<0.001). Conclusion Post-operative AKI is associated with significantly higher rate of 1-year mortality and MAKE-365 endpoints. Improved monitoring of these patients may be warranted to identify and facilitate potential avenues for intervention Take-home message Post-operative AKI is associated with significantly higher rate of 1-year mortality. Hence, early detection and improved monitoring of patients with AKI with improve long-term outcomes of these patients.

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Prediction of Acute Kidney Injury after Liver Transplantation: Machine Learning Approaches vs. Logistic Regression Model

Journal of Clinical Medicine ◽

10.3390/jcm7110428 ◽

2018 ◽

Vol 7 (11) ◽

pp. 428 ◽

Cited By ~ 31

Author(s):

Hyung-Chul Lee ◽

Soo Yoon ◽

Seong-Mi Yang ◽

Won Kim ◽

Ho-Geol Ryu ◽

...

Keyword(s):

Machine Learning ◽

Liver Transplantation ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Kidney Injury ◽

Gradient Boosting ◽

Learning Approaches ◽

Gradient Boosting Machine

Acute kidney injury (AKI) after liver transplantation has been reported to be associated with increased mortality. Recently, machine learning approaches were reported to have better predictive ability than the classic statistical analysis. We compared the performance of machine learning approaches with that of logistic regression analysis to predict AKI after liver transplantation. We reviewed 1211 patients and preoperative and intraoperative anesthesia and surgery-related variables were obtained. The primary outcome was postoperative AKI defined by acute kidney injury network criteria. The following machine learning techniques were used: decision tree, random forest, gradient boosting machine, support vector machine, naïve Bayes, multilayer perceptron, and deep belief networks. These techniques were compared with logistic regression analysis regarding the area under the receiver-operating characteristic curve (AUROC). AKI developed in 365 patients (30.1%). The performance in terms of AUROC was best in gradient boosting machine among all analyses to predict AKI of all stages (0.90, 95% confidence interval [CI] 0.86–0.93) or stage 2 or 3 AKI. The AUROC of logistic regression analysis was 0.61 (95% CI 0.56–0.66). Decision tree and random forest techniques showed moderate performance (AUROC 0.86 and 0.85, respectively). The AUROC of support the vector machine, naïve Bayes, neural network, and deep belief network was smaller than that of the other models. In our comparison of seven machine learning approaches with logistic regression analysis, the gradient boosting machine showed the best performance with the highest AUROC. An internet-based risk estimator was developed based on our model of gradient boosting. However, prospective studies are required to validate our results.

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How Reliable Is Automated Urinalysis in Acute Kidney Injury?

Laboratory Medicine ◽

10.1093/labmed/lmaa069 ◽

2020 ◽

Author(s):

Vani Chandrashekar ◽

Anil Tarigopula ◽

Vikram Prabhakar

Keyword(s):

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Epithelial Cells ◽

Logistic Regression Analysis ◽

Blood Cells ◽

White Blood Cells ◽

Kidney Injury ◽

Tubular Epithelial Cells ◽

Spearman Test

Abstract Objective Examination of urine sediment is crucial in acute kidney injury (AKI). In such renal injury, tubular epithelial cells, epithelial cell casts, and dysmorphic red cells may provide clues to etiology. The aim of this study was to compare automated urinalysis findings with manual microscopic analysis in AKI. Methods Samples from patients diagnosed with AKI and control patients were included in the study. Red blood cells, white blood cells, renal tubular epithelial cells/small round cells, casts, and pathologic (path) cast counts obtained microscopically and by a UF1000i cytometer were compared by Spearman test. Logistic regression analysis was used to assess the ability to predict AKI from parameters obtained from the UF1000i. Results There was poor correlation between manual and automated analysis in AKI. None of the parameters could predict AKI using logistic regression analysis. However, the increment in the automated path cast count increased the odds of AKI 93 times. Conclusion Automated urinalysis parameters are poor predictors of AKI, and there is no agreement with manual microscopy.

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Impaired T Lymphocyte Subsets Early Predict Acute Kidney Injury in Sepsis Patients

10.21203/rs.3.rs-612917/v1 ◽

2021 ◽

Author(s):

Guanglan Li ◽

Yu Zhang ◽

Ganyuan He ◽

Wenke Hao ◽

Wenxue Hu

Keyword(s):

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

T Lymphocyte ◽

Logistic Regression Analysis ◽

Lymphocyte Subsets ◽

Kidney Injury ◽

High Morbidity ◽

T Helper ◽

T Lymphocyte Subsets

Abstract Objective: Acute kidney injury (AKI) is a frequent complication of sepsis patients and is associated with high morbidity and mortality. Early recognition of sepsis-associated AKI (SA-AKI) is crucial to provide supportive treatment and improve prognosis. Thus, the objective is to analyze the early discriminative predictive information regarding T lymphocyte subsets of SA-AKI.Methods: We evaluated the relationships of T lymphocyte subsets and clinical parameters of sepsis patients, and assessed their potential roles in SA-AKI diagnosis. The following T lymphocyte subsets were studied: total T lymphocyte (CD3+), helper T lymphocyte (T helper, CD3+CD4+), cytotoxic T lymphocyte (CTL, CD3+CD8+), totally activated T lymphocyte (CD3+HLADR+), early activated T lymphocyte (CD4+CD69+, CD8+CD69+), regulatory T lymphocyte (Treg, CD4+CD25+, CD8+CD25+).Results: A total of 171 patients with sepsis were enrolled. The incidence of AKI was 80.1%. The percentages of total T lymphocyte, CTL, and totally activated T lymphocyte of SA-AKI patients were lower than those of sepsis patients without AKI (61.95±19.65 % vs 68.80±18.57 %, 19.95±17.22 % vs 26.48±18.31 %, 19.00±14.21 % vs 30.88±28.86 %, respectively, P<0.05). There were no significant differences in the percentages of T helper, early activated T lymphocyte, and Tregs between SA-AKI group and non-SA-AKI group. Univariate logistic regression analysis showed that percentages of total T lymphocyte, CTL, and totally activated T lymphocyte were protective factors for SA-AKI. Multivariate logistic regression analysis revealed that percentage of totally activated T lymphocyte had a negative association with SA-AKI independently (OR: 0.952, 95% CI: 0.926-0.978, P=0.000). Moreover, ROC analysis showed that total T lymphocyte, CTL, and totally activated T lymphocyte had discriminatory abilities, with areas under the curve (AUC) value of 0.638, 0.615, and 0.661, respectively (P<0.05). Conclusions: Impaired total T lymphocyte, CTL, and totally activated T lymphocyte could contribute to early diagnosis for SA-AKI.

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Risk factors for acute kidney injury and mortality in high risk patients undergoing cardiac surgery

PLoS ONE ◽

10.1371/journal.pone.0252209 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0252209

Author(s):

Giuseppe Filiberto Serraino ◽

Michele Provenzano ◽

Federica Jiritano ◽

Ashour Michael ◽

Nicola Ielapi ◽

...

Keyword(s):

Risk Factors ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Cardiac Surgery ◽

Blood Glucose ◽

Kidney Injury ◽

Glucose Levels ◽

Blood Glucose Levels ◽

Risk Patients

Background Acute Kidney Injury (AKI) represents a clinical condition with poor prognosis. The incidence of AKI in hospitalized patients was about 22–57%. Patients undergoing cardiac surgery (CS) are particularly exposed to AKI because of the related oxidative stress, inflammation and ischemia-reperfusion damage. Hence, the risk profile of patients undergoing CS who develop AKI and who are consequently at increased mortality risk deserves further investigation. Methods We designed a retrospective study examining consecutive patients undergoing any type of open-heart surgery from January to December 2018. Patients with a history of AKI were excluded. AKI was diagnosed according to KDIGO criteria. Univariate associations between clinical variables and AKI were tested using logistic regression analysis. Variable thresholds maximizing the association with AKI were measured with the Youden index. Multivariable logistic regression analysis was performed to assess predictors of AKI through backward selection. Mortality risk factors were assessed through the Cox proportional hazard model. Results We studied 158 patients (mean age 51.2±9.7 years) of which 74.7% were males. Types of procedures performed were: isolated coronary artery bypass (CABG, 50.6%), valve (28.5%), aortic (3.2%) and combined (17.7%) surgery. Overall, incidence of AKI was 34.2%. At multivariable analysis, young age (p = 0.016), low blood glucose levels (p = 0.028), estimated Glomerular Filtration Rate (p = 0.007), pH (p = 0.008), type of intervention (p = 0.031), prolonged extracorporeal circulation (ECC, p = 0.028) and cross-clamp (p = 0.021) times were associated with AKI. The threshold for detecting AKI were 91 and 51 minutes for ECC and cross-clamp times, respectively. At survival analysis, the presence of AKI, prolonged ECC and cross-clamp times, and low blood glucose levels forecasted mortality. Conclusions AKI is common among CS patients and associates with shortened life-expectancy. Several pre-operative and intra-operative predictors are associated with AKI and future mortality. Future studies, aiming at improving prognosis in high-risk patients, by a stricter control of these factors, are awaited.

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Prognostic value of suPAR and hsCRP on acute kidney injury after cardiac surgery

BMC Nephrology ◽

10.1186/s12882-021-02322-0 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Sebastian Roed Rasmussen ◽

Rikke Vibeke Nielsen ◽

Rasmus Møgelvang ◽

Sisse Rye Ostrowski ◽

Hanne Berg Ravn

Keyword(s):

Acute Kidney Injury ◽

Logistic Regression ◽

Cardiac Surgery ◽

Kidney Injury ◽

High Sensitivity ◽

Reactive Protein ◽

Type Plasminogen Activator ◽

Urokinase Type Plasminogen Activator ◽

Adjusted Logistic Regression ◽

Postoperative Aki

Abstract Background Acute kidney injury (AKI) represents a serious complication following cardiac surgery. Adverse outcome after cardiac surgery has been observed in the presence of elevated levels of soluble urokinase-type plasminogen activator receptor (suPAR) and high-sensitivity C-Reactive Protein (hsCRP). The aim of study was (i) to investigate the relationship between preoperative elevated levels of suPAR and hsCRP and postoperative AKI in unselected cardiac surgery patients and (ii) to assess whether the concentration of the biomarkers reflected severity of AKI. Methods In a retrospective observational study, biobank blood plasma samples (n = 924) from patients admitted for elective on-pump cardiac surgery were analysed for suPAR and hsCRP levels. The relation between suPAR and hsCRP-values and AKI (any stage), defined by the KDIGO (Kidney Disease: Improving Global Outcomes) criteria, was assessed using adjusted logistic regression. Further, the association between biomarkers and severity (KDIGO 1, KDIGO 2–3 and renal replacement therapy (RRT)) was assessed using adjusted logistic regression. Results Postoperative AKI (any stage) was observed in 327 patients (35.4 %). A doubling of preoperative suPAR corresponded to an adjusted odds ratio (OR) for postoperative AKI (any stage) of 1.62 (95 % CI 1.26–2.09, p < 0.001). Furthermore, a doubling of suPAR had an adjusted OR of 1.50 (95 % CI 1.16–1.93, p = 0.002), 2.44 (95 % CI 1.56–3.82, p < 0.001) and 1.92 (95 % CI 1.15–3.23, p = 0.002), for KDIGO 1, KDIGO 2–3 and need for RRT, respectively. No significant association was found between elevated levels of hsCRP and any degree of AKI. Conclusions Increasing levels of suPAR, but not hsCRP, were associated with development and severity of AKI following on-pump cardiac surgery.

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Elevated De Ritis Ratio as a Predictor for Acute Kidney Injury after Radical Retropubic Prostatectomy

Journal of Personalized Medicine ◽

10.3390/jpm11090836 ◽

2021 ◽

Vol 11 (9) ◽

pp. 836

Author(s):

Jun-Young Park ◽

Jihion Yu ◽

Jun Hyuk Hong ◽

Bumjin Lim ◽

Youngdo Kim ◽

...

Keyword(s):

Risk Factors ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Roc Curve ◽

Kidney Injury ◽

Radical Retropubic Prostatectomy ◽

Multivariable Logistic Regression Analysis ◽

Retropubic Prostatectomy

Acute kidney injury (AKI) is related to mortality and morbidity. The De Ritis ratio, calculated by dividing the aspartate aminotransferase by the alanine aminotransferase, is used as a prognostic indicator. We evaluated risk factors for AKI after radical retropubic prostatectomy (RRP). This retrospective study included patients who performed RRP. Multivariable logistic regression analysis and a receiver operating characteristic (ROC) curve analysis were conducted. Other postoperative outcomes were also evaluated. Among the 1415 patients, 77 (5.4%) had AKI postoperatively. The multivariable logistic regression analysis showed that estimated glomerular filtration rate, albumin level, and the De Ritis ratio at postoperative day 1 were risk factors for AKI. The area under the ROC curve of the De Ritis ratio at postoperative day 1 was 0.801 (cutoff = 1.2). Multivariable-adjusted analysis revealed that the De Ritis ratio at ≥1.2 was significantly related to AKI (odds ratio = 8.637, p < 0.001). Postoperative AKI was associated with longer hospitalization duration (11 ± 5 days vs. 10 ± 4 days, p = 0.002). These results collectively show that an elevated De Ritis ratio at postoperative day 1 is associated with AKI after RRP in patients with prostate cancer.

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Preoperative hypoalbuminemia was associated with acute kidney injury in high-risk patients following non-cardiac surgery: a retrospective cohort study

10.21203/rs.2.9275/v2 ◽

2019 ◽

Author(s):

Nan Li ◽

Hong Qiao ◽

Jing-Fei Guo ◽

Hong-Yun Yang ◽

Xue-Ying Li ◽

...

Keyword(s):

Acute Kidney Injury ◽

Logistic Regression ◽

Cardiac Surgery ◽

Serum Albumin ◽

Multivariate Logistic Regression Analysis ◽

Kidney Injury ◽

Albumin Concentration ◽

Multivariate Logistic Regression ◽

Preoperative Serum ◽

Postoperative Aki

Abstract Background: Acute kidney injury (AKI) is a common complication following non-cardiac surgery with adverse short- and long- term morbidity and mortality. Evidence shows that hypoalbuminemia is associated with increased AKI risk in patients with infectious diseases and cancer and following cardiac surgery and transplant surgery. However, little evidence is available on non-cardiac surgery population. Thus, we investigated the association between preoperative hypoalbuminemia and AKI following non-cardiac surgery. Methods: We retrospectively assessed perioperative risk factors and preoperative serum albumin concentration in 729 consecutive adult patients who underwent non-cardiac surgery from July 1, 2017, to June 30, 2018. Each patient was categorized according to maximal Kidney Disease Improving Global Outcomes criteria based on creatinine changes and urine output within the first week after surgery. Multivariate Logistic regression models were used to analyze the association between preoperative hypoalbuminemia and postoperative AKI. Results: Of 729 patients, 188 (25.8%) developed AKI. AKI incidence was higher in patients with preoperative serum albumin <37.5 g/L than in those with preoperative serum albumin ≥37.5 g/L [35.9% (98/273) vs. 19.7% (90/456), P<0.001]. Multivariate logistic regression analysis showed that preoperative serum albumin <37.5 g/L (odds ratio 1.892; 95% confidence interval 1.238-2.891; P=0.003) was independently associated with postoperative AKI. Patients with preoperative serum albumin <37.5 g/L tended to have a higher but not significant ratio in AKI stage 2 (2.6% vs 1.1%, P=0.144) and much higher ratio in AKI stage 3 (4.8% vs 0.7%, P<0.001) than those with preoperative serum albumin ≥37.5 g/L. AKI patients had a higher in-hospital mortality rate [6.9% (13/188) vs. 0.2% (1/541), P<0.001]. Kaplan-Meier analysis revealed that the cumulative survival rate decreased with increasing AKI severity (P<0.001). Postoperative AKI was also associated with other worse outcomes, such as prolonged mechanical ventilation [53.4 (33.0, 73.8) vs 14.7 (11.1, 18.3) hours, P<0.001], intensive care unit stay [4.0 (3.1, 4.9) vs 2.0 (1.8, 2.3) days, P<0.001], postoperative hospital stay [17.8 (14.8, 20.9) vs 12.3 (11.3, 13.3) days, P<0.001], and higher total cost [13,453 (8,538, 20,228) vs 11,306 (6,277, 16,400) dollars, P<0.001]. Conclusions: Preoperative hypoalbuminemia was independently associated with AKI after non-cardiac surgery, and postoperative AKI was associated with poor outcomes.

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Perioperative ABO Blood Group Isoagglutinin Titer and the Risk of Acute Kidney Injury after ABO-Incompatible Living Donor Liver Transplantation

Journal of Clinical Medicine ◽

10.3390/jcm10081679 ◽

2021 ◽

Vol 10 (8) ◽

pp. 1679

Author(s):

Hyeyeon Cho ◽

Jinyoung Bae ◽

Hyun-Kyu Yoon ◽

Ho-Jin Lee ◽

Seong-Mi Yang ◽

...

Keyword(s):

Liver Transplantation ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Confidence Interval ◽

Odds Ratio ◽

Kidney Injury ◽

Multivariable Logistic Regression Analysis ◽

Ig G ◽

Postoperative Aki

For ABO-incompatible liver transplantation (ABO-i LT), therapeutic plasma exchange (TPE) is performed preoperatively to reduce the isoagglutinin titer of anti-ABO blood type antibodies. We evaluated whether perioperative high isoagglutinin titer is associated with postoperative risk of acute kidney injury (AKI). In 130 cases of ABO-i LT, we collected immunoglobulin (Ig) G and Ig M isoagglutinin titers of baseline, pre-LT, and postoperative peak values. These values were compared between the patients with and without postoperative AKI. Multivariable logistic regression analysis was used to evaluate the association between perioperative isoagglutinin titers and postoperative AKI. Clinical and graft-related outcomes were compared between high and low baseline and postoperative peak isoagglutinin groups. The incidence of AKI was 42.3%. Preoperative baseline and postoperative peak isoagglutinin titers of both Ig M and Ig G were significantly higher in the patients with AKI than those without AKI. Multivariable logistic regression analysis showed that preoperative baseline and postoperative peak Ig M isoagglutinin titers were significantly associated with the risk of AKI (baseline: odds ratio 1.06, 95% confidence interval 1.02 to 1.09; postoperative peak: odds ratio 1.08, 95% confidence interval 1.04 to 1.13). Cubic spline function curves show a positive relationship between the baseline and postoperative peak isoagglutinin titers and the risk of AKI. Clinical outcomes other than AKI were not significantly different according to the baseline and postoperative peak isoagglutinin titers. Preoperative high initial and postoperative peak Ig M isoagglutinin titers were significantly associated with the development of AKI. As the causal relationship between high isoagglutinin titers and risk of AKI is unclear, the high baseline and postoperative isoagglutinin titers could be used simply as a warning sign for the risk of AKI after liver transplantation.

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