Preoperative serum uric acid predicts incident acute kidney injury following cardiac surgery

Low preoperative serum uric acid is associated with early acute kidney injury after living donor liver transplantation

BACKGROUND

Liver transplantation is treatment option for patients with end-stage liver disease and hepatocellular carcinoma. Renal function deterioration significantly impacts the survival rates of liver recipients, and serum uric acid (SUA) is associated with both acute and chronic renal function disorders. Thus, our study aimed to assess the relationship and predictive value of preoperative SUA level and postoperative acute kidney injury (AKI) in living donor liver transplantation (LDLT).

METHODS

We conducted a prospective observational study on 87 patients undergoing LDLT. Blood samples were collected immediately before LDLT, and renal function status was followed up for 3 consecutive days postoperatively.

RESULTS

Low SUA levels (cutoff value 4.15 mg/dL) were associated with a high risk of early posttransplantation AKI. The area under the curve was 0.73 (sensitivity, 79.2%; specificity, 59.4%). Although not statistically significant, there were no deaths in the non-AKI group but two in the early AKI group secondary to liver graft dysfunction in addition to early AKI within the first month after LDLT.

CONCLUSION

AKI after liver transplantation may lead to a deterioration of patient status and increased mortality rates. We determined low preoperative SUA levels as a possible risk factor for early postoperative AKI.

Classification and Regression Tree Predictive Model for Acute Kidney Injury in Traumatic Brain Injury Patients

Background

Acute kidney injury (AKI) is prevalent in hospitalized patients with traumatic brain injury (TBI), and increases the risk of poor outcomes. We designed this study to develop a visual and convenient decision-tree-based model for predicting AKI in TBI patients.

Methods

A total of 376 patients admitted to the emergency department of the West China Hospital for TBI between January 2015 and June 2019 were included. Demographic information, vital signs on admission, laboratory test results, radiological signs, surgical options, and medications were recorded as variables. AKI was confirmed since the second day after admission, based on the Kidney Disease Improving Global Outcomes criteria. We constructed two predictive models for AKI using least absolute shrinkage and selection operator (LASSO) regression and classification and regression tree (CART), respectively. Receiver operating characteristic (ROC) curves of these two predictive models were drawn, and the area under the ROC curve (AUC) was calculated to compare their predictive accuracy.

Results

The incidence of AKI on the second day after admission was 10.4% among patients with TBI. Lasso regression identified five potent predictive factors for AKI: glucose, serum creatinine, cystatin C, serum uric acid, and fresh frozen plasma transfusions. The CART analysis showed that glucose, serum uric acid, and cystatin C ranked among the top three in terms of the feature importance of the decision tree model. The AUC value of the decision-tree predictive model was 0.892, which was higher than the 0.854 of the LASSO regression model, although the difference was not statistically significant.

Conclusion

The decision tree model is valuable for predicting AKI among patients with TBI. This tree-based flowchart is convenient for physicians to identify patients with TBI who are at high risk of AKI and prompts them to develop suitable therapeutic strategies.

Renal Biomarkers in Cardiovascular Patients with Acute Kidney Injury: A Case Report and Literature Review

Biomarkers have become important tools in the diagnosis and management of cardiorenal syndrome (CRS), a complex condition characterized by dysfunction in both the cardiovascular and renal systems. Biomarkers can help identify the presence and severity of CRS, predict its progression and outcomes, and facilitate personalized treatment options. Several biomarkers, including natriuretic peptides, troponins, and inflammatory markers, have been extensively studied in CRS, and have shown promising results in improving diagnosis and prognosis. In addition, emerging biomarkers, such as kidney injury molecule-1 and neutrophil gelatinase-associated lipocalin, offer potential for early detection and intervention of CRS. However, the use of biomarkers in CRS is still in its infancy, and further research is needed to establish their utility in routine clinical practice. This review highlights the role of biomarkers in the diagnosis, prognosis, and management of CRS, and discusses their potential as valuable clinical tools for personalized medicine in the future.

Postoperative Hyperuricemia-A Risk Factor in Elective Cardiosurgical Patients

Hyperuricemia is a well-known cardiovascular risk factor. The aim of our study was to investigate the connection between postoperative hyperuricemia and poor outcomes after elective cardiac surgery compared to patients without postoperative hyperuricemia. In this retrospective study, a total of 227 patients after elective cardiac surgery were divided into two groups: 42 patients with postoperative hyperuricemia (mean age 65.14 ± 8.9 years) and a second group of 185 patients without it (mean age 62.67 ± 7.45 years). The time spent on mechanical ventilation (hours) and in the intensive care unit (days) were taken as the primary outcome measures while the secondary measure comprised postoperative complications. The preoperative patient characteristics were similar. Most of the patients were men. The EuroSCORE value of assessing the risk was not different between the groups nor the comorbidities. Among the most common comorbidities was hypertension, seen in 66% of all patients (69% in patients with postoperative hyperuricemia and 63.7% in those without it). A group of patients with postoperative hyperuricemia had a prolonged time of treatment in the intensive care unit (p = 0.03), as well as a prolonged duration of mechanical ventilation (p < 0.01) and a significantly higher incidence of the following postoperative complications: circulatory instability and/or low cardiac output syndrome (LCOS) (χ2 = 4486, p < 0.01), renal failure and/or continuous venovenous hemodiafiltration (CVVHDF's) (χ2 = 10,241, p < 0.001), and mortality (χ2 = 5.22, p < 0.01). Compared to patients without postoperative hyperuricemia, elective cardiac patients with postoperative hyperuricemia have prolonged postoperative treatment in intensive care units, extended durations of mechanically assisted ventilation, and a higher incidence of postoperative circulatory instability, renal failure, and death.

Systemic immune-inflammation index may predict the acute kidney injury and prognosis in patients with spontaneous cerebral hemorrhage undergoing craniotomy: a single-center retrospective study

BACKGROUND

The systemic immune-inflammation index (SII) is an emerging prognostic marker of cancer. We aimed to explore the predictive ability of the SII on acute kidney injury (AKI) and prognosis in patients with spontaneous cerebral hemorrhage (SCH) who underwent craniotomy.

METHODS

Patients with SCH who underwent craniotomy between 2014 and 2021 were enrolled in this study. The epidemiology and predictive factors for AKI after SCH were analyzed. The prognostic factors for clinical outcomes in patients with SCH and AKI were further investigated. The prognostic factors were then analyzed using a logistic regression model and a receiver operating characteristic curve.

RESULTS

In total, 305 patients were enrolled in this study. Of these, 129 (42.3%) patients presented with AKI, and 176 (57.7%) patients were unremarkable. The SII (odds ratio [OR], 1.261; 95% confidence interval [CI], 1.036-1.553; P = 0.020) values and serum uric acid levels (OR, 1.004; 95% CI, 1.001-1.007; P = 0.005) were significant predictors of AKI after SCH craniotomy. The SII cutoff value was 1794.43 (area under the curve [AUC], 0.669; 95% CI, 0.608-0.730; P < 0.001; sensitivity, 65.9%; specificity, 65.1%). Of the patients with AKI, 95 and 34 achieved poor and good outcomes, respectively. SII values (OR, 2.667; 95% CI, 1.167-6.095; P = 0.020), systemic inflammation response index values (OR, 1.529; 95% CI, 1.064-2.198; P = 0.022), and Glasgow Coma Scale (GCS) scores on admission (OR, 0.593; 95% CI, 0.437-0.805; P = 0.001) were significant in the multivariate logistic regression analysis. The cutoff SII value was 2053.51 (AUC, 0.886; 95% CI, 0.827-0.946; P < 0.001; sensitivity, 78.9%; specificity, 88.2%).

CONCLUSIONS

The SII may predict AKI in patients with SCH who underwent craniotomy and may also predict the short-term prognosis of these patients.

Risk Factors for Postoperative Acute Kidney Injury in Patients Undergoing Redo Cardiac Surgery Using Cardiopulmonary Bypass

Objective: This paper aimed to investigate the incidence and risk factors of postoperative acute kidney injury (AKI) in adult patients undergoing redo cardiac surgery with cardiopulmonary bypass (CPB), and explore the impact of AKI on early outcomes. Methods: A total of 116 patients undergoing redo cardiac surgery with CPB between November 2017 and May 2021 were included. Patients were divided into two groups, AKI group and non-AKI group, according to the Kidney Disease Improving Global Outcomes criteria. Perioperative variables were retrospectively collected and analyzed. Risk factors for the development of AKI were investigated by univariate and multiple logistic regression models. Clinical outcomes were also compared between the groups. Results: Postoperative AKI occurred in 63 patients (54.3%), among whom renal replacement therapy was required in 12 patients (19.0%). The mechanical ventilation time (AKI: 43.00 (19.00, 72.00) hours; non-AKI: 18.00 (15.00, 20.00) hours; p < 0.001), ICU length of stay (AKI: 4.00 (2.00, 6.00) days; non-AKI: 3.00 (2.00, 4.00) days; p = 0.010), hospital length of stay since operation (AKI: 12.00 (8.00, 18.00) days; non-AKI: 9.00 (7.00, 12.50) days; p = 0.024), dialysis (AKI: 12.00 (19.05%); non-AKI: 0 (0%); p = 0.001), reintubation (AKI: 7.00 (11.11%); non-AKI: 0 (0%); p = 0.035), and hospital mortality (AKI: 8.00 (12.70%); non-AKI: 0 (0%); p = 0.020) were all higher in the AKI group than in the non-AKI group. Multivariate analysis revealed that high aspartate aminotransferase (OR, 1.028, 95% CI, 1.003 to 1.053, p = 0.025), coronary angiogram within 2 weeks before surgery (OR, 3.209, 95% CI, 1.307 to 7.878, p = 0.011) and CPB time (OR, 1.012, 95% CI, 1.005 to 1.019, p = 0.001) were independent risk factors for postoperative AKI. Conclusions: High aspartate aminotransferase, coronary angiogram within 2 weeks before surgery and CPB time seem to be associated with an increased incidence of postoperative AKI in patients with redo cardiac surgery.

Effects of hyperuricaemia, with the superposition of being overweight and hyperlipidaemia, on the incidence of acute kidney injury following cardiac surgery: a retrospective cohort study

OBJECTIVES

Acute kidney injury (AKI) is a common complication of cardiac surgery. This study aimed to explore the effects of hyperuricaemia, being overweight and hyperlipidaemia as risk factors for AKI in patients following cardiac surgery (cardiac surgery-associated acute kidney injury (CSA-AKI)).

DESIGN

Retrospective observational study.

SETTING

University teaching, grade-A tertiary hospital in Shanghai, China.

PARTICIPANTS

Patients who underwent cardiac surgery from July 2015 to December 2015 in Zhongshan Hospital, Fudan University.

MAIN OUTCOME MEASURES

We investigated the effect of hyperuricaemia, in combination with being overweight and hyperlipidaemia, on the risk of CSA-AKI.

RESULTS

A total of 1420 patients were enrolled. The AKI incidence in the highest uric acid group was 44.4%, while that in the lowest uric acid group was 28.5% (p<0.001). Patients in the higher uric acid quartiles were more likely to be overweight and hyperlipidaemic at the same time (p<0.001). Multivariate logistic regression analysis showed that hyperuricaemia was an independent risk factor for AKI (OR=1.237, 95% CI 1.095 to 1.885; p=0.009); being overweight or hyperlipidaemia alone was not an independent risk factor, but the combination of being overweight and hyperlipidaemia was (OR=1.544, 95% CI 1.059 to 2.252; p=0.024). In the final model, the OR value increased to 3.126 when hyperuricaemia was combined with being overweight and hyperlipidaemia, and the Hosmer-Lemeshow test showed that all three models fit well (p=0.433, 0.638 and 0.597, respectively).

CONCLUSIONS

The combination of being overweight and having hyperlipidaemia was an independent risk factor, but being overweight or having hyperlipidaemia alone was not. The combination of hyperuricaemia, being overweight and hyperlipidaemia further increased the risk of CSA-AKI.

Predictive value of vitamin A and E levels in pre-eclampsia and postpartum kidney injury

OBJECTIVE

This research aimed to explore the predictive value of levels of vitamin A and E in pre-eclampsia and postpartum kidney injury.

METHODS

A total of 106 pregnant women with severe pre-eclampsia diagnosed in our hospital from May 2015 to December 2018 were selected as the research subjects. There from, 75 pregnant women with severe pre-eclampsia were enrolled into the severe PE group (SPE) and 31 with acute kidney injury were divided into the severe PE and AKI group (SPE and AKI). Serum vitamin A and E content was determined by high-performance liquid chromatography (HPLC), and the correlation between vitamins A and E and disease was analyzed. The expression levels of kidney injury markers in both groups were detected, and the correlation between markers and vitamin A and E levels was analyzed.

RESULTS

The expression level of vitamins A and E decreased in the pre-eclampsia and postpartum kidney injury, and it was negatively correlated with disease severity. The expression of the two decreased further in the severe pre-eclampsia patients with kidney injury. In addition, the expression of kidney injury markers in the severe pre-eclampsia patients with postpartum kidney injury was higher than that in severe pre-eclampsia patients, and it was negatively correlated with vitamin A and E levels.

CONCLUSION

Vitamins A and E are expressed in low levels in pre-eclampsia and postpartum kidney injury, and the latter has a higher sensitivity and specificity than the former. It is negatively correlated with kidney injury markers KIM-1, NGAL, UA and Scr, which can be used as a physical and chemical indexes for clinical prediction.

Development and validation of a model for predicting acute kidney injury after cardiac surgery in patients of advanced age

Objective

To develop a clinical model for predicting postoperative acute kidney injury (AKI) in patients of advanced age undergoing cardiac surgery.

Methods

A total of 848 patients (aged ≥ 60 years) undergoing cardiac surgery were consecutively enrolled. Among them, 597 were randomly selected for the development set and the remaining 251 for the validation set. AKI was the primary outcome. To develop a model for predicting AKI, visualized as a nomogram, we performed logistic regression with variables selected by Lasso regression analysis. The discrimination, calibration, and clinical usefulness of the new model were assessed and compared with those of Cleveland Clinic score and Simplified Renal Index (SRI) score in the validation set.

Results

The incidence of AKI was 61.8% in the development set. The new model included seven variables including preoperative serum creatinine, hypertension, preoperative uric acid, New York Heart Association classification ≥ 3, cardiopulmonary bypass time > 120 min, intraoperative red blood cell transfusion, and postoperative prolonged mechanical ventilation. In the validation set, the areas under the receiver operating characteristic curves for assessing discrimination of the new model, Cleveland Clinic score, and SRI score were 0.801, 0.670, and 0.627, respectively. Compared with the other two scores, the new model presented excellent calibration according to the calibration curves. Decision curve analysis presented the new model was more clinically useful than the other two scores.

Conclusions

We developed and validated a new model for predicting AKI after cardiac surgery in patients of advanced age, which may help clinicians assess patients' risk for AKI.

Hyperuricaemia and gout in cardiovascular, metabolic and kidney disease

During the last century, there has been an increasing prevalence of hyperuricaemia noted in many populations. While uric acid is usually discussed in the context of gout, hyperuricaemia is also associated with hypertension, chronic kidney disease, hypertriglyceridaemia, obesity, atherosclerotic heart disease, metabolic syndrome, and type 2 diabetes. Here we review the connection between hyperuricaemia and cardiovascular, kidney and metabolic diseases. Contrary to the popular view that uric acid is an inert metabolite of purine metabolism, recent studies suggest serum uric acid may have a variety of pro-inflammatory, pro-oxidative and vasoconstrictive actions that may contribute to cardiometabolic diseases. Hyperuricaemia is a predictive factor for the development of hypertension, metabolic syndrome, type 2 diabetes, coronary artery disease, left ventricular hypertrophy, atrial fibrillation, myocardial infarction, stroke, heart failure and chronic kidney disease. Treatment with uric acid-lowering therapies has also been found to improve outcomes in patients with hypertension and kidney disease, in some but not all studies. In conclusion, uric acid is emerging as a potentially treatable risk factor for cardiometabolic diseases, and more clinical trials investigating the potential benefit of lowering serum uric acid are recommended in individuals with hyperuricaemia with and without deposition and concomitant hypertension, metabolic syndrome or chronic kidney disease.

The Predictive Value of Serum Uric Acid on Acute Kidney Injury following Traumatic Brain Injury

Backgrounds

Acute kidney injury (AKI) is a prevalent nonneurological complication in patients with traumatic brain injury (TBI). We designed this study to explore the association between serum uric acid (SUA) level and the occurrence of AKI following TBI.

Methods

This is a retrospective single-center study. A total of 479 patients admitted with TBI were included in this study. We utilized SUA and other risk factors for AKI to construct a predictive model by performing multivariate logistic regression. 374 patients and 105 patients were, respectively, divided into a training set and validation set. The predictive value of the single SUA and constructed model was evaluated by drawing a receiver operating characteristic (ROC) curve. AKI was diagnosed according to the KIDGO criteria.

Results

79 (21.12%) patients were diagnosed with AKI in the training cohort. The patients in the AKI group are older than those in the non-AKI group (p = 0.01). And the Glasgow Coma Scale (GCS) of the AKI group was lower than that of the non-AKI group (p < 0.001). In a multivariate logistic regression analysis, we found that heart rate (p = 0.041), shock (p = 0.018), serum creatinine (p < 0.001), and serum uric acid (SUA) (p < 0.001) were significant risk factors for AKI. Bivariate correlation analyses showed that serum creatinine was moderately positively correlated with SUA (r = 0.523, p < 0.001). Finally, the area under the receiver operating characteristic curve (AUC) of SUA for predicting AKI in the training set and validation set was 0.850 (0.805-0.895) and 0.869 (0.801-0.938), respectively.

Conclusions

SUA is an effective risk factor for AKI following TBI. Combining SUA with serum creatinine could more accurately identify TBI patients with high risk of developing AKI.

Serum alpha 1-antitrypsin predicts severe acute kidney injury after cardiac surgery

Background

Human alpha 1-antitrypsin (A1AT) is involved in the pathophysiological process underlying ischemic acute kidney injury (AKI). To test the hypothesis that serum A1AT (sA1AT) is a predictor for severe AKI after cardiopulmonary bypass (CPB), we conducted a prospective cohort study in 201 patients undergoing cardiac surgery.

Methods

We collected blood and urine samples, and analyzed the sA1AT and other injury biomarkers during the perioperative period. Severe AKI is defined as Kidney Disease Improving Global Outcomes (KDIGO) stage 2 or 3, and overall AKI is defined as KDIGO stage 1, 2, or 3.

Results

Ninety-one (45.3%) patients developed overall AKI, and 22 (10.9%) among them developed severe AKI after operation. sA1AT level spiked 2 hours after surgery in patients who subsequently developed severe AKI, while serum creatinine peaked 12 hours after operation. Higher postoperative sA1AT independently correlated to the development of severe AKI [OR, 1.54 (1.17-2.03); P=0.002]. The highest quartile of postoperative sA1AT level was associated with 6-fold higher hazards of severe AKI compared to the lowest quartile. Higher sA1AT levels were correlated with longer stays in the intensive care unit and the hospital. For predicting severe AKI, the AUC of sA1AT 2 hours after CPB reached 0.814. After combining with urine T cell immunoglobulin mucin-1 and clinical model, the AUC improved to 0.923.

Conclusions

In summary, sA1AT is a valuable predictor of severe AKI development and prolonged ICU and hospital stays in patients after cardiac surgery.

Biomarkers of Acute Kidney Injury after Cardiac Surgery: A Narrative Review

Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major and serious complication in patients undergoing cardiac surgery and is independently associated with perioperative mortality and mortality. Therapeutic intervention aiming at reversing kidney dysfunction seems disappointing across multiple settings. Consequently, attention has shifted from treatment to prevention and early detection. The Kidney Disease: Improving Global Outcomes (KDIGO) guidelines have unified diagnostic standards mainly based on the serum creatinine (Scr) level or urine output, but neither marker is kidney specific. Efforts have been made to identify novel biomarkers with high sensitivity and specificity. The diagnostic capabilities of neutrophil gelatinase-associated lipocalin (NGAL) and G1 cell cycle arrest biomarker as biomarkers have been confirmed in a large number of clinical trials. The utility of biomarkers of cardiac function and inflammation has been validated in clinical studies. Aiming to offer valuable information for further research, we summarize the progress in defining current markers relevant to CSA-AKI in the last three years.

Uric Acid and Acute Kidney Injury in the Critically Ill

Rationale & Objective

Uric acid is excreted by the kidney and accumulates in acute kidney injury (AKI). Whether higher plasma uric acid level predisposes to AKI or its complications is not known.

Study Design

Prospective observational cohort study.

Setting & Participants

2 independent cohorts of critically ill patients: (1) 208 patients without AKI admitted to the intensive care unit (ICU) at Brigham & Women's Hospital between October 2008 and December 2016; and (2) 250 participants with AKI requiring renal replacement therapy (RRT) who had not yet initiated RRT enrolled in the Acute Renal Failure Trial Network (ATN) Study.

Exposure

Plasma uric acid level upon ICU admission and before RRT initiation in the ICU and ATN Study cohorts, respectively.

Outcomes

Incident AKI and 60-day mortality in the ICU and ATN Study cohorts, respectively.

Analytical Approach

Logistic regression models were used to test the association of plasma uric acid level with incident AKI and 60-day mortality.

Results

In the ICU cohort, median plasma uric acid level was 4.7 (interquartile range [IQR], 3.6-6.4) mg/dL, and 40 patients (19.2%) developed AKI. Higher plasma uric acid levels associated with incident AKI, but this association was confounded by serum creatinine level and was not significant after multivariable adjustment (adjusted OR per doubling of uric acid, 1.50; 95% CI, 0.80-2.81). In the ATN Study cohort, median plasma uric acid level was 11.1 (IQR, 8.6-14.2) mg/dL, and 125 participants (50.0%) died within 60 days. There was no statistically significant association between plasma uric acid levels and 60-day mortality in either unadjusted models or after multivariable adjustment for demographic, severity-of-illness, and kidney-specific covariates (adjusted OR per doubling of uric acid, 1.15; 95% CI, 0.71-1.86).

Limitations

Heterogeneity of ICU patients.

Conclusions

Plasma uric acid levels upon ICU admission or before RRT initiation are not independently associated with adverse clinical outcomes in critically ill patients.