The Association of Serum Lactate Level with the Occurrence of Contrast-Induced Acute Kidney Injury and Long-Term Prognosis in Patients Undergoing Emergency Percutaneous Coronary Intervention

Predicting pre- and post-operative acute kidney injury in elderly patients with coronary artery disease

Background

Limited evidence exists regarding the clinical baseline characteristics at admission for acute kidney injury (AKI) before and after interventional cardiac procedures (ICP) in elderly patients with coronary artery disease (CAD).

Methods

A total of 488 elderly patients were enrolled in this retrospective single-center study conducted from January 2019 to July 2022, and a classification and regression tree (CART) analysis was performed to identify the high-risk population.

Results

The AKI incidence was 21.1 % (103/488) in this study, with 27 and 76 individuals developing AKI before and after ICP, respectively. CART analysis revealed that exposure to nephrotoxic drugs and diuretics had the strongest predictive capacities for identifying patients at risk of developing pre-ICP AKI, with the incidence among these high-risk patients ranging from 6.5 % to 13.8 %. Meanwhile, the optimum discriminators for identifying those at high risk of post-ICP AKI were the administration of diuretics, D-value ≤ -860 mL, age >73 years, and administration of nephrotoxic drugs, and the latter model predicted that the AKI incidence among high-risk patients was between 50.0 % and 60.0 %.

Conclusions

Elderly patients with CAD exhibited an elevated incidence of AKI. CART models suggested that exposure to nephrotoxic drugs and diuretics, D-value, and age were significantly associated with AKI in the elderly with CAD. Importantly, these baseline characteristics at admission could be utilized to identify elderly patients at high risk of pre- and post-ICP AKI.

Association of Postoperative Serum Lactate Levels with Acute Kidney Injury in Mexican Patients Undergoing Cardiac Surgery

Acute kidney injury (AKI) is a highly prevalent and a critical complication of cardiac surgery (CS). Serum lactate (sLac) levels have consistently shown an association with morbimortality after CS. We performed a cross-sectional study including 264 adult patients that had a cardiac surgery between January and December 2020. Logistic regression analysis was performed to determine factors associated with AKI development. We measured the postoperative levels of sLac for all participants immediately after CS (T0) and at 4 h (T4) after the surgical intervention. A linear regression model was used to identify the factors influencing both sLac metrics. We identified four risk predictors of AKI; one was preoperative (atrial fibrillation), one intraoperative (cardiopulmonary bypass time), and two were postoperative (length of hospital stay and postoperative sLac). T0 and T4 sLac levels were higher among CS-AKI patients than in Non-CS-AKI patients. Postoperative sLac levels were significant independent predictors of CSA-AKI, and sLac levels are influenced by length of hospital stay, the number of transfused packed red blood cells, and the use of furosemide in CS-AKI patients. These findings may facilitate the earlier identification of patients susceptible to AKI after CS.

Lactate metabolism and acute kidney injury

ABSTRACT

Acute kidney injury (AKI) is a common clinically critical syndrome in hospitalized patients with high morbidity and mortality. At present, the mechanism of AKI has not been fully elucidated, and no therapeutic drugs exist. As known, glycolytic product lactate is a key metabolite in physiological and pathological processes. The kidney is an important gluconeogenic organ, where lactate is the primary substrate of renal gluconeogenesis in physiological conditions. During AKI, altered glycolysis and gluconeogenesis in kidneys significantly disturb the lactate metabolic balance, which exert impacts on the severity and prognosis of AKI. Additionally, lactate-derived posttranslational modification, namely lactylation, is novel to AKI as it could regulate gene transcription of metabolic enzymes involved in glycolysis or Warburg effect. Protein lactylation widely exists in human tissues and may severely affect non-histone functions. Moreover, the strategies of intervening lactate metabolic pathways are expected to bring a new dawn for the treatment of AKI. This review focused on renal lactate metabolism, especially in proximal renal tubules after AKI, and updated recent advances of lactylation modification, which may help to explore potential therapeutic targets against AKI.

High Intraoperative Serum Lactate Level is Associated with Acute Kidney Injury after Brain Tumor Resection

BACKGROUND

Postoperative acute kidney injury (AKI) is associated with poor clinical outcomes. Identification of risk factors for postoperative AKI is clinically important. Serum lactate can increase in situations of inadequate oxygen delivery and is widely used to assess a patient's clinical course. We investigated the association between intraoperative serum lactate levels and AKI after brain tumor resection.

METHODS

Demographics, medical and surgical history, tumor characteristics, surgery, anesthesia, preoperative and intraoperative blood test results, and postoperative clinical outcomes were retrospectively collected from 4131 patients who had undergone brain tumor resection. Patients were divided into high (n=1078) and low (n=3053) lactate groups based on an intraoperative maximum serum lactate level of 3.35 mmol/L. After propensity score matching, 1005 patients were included per group. AKI was diagnosed using the Kidney Disease Improving Global Outcomes criteria, based on serum creatinine levels within 7 days after surgery.

RESULTS

Postoperative AKI was observed in 53 (1.3%) patients and was more frequent in those with high lactate both before (3.2% [n=35] vs. 0.6% [n=18]; P < 0.001) and after (3.3% [n=33] vs. 0.6% [n=6]; P < 0.001) propensity score matching. Intraoperative predictors of postoperative AKI were maximum serum lactate levels > 3.35 mmol/L (odds ratio [95% confidence interval], 3.57 [1.45-8.74], P = 0.005), minimum blood pH (odds ratio per 1 unit, 0.01 [0.00-0.24], P = 0.004), minimum hematocrit (odds ratio per 1%, 0.91 [0.84-1.00], P = 0.037), and mean serum glucose levels > 200 mg/dL (odds ratio, 6.22 [1.75-22.16], P = 0.005).

CONCLUSION

High intraoperative serum lactate levels were associated with AKI after brain tumor resection.

Cutaneous Arsenical Exposure Induces Distinct Metabolic Transcriptional Alterations of Kidney Cells

Arsenicals are deadly chemical warfare agents that primarily cause death through systemic capillary fluid leakage and hypovolemic shock. Arsenical exposure is also known to cause acute kidney injury, a condition that contributes to arsenical-associated death due to the necessity of the kidney in maintaining whole-body fluid homeostasis. Because of the global health risk that arsenicals pose, a nuanced understanding of how arsenical exposure can lead to kidney injury is needed. We used a nontargeted transcriptional approach to evaluate the effects of cutaneous exposure to phenylarsine oxide, a common arsenical, in a murine model. Here we identified an upregulation of metabolic pathways such as fatty acid oxidation, fatty acid biosynthesis, and peroxisome proliferator-activated receptor (PPAR)-α signaling in proximal tubule epithelial cell and endothelial cell clusters. We also revealed highly upregulated genes such as Zbtb16, Cyp4a14, and Pdk4, which are involved in metabolism and metabolic switching and may serve as future therapeutic targets. The ability of arsenicals to inhibit enzymes such as pyruvate dehydrogenase has been previously described in vitro. This, along with our own data, led us to conclude that arsenical-induced acute kidney injury may be due to a metabolic impairment in proximal tubule and endothelial cells and that ameliorating these metabolic effects may lead to the development of life-saving therapies. SIGNIFICANCE STATEMENT: In this study, we demonstrate that cutaneous arsenical exposure leads to a transcriptional shift enhancing fatty acid metabolism in kidney cells, indicating that metabolic alterations might mechanistically link topical arsenical exposure to acute kidney injury. Targeting metabolic pathways may generate promising novel therapeutic approaches in combating arsenical-induced acute kidney injury.

Predicting renal function recovery and short-term reversibility among acute kidney injury patients in the ICU: comparison of machine learning methods and conventional regression

BACKGROUND

Acute kidney injury (AKI) is one of the most frequent complications of critical illness. We aimed to explore the predictors of renal function recovery and the short-term reversibility after AKI by comparing logistic regression with four machine learning models.

METHODS

We reviewed patients who were diagnosed with AKI in the MIMIC-IV database between 2008 and 2019. Recovery from AKI within 72 h of the initiating event was typically recognized as the short-term reversal of AKI. Conventional logistic regression and four different machine algorithms (XGBoost algorithm model, Bayesian networks [BNs], random forest [RF] model, and support vector machine [SVM] model) were used to develop and validate prediction models. The performance measures were compared through the area under the receiver operating characteristic curve (AU-ROC), calibration curves, and 10-fold cross-validation.

RESULTS

A total of 12,321 critically ill adult AKI patients were included in our analysis cohort. The renal function recovery rate after AKI was 67.9%. The maximum and minimum serum creatinine (SCr) within 24 h of AKI diagnosis, the minimum SCr within 24 and 12 h, and antibiotics usage duration were independently associated with renal function recovery after AKI. Among the 8364 recovered patients, the maximum SCr within 24 h of AKI diagnosis, the minimum Glasgow Coma Scale (GCS) score, the maximum blood urea nitrogen (BUN) within 24 h, vasopressin and vancomycin usage, and the maximum lactate within 24 h were the top six predictors for short-term reversibility of AKI. The RF model presented the best performance for predicting both renal functional recovery (AU-ROC [0.8295 ± 0.01]) and early recovery (AU-ROC [0.7683 ± 0.03]) compared with the conventional logistic regression model.

CONCLUSIONS

The maximum SCr within 24 h of AKI diagnosis was a common independent predictor of renal function recovery and the short-term reversibility of AKI. The RF machine learning algorithms showed a superior ability to predict the prognosis of AKI patients in the ICU compared with the traditional regression models. These models may prove to be clinically helpful and can assist clinicians in providing timely interventions, potentially leading to improved prognoses.

Lactate level and lactate clearance for acute kidney injury prediction among patients admitted with ST-segment elevation myocardial infarction: A retrospective cohort study

Background

Hyperlactatemia is a prognostic marker among patients with ST-segment elevation acute myocardial infarction (STEMI). However, the predictive value of lactate and the dynamic change associated with acute kidney injury (AKI) among patients with STEMI, remain poorly understood. We aimed to compare single lactate values at admission (Lacadm) and 12 h after admission (Lac12h) with lactate clearance (LC) 12 h after admission for AKI prediction in patients with STEMI.

Methods

A total of 1,784 patients with STEMI were included. The study endpoint was AKI occurrence during hospitalization. The predictive value of lactate levels measured at admission and 12 h after admission and LC for AKI prediction was determined using multivariate logistic regression analyses and compared with receiver operator characteristic (ROC) curve analysis.

Results

Overall, AKI was observed in 353 (19.8%) patients. In multivariate logistic regression analyses, Lacadm ≥ 4.3 mmol/L (OR: 1.53; 95% CI: 1.01-2.30), Lac12h ≥ 2.1 mmol/L (OR: 1.81; 95% CI: 1.36-2.42), and LC ≥ -7.5% (OR: 0.40; 95% CI: 0.30-0.53) were the independent predictive factors for AKI after adjusting for confounders. ROC curve analysis results revealed that Lac12h (0.639; 95% CI: 0.616-0.661) exhibited a significantly higher area under the curve (AUC) than those of Lacadm (0.551; 95% CI: 0.527-0.574) and LC (0.593; 95% CI: 0.570-0.616) in the prediction of AKI. LC (△AUC = 0.037, p < 0.001) and Lac12h (△AUC = 0.017, p = 0.029) enhanced the discrimination capacity of Mehran Risk Score (MRS) for AKI among patients undergoing emergency coronary angiography.

Conclusion

Lac12h is more effective for AKI prediction among patients with STEMI than Lacadm and LC. Furthermore, Lac12h and LC enhance the prediction capacity of MRS for AKI among patients after emergency coronary angiography.

Serum Lactate Level in Early Stage Is Associated With Acute Kidney Injury in Traumatic Brain Injury Patients

Background

Acute kidney injury (AKI) is a common complication in the clinical practice of managing patients with traumatic brain injury (TBI). Avoiding the development of AKI is beneficial for the prognosis of patients with TBI. We designed this study to testify whether serum lactate could be used as a predictive marker of AKI in patients with TBI.

Materials and Methods

In total, 243 patients with TBI admitted to our hospital were included in this study. Univariate and multivariate logistic regression analyses were utilized to analyze the association between lactate and AKI. The receiver operating characteristic (ROC) curves were drawn to verify the predictive value of lactate and the logistic model.

Results

Acute kidney injury group had higher age (p = 0.016), serum creatinine (p < 0.001), lactate (p < 0.001), and lower Glasgow Coma Scale (GCS; p = 0.021) than non-AKI group. Multivariate logistic regression showed that age [odds ratio (OR) = 1.026, p = 0.022], serum creatinine (OR = 1.020, p = 0.010), lactate (OR = 1.227, p = 0.031), fresh frozen plasma (FFP) transfusion (OR = 2.421, p = 0.045), and platelet transfusion (OR = 5.502, p = 0.044) were risk factors of AKI in patients with TBI. The area under the ROC curve (AUC) values of single lactate and predictive model were 0.740 and 0.807, respectively.

Conclusion

Serum lactate level in the early phase is associated with AKI in patients with TBI. Lactate is valuable for clinicians to evaluate the probability of AKI in patients with TBI.

Incidence of contrast-induced acute kidney injury in patients with acute mesenteric ischemia and identification of potential predictive factors

OBJECTIVE

Contrast-enhanced computed tomography angiography (CTA) is commonly used to investigate acute abdominal conditions, but the risk of contrast-induced acute kidney injury (CI-AKI) has been poorly investigated in patients with acute mesenteric ischemia. The aim of the present study was to evaluate the incidence of CI-AKI in these patients and identify potential predictive factors.

METHODS

Patients admitted for acute mesenteric ischemia who had a diagnostic CTA with contrast medium and a follow-up of creatinine concentration were retrospectively included.

RESULTS

Among 53 patients included, 9 (16.9%) developed CI-AKI. The prevalence of chronic kidney disease did not differ significantly between those who developed CI-AKI and those who did not (33.3 vs 18.2%, p=.372). Plasma total bilirubin and conjugated bilirubin levels were significantly higher in patients who developed CI-AKI (17.5 vs 8.0 μmol/L, p=.013 and 8.0 vs 3.0 μmol/L, p=.031, respectively). The proportion of patients who had revascularization was similar between patients who developed CI-AKI and those who did not (11.1 vs 20.5%, p>.999). No significant difference was observed for 30-day mortality and all-cause mortality for a median follow-up of 168 days (22.2 vs 13.6%, p=.611; and 33.3 vs 61.4%, p=.153, respectively).

CONCLUSION

This study reports the incidence of CI-AKI in patients with acute mesenteric ischemia after diagnostic CTA with contrast medium. Plasma bilirubin levels were a predictive factor of CI-AKI in these patients. The administration of contrast media during revascularization was not associated with an increased risk of CI-AKI.