Prediction Of Acute Kidney Injury Research Articles

A contemporary simple risk score for prediction of severe acute kidney injury after heart transplantation.

The aim of this study was to develop a simple risk score to estimate severe acute kidney injury (AKI) risk based on a large contemporary heart transplantation (HT) cohort. From 1 January 2015 to 31 December 2021, all consecutive HT recipients in our institute were included and analysed for the occurrence of AKI within the first seven postoperative days. Patients transplanted between 2015 and 2019 comprised the derivation cohort, and those transplanted between 2020 and 2021 formed the validation cohort. The primary endpoint was severe AKI (AKI stages 2-3). The impact of severe AKI on 90day mortality was also evaluated. Overall, 430 HT patients were included in the derivation cohort, and 108 were included in the validation cohort. Postoperative AKI occurred in 388 (72%) patients, including 162 (30%) severe AKI. The risk of 90day mortality significantly increased in patients with severe-AKI. Seven independent predictors of severe AKI were found in the derivation cohort, including recipients' body mass index, history of diabetes, anaemia, preoperative inotropes, estimated glomerular filtration rate, cardiopulmonary bypass duration and intraoperative red blood cell transfusion. The occurrence of severe AKI increased gradually from the lowest to the highest of the four risk score groups in the derivation and validation cohort. The scoring prediction model showed a highly acceptable discriminating power for severe-AKI [C statistic: 0.76, 95% confidence interval (CI): 0.71-0.80 for derivation cohort; C statistic: 0.79, 95% CI: 0.71-0.89 for validation cohort]. A contemporary simple risk score based on available variables from patients undergoing HT can accurately discriminate the risk of severe AKI.

Abstract 4147623: PORTAL VEIN PULSATILITY INDEX, INDEPENDENT OF INFERIOR VENA CAVA DILATATION, PREDICTS ACUTE KIDNEY INJURY IN PATIENTS WITH ACUTE HEART FAILURE

Background: The VExUS score is a useful tool for assessing systemic venous congestion that has shown the ability to predict acute kidney injury (AKI) in various populations (post cardiac surgical, CKD&ACS patients). Among the variables included in VExUS, inferior vena cava diameter (IVCD) is of particular importance, as the finding of a non-dilated IVCD (<20 mm) assigns a VExUS score of 0 (indicating no venous congestion). However, multiple factors in addition to congestion status may affect the IVCD, which may result in an errouneous assessment of congestion. Previous studies have suggested that portal vein pulsatility index (PVPI) and renal vein doppler are associated with volume status; however, no previous studies have assessed the PVPI, independently of IVCD, in the prediction of AKI. Hypothesis: We hypothezise that PVPI may predict AKI independently of the IVCD in patients with AHF. Methods: A prospective, single-center study was conducted, including patients admitted to the emergency room from July 2023 to January 2024 with the diagnosis of AHF, and in whom VExUS evaluation was performed during the first 8 hours of admission. For the analysis of the primary endpoint, patients were divided into four groups based on the presence or absence of a dilated inferior vena cava (cutoff <20 mm) and a PVPI ≥30%. We calculated the differences in time to the development of AKI for each group using survival analysis, Log-rank test and depicted the results using Kaplan-Meier curves. All statistical analyses were conducted using STATA v14.1. Results: A total sample of 189 patients was available for analysis (Figure 1). The mean age was 58.3 years (45.7–70.9), and the proportion of men was 73.6% (137), 5.9% patients had CKD stage IV (n = 11) and 18.8% CHF (n = 35). The median of serum creatinine at admission was 1.1 mg/dL (0.8 – 1.56) and NT-proBNP 4422 (1266 – 10783). Conclusion: PVPI, independent of dilatation of IVC, is a predictor of AKI in patients with AHF.

Incidence of acute kidney injury and its predictors among neonates admitted at neonatal intensive care unit of, Northwest Ethiopia comprehensive specialized hospitals, 2023.

Acute kidney injury is an acute and reversible increment in serum creatinine (SCr) levels with a reduction in urine output oliguria, or anuria. Acute kidney injury is a major cause of neonatal morbidity and mortality worldwide; it is a serious problem in low and middle-income countries, particularly in sub-Saharan Africa such as Ethiopia. Moreover, there are few studies in developing countries. This study aimed to investigate the incidence and predictors of acute kidney injury in neonates admitted to the neonatal intensive care unit of some specialized hospitals in the Amhara region of northwestern Ethiopia. A facility-based retrospective follow-up study was conducted in the Northwest Amhara Region's comprehensive specialized hospitals with 634 neonates from January 2020 to December 2022. Data were collected by reviewing patient charts using simple random sampling with a pretested checklist, entered using Epi-data 4.6, and analyzed using STATA 14. Median survival time, Kaplan-Meier survival curve, and log-rank test were calculated. Bivariable and multivariable Cox hazard models were used to determine the determinants of acute kidney injury. A hazard ratio with a 95% confidence interval was calculated. Variables with p-values less than 0.05 were considered statistically significant. The incidence of Acute Kidney Injury among Neonates admitted to Neonatal IntensiveCare Unit was 14.9 per 1000 (95% CI: 12.5-17.7) with the proportion of acute kidney injury (20.19%) (95% CI: 17.23-23.50) neonates with sepsis (AHR: 2.59; 95%CI: 1.21-5.56), neonates with perinatal asphyxia [(AHR: 2.70; 95%CI: 1.29-5.65) were taking gentamicin drugs [(AHR = 1.74; 95%CI: 1.03-2.94], neonates were preterm [(AHR; 1.77: 95%CI: 1.05 -2.98], and neonatal-hyponatremia [(AHR: 2.14; 95%CI: (1.00 -4.9)] and hyperkalemia [(AHR: 2.64; 95 CI: (1.11- 6.2)] were statistically found to be significant predictors of acute kidney injury. The incidence of acute kidney injury in neonates was high. Premature infants, neonates with sepsis, who suffered perinatal asphyxia, who received gentamicin drugs, whose sodium levels decreased and potassium levels increased were at higher risk of developing acute kidney injury. All concerned agencies should work to prevent acute kidney injury and pay special attention to multifactorial causes. Therefore, strategies need to be developed and/or strengthened to prevent the occurrence of acute kidney injury in infants with sepsis, neonates who suffered perinatal asphyxia, and preterm infants whose sodium levels decreased and potassium levels increased.

Predictors of acute kidney injury in chronic kidney disease patients treated for cardiovascular disease in the cardiac intensive care unit (MORCOR-TURK subgroup analysis).

Acute kidney injury (AKI) is a common complication in chronic kidney disease (CKD) patients in the cardiac intensive care unit (cardiac ICU). In this study, we aimed to identify predictors of AKI in CKD patients treated in the cardiac ICU for cardiovascular diseases. The MORCOR-TURK trial was conducted as a multicenter, prospective, cross-sectional, and noninterventional investigation. A total of 3157 patients treated in the cardiac ICU were enrolled from 50 centers over the course of one month. In this subgroup analysis, 615 patients with CKD treated in the cardiac ICU for cardiovascular disease were included in the study. The primary outcome of this study was the development of AKI. During hospitalization, patients who developed AKI were identified. AKI developed in 288 patients (46%). After multivariable analysis, decompensated heart failure (OR: 3.72, p = 0.005), primary percutaneous coronary intervention (OR: 3.75, p = 0.004), non-primary percutaneous coronary intervention(OR: 2.85, p = 0.033), troponin levels (OR: 1.04, p = 0.031), and need for mechanical ventilation (OR: 3.11, p < 0.001) were identified as independent predictors of AKI development in CKD patients. Our efforts to identify AKI predictors in cardiac ICU patients with CKD have yielded directly applicable results in clinical practice. AKI can be prevented by developing personalized strategies to follow up and treat cardiac ICU patients with CKD who have decompensated heart failure, are undergoing percutaneous coronary intervention (primary and non-primary), have high troponin levels, and need mechanical ventilation.

Serum Methotrexate Level Predicts Acute Kidney Injury After High-Dose Methotrexate: A Case Report and Single-Center Experience.

Acute kidney injury (AKI) is a serious complication following high-dose methotrexate (HD-MTX) treatment, despite established preventive measures. This study presents a case report and a retrospective review of patients treated with HD-MTX, aiming to identify risk factors for AKI and propose a modified treatment protocol. We report a case of a 43-year-old man with diffuse large B-cell lymphoma who developed severe AKI after HD-MTX therapy. Additionally, a retrospective review of 70 patients receiving HD-MTX at our institution was conducted to identify predictors of AKI. Serum methotrexate levels were analyzed to determine their significance in predicting AKI. The index patient developed methotrexate intoxication and severe AKI despite receiving standard prophylactic measures, requiring temporary hemodialysis. The retrospective review identified serum methotrexate levels as a significant predictor of AKI (OR 11.84, 95% CI: 2.62-53.53, p = 0.001). Higher initial serum methotrexate levels correlated with the development of AKI. Timely measurement of serum methotrexate levels is crucial in managing and preventing AKI in patients undergoing HD-MTX therapy. Based on our findings, we propose a modified HD-MTX treatment protocol to reduce the incidence of AKI. This includes earlier serum methotrexate level monitoring and adjustments in urine alkalization and leucovorin dosing strategies.

Research hotspots and frontiers of machine learning in renal medicine: a bibliometric and visual analysis from 2013 to 2024.

The kidney, an essential organ of the human body, can suffer pathological damage that can potentially have serious adverse consequences on the human body and even affect life. Furthermore, the majority of kidney-induced illnesses are frequently not readily identifiable in their early stages. Once they have progressed to a more advanced stage, they impact the individual's quality of life and burden the family and broader society. In recent years, to solve this challenge well, the application of machine learning techniques in renal medicine has received much attention from researchers, and many results have been achieved in disease diagnosis and prediction. Nevertheless, studies that have conducted a comprehensive bibliometric analysis of the field have yet to be identified. This study employs bibliometric and visualization analyses to assess the progress of the application of machine learning in the renal field and to explore research trends and hotspots in the field. A search was conducted using the Web of Science Core Collection database, which yielded articles and review articles published from the database's inception to May 12, 2024. The data extracted from these articles and review articles were then analyzed. A bibliometric and visualization analysis was conducted using the VOSviewer, CiteSpace, and Bibliometric (R-Tool of R-Studio) software. 2,358 papers were retrieved and analyzed for this topic. From 2013 to 2024, the number of publications and the frequency of citations in the relevant research areas have exhibited a consistent and notable increase annually. The data set comprises 3734 institutions in 91 countries and territories, with 799 journals publishing the results. The total number of authors contributing to the data set is 14,396. China and the United States have the highest number of published papers, with 721 and 525 papers, respectively. Harvard University and the University of California System exert the most significant influence at the institutional level. Regarding authors, Cheungpasitporn, Wisit, and Thongprayoon Charat of the Mayo Clinic organization were the most prolific researchers, with 23 publications each. It is noteworthy that researcher Breiman I had the highest co-citation frequency. The journal with the most published papers was "Scientific Reports," while "PLoS One" had the highest co-citation frequency. In this field of machine learning applied to renal medicine, the article "A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury" by Tomasev N et al., published in NATURE in 2019, emerged as the most influential article with the highest co-citation frequency. A keyword and reference co-occurrence analysis reveals that current research trends and frontiers in nephrology are the management of patients with renal disease, prediction and diagnosis of renal disease, imaging of renal disease, and development of personalized treatment plans for patients with renal disease. "Acute kidney injury," "chronic kidney disease," and "kidney tumors" are the most discussed diseases in medical research. The field of renal medicine is witnessing a surge in the application of machine learning. On one hand, this study offers a novel perspective on applying machine learning techniques to kidney-related diseases based on bibliometric analysis. This analysis provides a comprehensive overview of the current status and emerging research areas in the field, as well as future trends and frontiers. Conversely, this study furnishes data on collaboration and exchange between countries, regions, institutions, journals, authors, keywords, and reference co-citations. This information can facilitate the advancement of future research endeavors, which aim to enhance interdisciplinary collaboration, optimize data sharing and quality, and further advance the application of machine learning in the renal field.

A simplified bedside model for acute kidney injury prediction after percutaneous coronary intervention

Abstract Background Concern for acute kidney injury (AKI) after percutaneous coronary intervention (PCI) is a major determinant in the decision to pursue cardiac catheterization if otherwise indicated. A bedside AKI risk prediction model derived from the National Cardiovascular Data Registry (NCDR), most recently updated in 2023, employs relatively complex parameters for AKI prediction. Purpose To test the efficacy of a simplified pre-procedural 5-variable bedside score for post-PCI AKI prediction based on the NCDR model. Methods We analyzed our institution’s NCDR-reported catheterization laboratory registry between Q2 2022 and Q1 2023. Inclusion criteria, variable selection, and definitions were based on the NCDR model. A bedside prediction model was validated, including 5 pre-procedural variables: anemia (hemoglobin &amp;lt;10 mg/dl), history of heart failure, stage 4 or 5 chronic kidney disease (glomerular filtration rate &amp;lt;30 mg/dl), cardiac arrest, and shock status. Results We included 840 patients, of which 593 (70.6%) were men. Mean age was 69 (±12.5). Most procedures were performed on an urgent basis (444, 52.9%). AKI developed in 107 (12.7%) patients. Compared to the non-AKI group, patients who developed AKI were older (age 74±11.5 vs 68.3 ±12.5), and more frequently had anemia (23.6% vs 7.4%), diabetes (51.4% vs 35.2%), severe frailty (45.8% vs 23.7%), heart failure (62.6% vs 29.7%), cardiac arrest (13.1% vs 2.9%), CKD (30.8% vs 6%), shock (12.1% vs 1.5%), and mechanical circulatory support (7.5% vs 2.9%), p&amp;lt;0.001. Utilizing integer scores, the simplified bedside model employing 5 pre-procedural variables demonstrated discrimination similar to the bedside NCDR model, with a C-statistic of 0.77 (0.60-0.88) and excellent calibration (intercept of 0.31 and slope of 1.03) (Figure), indicating the robust performance of the model (compared to bedside NCDR model with a C-statistic 0.793, intercept of -0.197, and slope of 0.957). Conclusion A simplified NCDR-based bedside score using 5 pre-procedural variables is an effective tool for predicting AKI as a complication of PCI, with comparable performance to the 2023 updated bedside NCDR AKI risk model.

Proenkephalin improves risk prediction in acute coronary syndromes: derivation and external validation of the KID-ACS risk score

Abstract Background Early assessment of renal and mortality risk in patients with acute coronary syndromes (ACS) is essential to guide treatment decisions according to international guidelines. Circulating proenkephalin (PENK) is a stable opioid metabolite with fast response to changes in kidney function. Purpose This study examined the predictive value of PENK for acute kidney injury (AKI) and mortality in patients presenting with acute coronary syndromes (ACS). Methods Plasma PENK levels were measured using a validated sandwich immunoassay in a prospective multicentre ACS cohort from Switzerland (n = 4 787) and in validation cohorts from the UK (n = 1 141) and Czechia (n = 920). A biomarker-enhanced risk score for simultaneous prediction of both in-hospital acute kidney injury (AKI) and 30-day death (KID-ACS score) with model coefficients adjusted to the outcome was derived and externally validated. In the development of the in-hospital AKI model, patients from one participating study centre were reserved for external validation (Swiss validation cohort). Results Circulating PENK ranked among the top predictors of renal outcomes and mortality in patients with ACS. Accounting for established risk factors and risk models, circulating PENK levels at presentation were independently associated with in-hospital AKI (per log2 increase: adjusted odds ratio [OR] 1.56, 95% CI 1.14 – 2.12, P = 0.005) and with 30-day mortality (per log2 increase: adjusted OR 2.69, 95% CI 1.89 – 3.84, P &amp;lt; 0.001). Dynamic changes in PENK levels within the first 12-24 hours after presentation were strongly and independently associated with in-hospital AKI (increase vs. decrease: adjusted OR 2.83, 95% CI 1.98 – 4.05, P &amp;lt; 0.001). The simple 6-item KID-ACS risk score for in-hospital AKI and 30-day mortality integrates PENK levels at presentation and showed an AUC of 0.72 (95% CI 0.68 – 0.76) for in-hospital AKI, and of 0.91 (95% CI 0.87 – 0.95) for 30-day mortality in the derivation cohort. Upon external validation, KID-ACS had similarly high performance for in-hospital AKI (Swiss validation cohort: AUC 0.73, 95% CI 0.70 – 0.77; Czech validation cohort: 0.74, 95% CI 0.68 – 0.80) and 30-day mortality (UK validation cohort: AUC of 0.87, 95% CI 0.82 – 0.91; Czech validation cohort: 0.91, 95% CI 0.87 – 0.94). The simple 6-item KID-ACS score was non-inferior to established risk models and significantly outperformed the CA-AKI risk score in predicting in-hospital AKI (Zurich cohort: delta AUC 0.11, 95% CI 0.07 – 0.15, P = 0.001) and the GRACE 2.0 in predicting 30-day mortality (UK cohort: delta AUC 0.05, 95% CI 0.01 – 0.09, P = 0.027). Conclusions Circulating PENK was identified as independent predictor of in-hospital AKI and 30-day mortality in patients with ACS. The simple 6-item KID-ACS risk score integrates circulating PENK levels and provides a novel tool for simultaneous assessment of renal and mortality risk in patients presenting with ACS.Independent Predictive Value PENKPerformance and validation of KID-ACS

External validation of the CA-AKI score in patients with acute coronary syndrome: A real-world cohort analysis from Asia

Abstract Background Contrast-associated acute kidney injury (CA-AKI) is associated with long-term impairment of kidney function, the need for renal replacement therapy, and subsequent all-cause deaths. A practical risk score, the CA-AKI risk score is derived for the prediction of contrast-associated acute kidney injury. However, this novel score has not received sufficient evidence of external validation in real-world studies, especially in Asian individuals. Methods Short-term endpoints and long-term endpoints were assessed in 8,816 patients with acute coronary syndrome enrolled in a large Asia registry. Discrimination was assessed by Harrell’s C statistic, and calibration was assessed by calibration plots. The ability of the CA-AKI score to predict short-term and long-term prognosis was assessed. Results CA-AKI occurred in 5.3% of the patients, with a stepwise increase of CA-AKI rates from the lowest to the highest of the 4 risk categories. When predicting the risk of CA-AKI, both discrimination and calibration were helpful in model 2 (C-index: 0.72; slope: 0.97) and in model 1(C-index: 0.69; slope: 1.02). The risks of 1-year all-cause mortality and 1-year bleeding were higher in CA-AKI patients (HR: 2.70 [95% CI: 2.22-3.30] and HR: 1.76 [95% CI: 1.41-2.46]; respectively). Conclusion The updated CA-AKI risk score could accurately identify patients with contrast-associated acute kidney injury, the occurrence of which is strongly associated with long-term mortality and bleeding.

Microaxial Flow Pump Use and Renal Outcomes in Infarct-Related Cardiogenic Shock - a Secondary Analysis of the DanGer Shock Trial.

In the Danish-German Cardiogenic Shock (DanGer Shock) trial, use of a microaxial flow pump (mAFP) in patients with ST-segment elevation myocardial infarction (STEMI)-related CS led to lower all-cause mortality but higher rates of renal replacement therapy (RRT). In this prespecified analysis, rates and predictors of acute kidney injury (AKI) and RRT were assessed. In this international, randomized, open label, multicenter trial, 355 adult patients with STEMI-CS were randomized to mAFP (N=179) or standard care alone (N=176). AKI was defined according to Risk, Injury, and Failure, sustained Loss and End-stage kidney disease (RIFLE) criteria and assessed using logistic regression models. Use of RRT was assessed accounting for the competing risk of death using Fine-Gray subdistribution hazard models. AKI (RIFLE≥1) was recorded in 110 patients (61%) in mAFP group and 79 (45%) in control group (p<0.01); RRT was used in 75 (42%) and 47 (27%) patients, respectively (p<0.01). About 2/3 of the RRTs were initiated within the first 24h from admission (n=48 (64%) in mAFP group, n=31 (66%) in control group). Occurrence of AKI and RRT were associated with higher 180-day mortality in both study arms. At 180 days, all patients alive were free of RRT. mAFP use was associated with higher rates of RRT, even when accounting for competing risk of death (subdistribution hazard: 1.67 [1.18-2.35]). This association was largely consistent among prespecified subgroups. Allocation to mAFP was associated with lower 180-day mortality irrespective of AKI or RRT (p=0.8 for interaction). Relevant predictors of AKI in both groups comprised reduced left ventricular ejection fraction, baseline kidney function, shock severity, bleeding events, and positive fluid balance. In addition, predictors of AKI specific to mAFP were suction events, higher pump speed, and longer duration of support. Shock severity, allocation to mAFP, and device-related complications were associated with an increased risk of AKI. AKI was generally associated with higher mortality, but the allocation to mAFP consistently led to lower mortality rates at 180 days irrespective of the occurrence of AKI with or without RRT initiation.

Early Prediction of Acute Kidney Injury in Living Donor Liver Transplantation by Serum Cystatin C Concentration at the End of the Surgery.

Acute kidney injury (AKI) is a prevalent complication of liver transplantation, leading to prolonged hospital or intensive care unit stay and significant morbidity. Recently, biomarkers such as neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C have been investigated for their potential role in the early detection of AKI in liver transplantation patients. Our study comprised 60 patients with end-stage liver disease undergoing living donor liver transplantation. Based on the postoperative development of AKI, the patients were categorised into two groups: the AKI group comprising 22 patients and the non-AKI group comprising 38 patients. Serum cystatin C and urine NGAL levels were measured twice: immediately after induction of anaesthesia (baseline) and at the end of the surgery. The overall incidence of AKI was 36.66%. The mean cystatin C level measured at the end of the surgery was significantly higher in the AKI group (1.12 ± 0.40 mg/L) than in the non-AKI group (0.82 ± 0.27 mg/L) [P = .001]. The receiver operating characteristic curve for the postoperative cystatin C biomarker demonstrated a significant difference between the AKI and non-AKI groups [area under the curve: 0.71, P = .007]. However, baseline cystatin C and urine NGAL levels did not significantly differ between the groups. Cystatin C levels measured at the end of the surgery showed a better predictive value and higher accuracy in identifying post-liver transplantation patients with AKI than baseline cystatin C and urine NGAL.

Analysis of influencing factors of acute kidney injury after unilateral nephrectomy

Unilateral Nephrectomy is one of the most common treatments for surgical diseases of the kidney but often results in postsurgical acute kidney injury (AKI). In the current study, we aimed to investigate the risk factors for AKI in patients who have received Unilateral Nephrectomy. We retrospectively analysed 528 patients who underwent Unilateral Nephrectomy for different etiologies between January 2013 and December 2018 at the Affiliated Hospital of Qingdao University. We recorded the prevalence and severity of AKI, age, gender, diabetes, body mass index (BMI), hypertension, preoperative renal function, etiology, performed surgically, anaemia, albumin, coagulation, lactate dehydrogenase, nitrogen (BUN), and uric acid. Univariate and multivariate logistic regression analyses were used to investigate the predictors of AKI in patients with Unilateral Nephrectomy. Overall, 218 of the 528 patients (41.2%) developed AKI during their hospitalisation. Univariate analysis showed that AKI was significantly associated with gender (male, OR = 1.866, P = 0.001), overweight (OR = 2.19, P = 0.0002), and surgical approach (OR = 1.7, P = 0.018), while multivariate logistic regression analysis showed that male gender (OR = 1.953, P = 0.001), overweight (OR = 2.176, P = 0.001), and preoperative renal function (OR = 0.507, P = 0.001) were independent factors for AKI. Regression analysis among different etiologies showed significant differences in postoperative AKI. After Unilateral nephrectomy, AKI is more likely to occur in overweight male patients with normal kidney function. AKI occurred more frequently in patients who are kidney donors, but rarely in those with non-function kidneys.

Neutrophil-platelet ratio as a predictor of acute kidney injury in severe COVID-19.

Acute kidney injury (AKI) is one of the most seen complications of coronavirus-2019 (COVID-19) infection. Patients with AKI caused by COVID-19 likely have higher neutrophil counts and lower platelet and lymphocyte levels. Therefore, the predictive value of many inflammation indexes calculated from the total blood count has been investigated to predict the AKI in COVID-19. According to our clinical experience, we thought that neutrophilia and thrombocytopenia may be more common in the development of AKI. For this reason, this study aimed to evaluate the predictive value of the neutrophil-to-platelet ratio (NPR) for AKI in severe COVID-19 patients. This retrospective study included 334 severe COVID-19 patients followed up in the intensive care unit (ICU). Predictive factors for AKI were analyzed. ROC curve analysis was performed to determine the inflammation indexes' cutoff values for the AKI prediction. Multivariate analyses were performed to determine correlations between the inflammation indexes and AKI. In this study, AKI was determined at the rate of 43% (n:145). Independent risk factors affecting AKI were determined to be age (HR = 1.047, 95% confidence interval [CI]: 1.021-1.072, P < .001), the need for invasive mechanical ventilation (HR = 3.003, 95% CI: 1.645-5.481, P = .001) and the need for vasopressor (HR = 8.111, 95% CI: 3.786-17.375, P < .001). The optimal cutoff values predicting AKI were determined to be 3.9 for the NPR (AUC = 0.679, 95% CI: 0.622-0.737, P < .001) with 71.7% sensitivity and 61.9% specificity, 16.1 for the neutrophil-to-lymphocyte ratio (NLR) (AUC = 0.634, 95% CI: 0.575-0.694, P < .001) with 65.5% sensitivity and 56.1% specificity, and 3872.5 × 109L for the systemic inflammatory index (SII) (AUC = 0.566, 95% CI: 0.504-0.629, P = .038) with 60% sensitivity and 55.6% specificity. In the regression model, only NPR values above the cutoff were related to AKI (HR = 3.817, 95% CI: 1.782-8.177, P = .001). The NPR has more predictive value than the NLPR, NLR, and SII in developing AKI in severe COVID-19 patients in the ICU. NPR is a new helpful index that can help clinicians predict early AKI in critical COVID-19.

Urinary L-FABP Assay in the Detection of Acute Kidney Injury following Haematopoietic Stem Cell Transplantation.

Background: Acute Kidney Injury (AKI) is a condition that affects a significant proportion of acutely unwell patients and is associated with a high mortality rate. Patients undergoing haemopoietic stem cell transplantation (HSCT) are in an extremely high group for AKI. Identifying a biomarker or panel of markers that can reliably identify at-risk individuals undergoing HSCT can potentially impact management and outcomes. Early identification of AKI can reduce its severity and improve prognosis. We evaluated the urinary Liver type fatty acid binding protein (L-FABP), a tubular stress and injury biomarker both as an ELISA and a point of care (POC) assay for AKI detection in HSCT. Methods: 85 patients that had undergone autologous and allogenic HSCT (35 and 50, respectively) had urinary L-FABP (uL-FABP) measured by means of a quantitative ELISA and a semi-quantitative POC at baseline, day 0 and 7 post-transplantation. Serum creatinine (SCr) was also measured at the same time. Patients were followed up for 30 days for the occurrence of AKI and up to 18 months for mortality. The sensitivity and specificity of uL-FABP as an AKI biomarker were evaluated and compared to the performance of sCr using ROC curve analysis and logistic regression. Results: 39% of participants developed AKI within 1 month of their transplantation. The incidence of AKI was higher in the allogenic group than in the autologous HTSC group (57% vs. 26%, p = 0.008) with the median time to AKI being 25 [range 9-30] days. This group was younger (median age 59 vs. 63, p < 0.001) with a lower percentage of multiple myeloma as the primary diagnosis (6% vs. 88%, p < 0.001). The median time to AKI diagnosis was 25 [range 9-30] days. uL-FABP (mcg/gCr) at baseline, day of transplant and on the 7th day post-transplant were 1.61, 5.39 and 10.27, respectively, for the allogenic group and 0.58, 4.36 and 5.14 for the autologous group. Both SCr and uL-FABP levels rose from baseline to day 7 post-transplantation, while the AUC for predicting AKI for baseline, day 0 and day 7 post-transplant was 0.54, 0.59 and 0.62 for SCr and for 0.49, 0.43 and 0.49 uL-FABP, respectively. Univariate logistic regression showed the risk of AKI to be increased in patients with allogenic HSCT (p = 0.004, 95%CI [0.1; 0.65]) and in those with impaired renal function at baseline (p = 0.01, 95%CI [0.02, 0.54]). The risk of AKI was also significantly associated with SCr levels on day 7 post-transplant (p = 0.03, 95%CI [1; 1.03]). Multivariate logistic regression showed the type of HSCT to be the strongest predictor of AKI at all time points, while SCr levels at days 0 and 7 also correlated with increased risk in the model that included uL-FABP levels at the corresponding time points. The POC device for uL-FABP measurement correlated with ELISA (p < 0.001, Spearman 'correlation' = 0.54) Conclusions: The urinary biomarker uL-FABP did not demonstrate an independent predictive value in the detection of AKI at all stages. The most powerful risk predictor of AKI in this setting appears to be allograft recipients and baseline renal impairment, highlighting the importance of clinical risk stratification. Urinary L-FAPB as a POC biomarker was comparable to ELISA, which provides an opportunity for simple and rapid testing. However, the utility of LFABP in AKI is unclear and needs further exploration. Whether screening through rapid testing of uL-FABP can prevent or reduce AKI severity is unknown and merits further studies.

Persistent acute kidney injury: Postoperative impact and predictors in patients undergoing liver resection.

Persistent acute kidney injury (AKI) has not been investigated in patients undergoing liver resection. We aimed to identify the predictors of persistent AKI, its effect on postoperative outcomes and long-term renal function in patients following liver resection, and its impact on survival in patients with hepatocellular carcinoma (HCC). We examined 990 patients who underwent liver resection, including a subgroup analysis of 384 patients with curative resection for initial HCC. Persistent AKI was defined as residual impairment of serum creatinine≥0.3mg/dL or≥50% from baseline 1month after surgery. The persistent AKI group had significantly worse postoperative outcomes, including overall morbidity, major morbidity, longer hospital stay, and 90-day mortality. In the subgroup analysis of patients with HCC, persistent AKI was associated with a significantly poorer overall survival (OS) rate (p<0.001), and the multivariate analysis confirmed persistent AKI as an independent poor prognostic factor for OS (p=0.005). The long-term postoperative estimated glomerular filtration rate decline was significantly greater in the persistent AKI group than in the no AKI and transient AKI groups (p<0.001 for both). Chronic kidney disease, albumin-bilirubin grade ≥2, and anatomical resection were independent predictors of persistent AKI (p=0.001, p=0.039, and p=0.015, respectively). Persistent AKI adversely affects postoperative outcomes and long-term renal function in patients undergoing liver resection. Furthermore, it is associated with poor prognosis in patients with HCC. Therapeutic strategies to prevent persistent AKI are critical for improving postoperative outcomes in these patients.

Unveiling the Interplay: Antioxidant Enzyme Polymorphisms and Oxidative Stress in Preterm Neonatal Renal and Hepatic Functions.

To explore the relationship between oxidative stress biomarkers and the occurrence of acute kidney injury (AKI) alongside notable liver function disturbances in preterm neonates. Given the immaturity of kidneys and incomplete liver development in preterm neonates, oxidative stress poses a considerable threat to their renal and hepatic health. To find out the association between various oxidative stress biomarkers and polymorphisms of antioxidant enzymes with renal and live functions. In this cross-sectional study, we gathered umbilical cord blood and peripheral blood samples for assessing oxidative stress biomarkers and identifying single nucleotide polymorphisms (SNPs) in antioxidant enzymes. Utilizing enzyme-linked immunosorbent assay kits, we quantified these oxidative stress biomarkers. Receiver-operating characteristics curve analysis was employed to ascertain the predictive capacity of these biomarkers, denoted by the area-under-the-curve (AUC). Our findings revealed that umbilical cord heat-shock proteins emerged as robust predictors of neonatal AKI (AUC: 0.92; 95% CI: 0.8-1) with a defined cut-off concentration of 1.8 ng/mL. Likewise, umbilical cord 8-hydroxy-2-deoxy guanosine demonstrated significant predictability for liver function alterations (AUC: 0.7; 95% CI: 0.6-0.9) at a cut-off concentration of 2487.6 pg/mL. We observed significant associations between SNPs in endothelial nitric oxide synthase and catalase with both AKI and impaired liver functions. Prospective studies are warranted to validate these findings, with a particular focus on exploring potential antioxidant interventions aimed at mitigating AKI and liver function abnormalities.

Development and validation of a web-based nomogram for acute kidney injury in acute non-variceal upper gastrointestinal bleeding patients.

Acute kidney injury (AKI) is a common and serious complication in patients with acute non-variceal upper gastrointestinal bleeding (NVUGIB). Early prediction and intervention are crucial for improving patient outcomes. Data for patients presenting with acute NVUGIB in this retrospective study were sourced from the MIMC-IV database. Patients were randomly allocated into training and validation cohorts for further analysis. Independent predictors for AKI were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses in the training cohort. Based on the logistic regression results, a nomogram was developed to predict early AKI onset in acute NVUGIB patients, and implemented as a web-based calculator for clinical application. The nomogram's performance was evaluated through discrimination, using the C-index, calibration curves, and decision curve analysis (DCA) to assess its clinical value. The study involved 1082 acute NVUGIB patients, with 406 developing AKI. A multivariable logistic regression identified five key AKI predictors: CKD, use of human albumin, chronic liver disease, glucose, and blood urea nitrogen. The nomogram was constructed based on independent predictors. The nomogram exhibited robust accuracy, evidenced by a C-index of 0.73 in the training cohort and 0.72 in the validation cohort. Calibration curves demonstrated satisfactory concordance between predicted and observed AKI occurrences. DCA revealed that the nomogram offered considerable clinical benefit within a threshold probability range of 7% to 54%. Our nomogram is a valuable tool for predicting AKI risk in patients with acute NVUGIB, offering potential for early intervention and improved clinical outcomes.

Assessment of Predictors of Acute Kidney Injury and Progression to Chronic Kidney Disease Following Bariatric Surgery

BackgroundDespite the overall safety of metabolic and bariatric surgery (MBS), the potential for postoperative complications such as acute kidney injury (AKI) remains a critical concern. Decade-old studies from our institution reported rates of AKI following MBS between 5.8% and 8.6%, with factors such as higher body mass index (BMI), diabetes, and hypertension identified as potential contributors. However, the incidence and factors associated with AKI following MBS have remained underexplored in contemporary literature. ObjectiveTo investigate the incidence and risk factors associated with postoperative AKI, as well as the potential for progression to CKD and renal failure. SettingQuaternary academic medical center with a high-volume MBS practice. MethodsA retrospective review of adult patients undergoing primary laparoscopic MBS between 2008 and 2022 to identify patients who developed AKI, defined as postoperative increase in serum creatinine (sCr) by 0.3 mg/dL within 72 hours. A multivariable logistic regression was constructed to identify potential AKI risk factors. ResultsAmong 1697 patients, the incidence of AKI was 3.0% (n=51). The distribution of AKI was not significantly different between procedure types. There was no significant correlation between anesthesia medications given and the occurrence of AKI. Male gender was the most significant predictor of AKI (adjusted odds ratio [aOR] = 3.87, 95% CI [2.14 – 6.99]), followed by hypertension (aOR = 2.12, 95%CI [1.03 – 4.83]) and longer surgical duration (aOR = 1.19, 95% CI [1.05 – 1.35]) per 30 minutes. Of those who developed AKI, 7 (13.7%) required dialysis acutely for management, while 3 patients (5.9%) progressed to chronic renal failure and required transplant. ConclusionAKI is a rare but serious complication following MBS that occurs in approximately 3% of cases. AKI incidence is higher in male patients, those with hypertension, insulin-requiring diabetes, renal insufficiency, and longer procedure durations. Heightened awareness of the identified risk factors should help guide patient selection, and additional efforts should be directed towards refining postoperative follow-up.

Urinary Cystatin B as a marker of acute kidney injury in cats

Diagnosing acute kidney injury (AKI) might be challenging due to lack of sensitive early markers. The objective of this study was to evaluate the diagnostic and prognostic utility of the urinary biomarker Cystatin B (uCysB) in cats with AKI. Seventy-six client-owned cats were included. Urine samples of healthy cats and cats with various urinary tract disease including urethral obstruction (UO), chronic kidney disease (CKD) and AKI, were collected. uCysB concentration was measured using a research sandwich format ELISA at IDEXX Laboratories, Inc.uCysB was different among groups (P <0.001). uCysB was higher in the AKI (P <0.001) and CKD (P =0.006) groups compared with controls [1052ng/mL (range, 7-3858) and 112ng/mL (range, 14-1370) vs. 22ng/mL (range, 11-154), respectively]. Cats with AKI had higher uCysB compared with cats with CKD (P =0.001) or UO (P =0.004). Receiver operator characteristic curve (ROC) analysis of uCysB as an AKI predictor vs. controls had an area under the curve (AUC) of 0.92 (95%CI, 0.84-1.0). A 84ng/mL cutoff point corresponded to sensitivity and specificity of 90% and 92%, respectively. uCysB concentration was higher in AKI non-survivors compared with survivors (1572ng/mL, range, 140-3858 vs. 584ng/mL, range, 7-2803 respectively; P =0.004). ROC analysis of uCysB as an AKI outcome predictor had an AUC of 0.84 (95%CI, 0.56-1.0), with an optimal cut-off point of 469ng/mL, corresponding to sensitivity and specificity of 100% and 75% respectively. In conclusion, uCysB is a useful diagnostic and prognostic marker of AKI in cats.

A new score predicting renal replacement therapy in patients with crush injuries: Analysis of a major earthquake

BackgroundIt is important to predict which patients may require renal replacement therapy (RRT) at the time of initial presentation after crush injuries. There is limited data in the literature examining the predictors of RRT. MethodsThis study was conducted by evaluating 2232 patients who presented to our hospital following two major earthquakes of magnitudes 7.6 and 7.7 Mw that occurred in Kahramanmaras, Turkey, on February 6, 2023. A total of 314 patients who were hospitalized upon being rescued from the rubble and had a creatine kinase (CK) level above 1000 U/L were included in the final analysis. Factors predicting the need for RRT were investigated, and a dialysis score was developed for this prediction. Resultsthe 314 patients included in the study, 95 (30.2 %) developed acute kidney injury (AKI). RRT was performed on 68 (21.6 %) patients. The optimal cut-off value of CK for the prediction of AKI was 23,000 U/L. Multivariate analysis revealed that factors predicting RRT were the number of traumatized sides (odds ratio [OR]: 2.2, 95 % confidence interval [CI]: 1.09–4.39, p = 0.026), albumin (OR:0.11, 95 % CI: 0.04–0.32, p < 0.001), and CK (OR: 1.00, 95 % CI 1.00–1.00, p < 0.001). A dialysis score was developed ranging from 0 to 7 based on the number of traumatized sides, albumin, and CK. The area under the curve (AUC) of the dialysis score in receiver operating characteristic analysis was 0.974. A dialysis score of 4 or higher had a sensitivity of 97.1 % and a specificity of 89.4 % for predicting the need for RRT. ConclusionsThe dialysis score predicts the need for RRT quite well. The simplicity of use and high sensitivity and specificity of this score in earthquake-related crush injuries will greatly facilitate clinicians in patient triage and follow-up.