Early Acute Kidney Injury Research Articles

Early Acute Kidney Injury in Stroke Patients Submitted to Endovascular Treatment: A Cohort Study

Background/Objectives: Acute kidney injury (AKI) is a potential complication of cardiovascular disorders and is associated with worse outcome. The aim of this study was to assess the incidence of early AKI after endovascular therapy for acute ischemic stroke, identify predictors for this complication, and test the association between AKI and mortality or death or dependency. Methods: This was a single-center cohort study involving consecutive patients with acute ischemic stroke submitted to endovascular therapy between 2015 and 2022. AKI was defined according to the KDIGO criteria and evaluated at 48 h. Other outcomes of interest were vital status and functional dependency at 3 months using the modified Rankin Scale, with death or dependency being defined as a score > 2. An adjustment for potential confounders was performed using logistic regression. Results: Overall, 1150 patients were included in the analysis, with a mean age of 74 years and a slight female preponderance (56%). The median NIHSS was 15, the mean onset-to-groin time was 392 min, and 92% of patients were successfully recanalized. The overall incidence rate of AKI was 6%. On univariate analysis, patients with AKI were older (p = 0.002), had a longer time to EVT (p = 0.042), higher NIHSS (p = 0.006), higher blood glucose (p = 0.033), and lower baseline glomerular filtration rate (GFR) (p < 0.001). After adjustment for confounders, AKI was independently associated with NIHSS (p = 0.012), time to treatment (p = 0.004), and lower baseline GFR (p < 0.001). AKI was also independently associated with higher mortality (OR = 2.302, p = 0.003). Conclusions: Patients with impaired baseline renal function and more severe stroke are at higher risk of AKI, and AKI begets worse stroke outcome. Better strategies are required to optimize treatment outcome in these patients and avert this vicious cycle.

The Impact of Heart Failure Chronic Treatment Prior to Cardiac Transplantation on Early Outcomes

Background and Objectives: Cardiac transplantation represents the option for patients with end-stage heart failure (HF), providing the best survival rate. However, the postoperative complications of transplant patients remain a challenge for clinicians. The objective of our study was to evaluate the effect of preoperative chronic HF treatment on the occurrence of in-hospital complications. Materials and Methods: We retrospectively included a total of 50 patients who underwent cardiac transplantation between January 2011 and December 2023 from the Emergency Institute for Cardiovascular Diseases and Transplantation of Targu Mures. We correlated the preoperative chronic HF treatment with the postoperative complications by Spearmen’s correlation coefficient, respectively. With logistic regression, the associations between the treatment and specific complications were determined. Results: Significant negative correlations were found between Carvedilol treatment with 2-month mortality (r = −0.30; 95% CI: −0.53–−0.02; p = 0.03), Ramipril with hospital stay (r = −0.38; 95% CI: −0.60–-0.12; p < 0.01) and intensive care unit (ICU) stay (r = −0.37; 95% CI: −0.59–−0.11; p = 0.01), and Spironolactone usage with hospitalization duration (r = −0.28; 95% CI: −0.52–−0.01; p = 0.04). Furthermore, Carvedilol treatment represented a protective factor against early acute kidney injury (AKI) (OR: 0.22; 95% CI: 0.05–0.91; p = 0.03). Spironolactone treatment was a protective factor against AGR (OR: 0.12; 95% CI: 0.02–0.66; p = 0.01) treatment, in contrast to angiotensin-converting enzyme inhibitor (ACEI) therapy (OR: 5.30; 95% CI: 1.03–27.17; p = 0.04). Conclusions: Pre-transplant Carvedilol treatment was negatively correlated with the 2-month mortality rate. Ramipril and Spironolactone therapy were negatively correlated with hospitalization duration, and Ramipril was additionally correlated with ICU stay. Moreover, Carvedilol therapy represented a protective factor against early AKI. Pre-transplant Spironolactone was associated with lower event rates of AGR, in contrast to ACEI treatment. Prospective studies with larger cohorts are needed in order to draw drastic conclusions.

Early acute kidney injury after tacrolimus administration in heart transplant recipients receiving basiliximab induction therapy.

In this study, we aimed to analyze the association among the timing of tacrolimus initiation, time required to reach the target blood concentration, and early acute kidney injury (AKI) after tacrolimus administration in heart transplant recipients who received basiliximab induction therapy. 88 patients treated with tacrolimus-based immunosuppressive therapy were retrospectively reviewed. Induction therapy was administered to 52 patients. AKI was evaluated within 7 days of tacrolimus administration. The rate of increase in tacrolimus trough concentration to the target trough concentration of 10 µg/mL early after its administration was set to be similar in the basiliximab induction and non-induction group; 8 and 2 patients developed AKI in the induction and non-induction group, respectively. In the induction group, there was no significant difference in the timing of tacrolimus initiation and the time required to reach the target concentration between patients who developed and did not develop AKI. In contrast, the cumulative incidence of AKI was significantly different between patients with an estimated glomerular filtration rate below and those with an estimated glomerular filtration rate above 43 mL/min/1.73m2 at the start of tacrolimus administration (37.5% and 11.4%, respectively; p=0.045). In patients receiving basiliximab induction therapy, the timing of tacrolimus initiation and the time to reach the target concentration are unlikely to be associated with early AKI after tacrolimus administration. However, the recovery of sufficient renal function after heart transplantation is important for determining the start time of tacrolimus.

031. Urine Neutrophil Gelatinase-Associated Lipocalin (NGAL) Levels as a Predictor of Early Acute Kidney Injury in Post Coronary Artery Bypass Graft (CABG) Patients in H. Adam Malik Hospital Medan

Background: One of the main complications after open heart surgery is acute kidney injury. Coronary Artery Bypass Graft surgery is one of the main factors in this complication. Currently, the use of serum creatinine as one of the diagnostic criteria for AKI is not sensitive for diagnosing AKI at an early stage. Elevated urine NGAL levels are more indicative of a renal damage process than an increase in circulation. An increase in NGAL levels in urine can occur 100 times faster than circulating NGAL. Thus our research aimed to view NGAL ability to predict AKI in CABG patient. Methods: This research is an observational study with cross-sectional data collection methods to find out whether NGAL can be a predictor of AKI in patients who have undergone CABG surgery. Results: The collection of research subjects was stopped when the number of samples had been reached so that this study was a cohort study with consecutive sampling techniques. In the results of this study, we obtained 31 research samples. In 31 research samples, it was found that the average age was 61.46 years with a standard deviation of 8.2 years. This study was dominated by male gender with a total of 20 people or 64% of the total sample. After CABG surgery, it was found that 4 patients had postoperative acute renal failure or 13.3% of the total sample. The sensitivity of the instrument is 100% with a specificity of 96%. The accuracy of the NGAL is 97.5%. Conclusion: NGAL is a useful parameter to predict AKI and would have significant advantage however further study with multi-center design would be necessary to validate these result.

Development and validation of an early acute kidney injury risk prediction model for patients with sepsis in emergency departments

In this study, we aimed to develop and validate a nomogram to predicting the risk of sepsis-associated acute kidney injury (SA-AKI) in patients admitted to emergency departments (EDs). We randomly divided a retrospective dataset of 391 patients with sepsis into a 294-person training cohort and a 97-person validation cohort, and developed three predictive models using multivariate logistic regression analysis and clinical insight. No difference was observed between the three models using the DeLong test and Model 3 was selected as the risk prediction model based on the principle of least inclusion indicators. The use of vasopressor drugs, patient age, platelet count, procalcitonin, and D-dimer levels were included. The training and validation cohorts had a consistency index of 0.832 and 0.866, respectively, indicating high accuracy and stability in predicting SA-AKI risk. The area under the receiver operating characteristic curve was 0.832, showing excellent discrimination. The calibration curves for the training and validation cohorts showed excellent calibration. The decision curve and clinical impact curve analyses showed that the net clinical benefit of using the nomogram was greatest over a probability threshold of 0.05–0.90. In addition, the model showed moderate validity in predicting the 30-day survival and the incidence of major adverse renal events within 30 days. The nomogram developed for SA-AKI risk assessment in patients in EDs showed good discriminability and clinical utility. It can provide a theoretical basis for emergency physicians to prevent SA-AKI.

Targeting Sepsis: Disease Tolerance, Immune Resilience, and Compartmentalized Immunity

Introduction: Sepsis remains a major contributor to critical care mortality and morbidity worldwide. Despite advances in understanding its complex immunopathology, the compartmentalized nature of immune responses across different organs has yet to be fully translated into targeted therapies. This review explores the burden of sepsis on organ-specific immune dysregulation, immune resilience, and epigenetic reprogramming, emphasizing translational challenges and opportunities. Methods: We implemented a systematic literature search strategy, incorporating data from studies published between 2010 and 2024, to evaluate the role of molecular profiling techniques, including transcriptomics and epigenetic markers, in assessing the feasibility of targeted therapies. Results: Sepsis-induced immune dysregulation manifests differently in various organs, with lung, heart, liver, and kidney responses driven by unique local immune environments. Organ-specific biomarkers, such as the Spns2/S1P axis in lung macrophages, mitochondrial dysfunction in the heart, proenkephalin for early acute kidney injury (AKI), and adrenomedullin for predicting multi-organ failure, offer promising avenues for timely intervention. Furthermore, immune resilience, particularly through regulatory T-cell modulation and cytokine targeting (e.g., IL-18), is crucial for long-term recovery. Epigenetic mechanisms, including histone modification and trained immunity, present opportunities for reprogramming immune responses but require more precision to avoid unintended inflammatory sequelae. Conclusions: A deeper understanding of compartmentalized immune responses and the dynamic immune landscape in sepsis is critical for developing precision therapies. Real-time immune monitoring and organ-targeted interventions could revolutionize sepsis management, although significant barriers remain in clinical translation. Further research is required to establish biomarkers and treatment timing that optimize therapeutic efficacy while minimizing systemic risks.

Plasma bioactive adrenomedullin predicts mortality and need for dialysis in critical COVID-19

COVID-19 is a severe respiratory disease affecting millions worldwide, causing significant morbidity and mortality. Adrenomedullin (bio-ADM) is a vasoactive hormone regulating the endothelial barrier and has been associated with COVID-19 mortality and other adverse events. This prospective cohort pilot study included 119 consecutive patients with verified SARS-CoV-2 infection admitted to two intensive care units (ICUs) in Southern Sweden. Bio-ADM was retrospectively analysed from plasma on ICU admission, and days 2 and 7. Information on comorbidities, adverse events and mortality was collected. The primary outcome was 90-day mortality, and secondary outcomes were markers of disease severity. The association between bio-ADM and outcomes was analysed using survival analysis and logistic regression. Bio-ADM on admission, day 2, and day 7 only moderately predicted 90-day mortality in univariate and multivariate Cox regression. The relative change in bio-ADM between sample times predicted 90-day mortality better even when adjusting for the SAPS3 score, with an HR of 1.09 (95% CI 1.04–1.15) and a C-index of 0.82 (95% CI 0.72–0.92) for relative change between day 2 and day 7. Bio-ADM had a good prediction of the need for renal replacement therapy in multivariate Cox regression adjusting for creatinine, where day 2 bio-ADM had an HR of 3.18 (95% CI 1.21–8.36) and C-index of 0.91 (95% CI 0.87–0.96). Relative changes did not perform better, possibly due to a small sample size. Admission and day 2 bio-ADM was associated with early acute kidney injury (AKI). Bio-ADM on ICU admission, day 2 and day 7 predicted 90-day mortality and dialysis needs, highlighting bio-ADM’s importance in COVID-19 pathophysiology. Bio-ADM could be used to triage patients with a risk of adverse outcomes and as a potential target for clinical interventions.

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.

Early Renal Outcomes Following Heart Transplantation Using Organs Procured After Circulatory Death.

Transplantation using hearts obtained through donation after circulatory death (DCD) is increasing, but data on recipient renal outcomes are limited. Patients at a single institution who underwent heart transplantation using organs procured through DCD or donation after brain death (DBD) from April 2016 to August 2022 were included in this retrospective cohort study. Hemodynamic measures were collected via right heart catheterization performed 1 week after transplantation. Posttransplantation renal outcomes included estimated glomerular filtration rate at 1 week, 4 weeks, and 16 weeks, and the incidence of acute kidney injury (AKI) and renal replacement therapy within 1 week. The analysis included 225 patients (55 recipients of DCD). Baseline characteristics were comparable between recipients of DCD and DBD. Renal outcomes within 1 week posttransplantation in recipients of DCD were similar to recipients of DBD, including percent change in estimated glomerular filtration rate (-37.9% [-58.6 to -6.2] versus -31.9% [-52.4 to -9.9]; P=0.91), incidence of AKI (47.3% versus 46.5%; P>0.99) and incidence of renal replacement therapy (3.6% versus 4.7%; P>0.99). Recipients of DCD with AKI within 1 week ("early AKI") did not recover to baseline estimated glomerular filtration rate (75.8 [60.2-91.3] mL/min per 1.73 m2) by week 16 (59.3 [46.9-73.6] mL/min per 1.73 m2; P=0.002), whereas recipients without early AKI exhibited comparable estimated glomerular filtration rate to baseline by week 4 (84.5 [70.8-98.5] mL/min per 1.73 m2; P=0.084). Similar trends were observed in recipients of DBD. Recipients of DCD demonstrated similar renal outcomes compared with recipients of DBD, supporting the ongoing use of DCD transplantation. Early AKI was associated with persistent renal dysfunction for recipients of both DCD and DBD.

Modified furosemide responsiveness index and biomarkers for AKI progression and prognosis: a prospective observational study.

Modified furosemide responsiveness index (mFRI) is a novel biomarker for assessing diuretic response and AKI progression in patients with early AKI. However, the comparative predictive performance of mFRI and novel renal biomarkers for adverse renal outcomes remains unclear. In a single-center prospective study, we aimed to evaluate the discriminatory abilities of mFRI and other novel renal biomarkers in predicting AKI progression and prognosis in patients with initial mild and moderate AKI (KDIGO stage 1 to 2). Patients with initial mild and moderate AKI within 48h following cardiac surgery were included in this study. The mFRI, renal biomarkers (including serum or urinary neutrophil gelatinase-associated lipocalin [sNGAL or uNGAL], serum cystatin C, urinary N-acetyl-beta-D-glycosaminidase [uNAG], urinary albumin-to-creatinine ratio) and cytokines (TNF, IL-1β, IL-2R, IL-6, IL-8, and IL-10) were measured at AKI diagnosis. The mFRI was calculated for each patient, which was defined as 2-hour urine output divided by furosemide dose and body weight. Of 1013 included patients, 154 (15.2%) experienced AKI progression, with 59 (5.8%) progressing to stage 3 and 33 (3.3%) meeting the composite outcome of hospital mortality or receipt of renal replacement therapy (RRT). The mFRI showed non-inferiority or potential superiority to renal biomarkers and cytokines in predicting AKI progression (area under the curve [AUC] 0.80, 95% confidence interval [CI] 0.77-0.82), progression to stage 3 (AUC 0.87, 95% CI 0.85-0.89), and composite outcome of death and receipt of RRT (AUC 0.85, 95% CI 0.82-0.87). Furthermore, the combination of a functional biomarker (mFRI) and a urinary injury biomarker (uNAG or uNGAL) resulted in a significant improvement in the prediction of adverse renal outcomes than either individual biomarker (all P < 0.05). Moreover, incorporating these panels into clinical model significantly enhanced its predictive capacity for adverse renal outcomes, as demonstrated by the C index, integrated discrimination improvement, and net reclassification improvement (all P < 0.05). As a rapid, cost-effective and easily accessible biomarker, mFRI, exhibited superior or comparable predictive capabilities for AKI progression and prognosis compared to renal biomarkers in cardiac surgical patients with mild to moderate AKI. Clinicaltrials.gov, NCT04962412. Registered July 15, 2021, https://clinicaltrials.gov/ct2/show/NCT04962412?cond=NCT04962412&draw=2&rank=1 .

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.

Integrin subunit beta 6 is a potential diagnostic marker for acute kidney injury in patients with diabetic kidney disease: a single cell sequencing data analysis

Background Diabetic kidney disease (DKD), a prevalent complication of diabetes mellitus, is often associated with acute kidney injury (AKI). Thus, the development of preventive and therapeutic strategies is crucial for delaying the progression of AKI and DKD. Methods The GSE183276 dataset, comprising the data of 20 healthy controls and 12 patients with AKI, was downloaded from the Gene Expression Omnibus (GEO) database to analyze the AKI group. For analyzing the DKD group, the GSE131822 dataset, comprising the data of 3 healthy controls and 3 patients with DKD, was downloaded from the GEO database. The common differentially expressed genes (DEGs) in renal tubular epithelial cells (TECs) were subjected to enrichment analyses. Next, a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes database to analyze gene-related regulatory networks. Finally, the AKI animal models and the DKD and AKI cell models were established, and the reliability of the identified genes was validated using quantitative real-time polymerase chain reaction analysis. Results Functional analysis was performed with 40 common DEGs in TECs. Eight hub genes were identified using the PPI and gene-related networks. Finally, validation experiments with the in vivo animal model and the in vitro cellular model revealed the four common DEGs. Four DEGs that share molecular mechanisms in the pathogenesis of DKD and AKI were identified. In particular, the expression of Integrin Subunit Beta 6(ITGB6), a hub and commonly upregulated gene, was upregulated in the in vitro models. Conclusion ITGB6 may serve as a biomarker for early AKI diagnosis in patients with DKD and as a target for early intervention therapies.

An early and stable mouse model of polymyxin-induced acute kidney injury

BackgroundPolymyxins have been revived as a last-line therapeutic option for multi-drug resistant bacteria and continue to account for a significant proportion of global antibiotic usage. However, kidney injury is often a treatment limiting event with kidney failure rates ranging from 5 to 13%. The mechanisms underlying polymyxin-induced nephrotoxicity are currently unclear. Researches of polymyxin-associated acute kidney injury (AKI) models need to be more standardized, which is crucial for obtaining consistent and robust mechanistic results.MethodsIn this study, male C57BL/6 mice received different doses of polymyxin B (PB) and polymyxin E (PE, also known as colistin) by different routes once daily (QD), twice daily (BID), and thrice daily (TID) for 3 days. We continuously monitored the glomerular filtration rate (GFR) and the AKI biomarkers, including serum creatinine (Scr), blood urea nitrogen (BUN), neutrophil gelatinase-associated lipocalin (NGAL), and kidney injury molecule-1 (KIM-1). We also performed histopathological examinations to assess the extent of kidney injury.ResultsMice receiving PB (35 mg/kg/day subcutaneously) once daily exhibited a significant decrease in GFR and a notable increase in KIM-1 two hours after the first dose. Changes in GFR and KIM-1 at 24, 48 and 72 h were consistent and demonstrated the occurrence of kidney injury. Histopathological assessments showed a positive correlation between the severity of kidney injury and the changes in GFR and KIM-1 (Spearman’s rho = 0.3167, P = 0.0264). The other groups of mice injected with PB and PE did not show significant changes in GFR and AKI biomarkers compared to the control group.ConclusionThe group receiving PB (35 mg/kg/day subcutaneously) once daily consistently developed AKI at 2 h after the first dose. Establishing an early and stable AKI model facilitates researches into the mechanisms of early-stage kidney injury. In addition, our results indicated that PE had less toxicity than PB and mice receiving the same dose of PB in the QD group exhibited more severe kidney injury than the BID and TID groups.

Predicting Early AKI in Two Large Multicenter Pediatric Critical Care Datasets

Predicting Early AKI in Two Large Multicenter Pediatric Critical Care Datasets

Biomarker-based acute kidney injury sub-phenotypes refine risk assessment in children undergoing cardiac surgery.

Pediatric cardiac surgery-associated acute kidney injury (CS-AKI) is common with variable association with outcomes, possibly because transient serum creatinine (SCr) elevations are unrelated to kidney disease. Sub-phenotypes of CS-AKI with biomarker integration may provide prognostic enrichment. This study aims to determine if combining early postoperative urine neutrophil gelatinase-associated lipocalin (uNGAL) and SCr into sub-phenotypes strengthens associations with AKI and outcomes. We hypothesized that patients with early subclinical (uNGAL + , SCr -) or damage (uNGAL + , SCr +) CS-AKI would have more postoperative day 2-4 KDIGO-defined AKI and worse clinical outcomes than patients with early functional AKI (uNGAL - , SCr +). Two-center prospective observational study evaluating combinations of early uNGAL (8-12h from ICU admission, ≥ 150ng/mL) and early postoperative (≤ 8h of admission) KDIGO SCr-defined AKI to predict CS-AKI on postoperative days (POD) 2-4. Four CS-AKI phenotypes were derived (uNGAL - /SCr - ; uNGAL + /SCr - ; uNGAL - /SCr + and uNGAL + /SCr +). The primary outcome was POD2-4 KDIGO SCr-defined CS-AKI. Secondary outcomes included ventilator and intensive care unit-free days (maximum 28). Four hundred seventy-six patients (median age 4.8 [IQR 1.4-30.4] months, 39% female) were included. POD2-4 AKI occurred in 44 (9.2%). 27% were uNGAL + /SCr - and 0.4% (n = 2) uNGAL + /SCr + . The adjusted odds of POD2-4 AKI was ninefold higher (aOR: 9.09, 95%CI: 3.84-21.53) in uNGAL + /SCr - when compared to uNGAL - /SCr - . uNGAL + /SCr - was associated with fewer ventilator-free (aOR: 0.30, 95%CI: 0.19-0.48) and ICU-free days (aOR: 0.41, 95%CI: 0.26-0.66) when compared to uNGAL - /SCr - . Early postoperative uNGAL, regardless of SCr elevation, refines risk assessment for pediatric POD2-4 CS-AKI and associated morbidity, enabling earlier AKI identification and prognostics.

Association of Preoperative Neutrophil to Lymphocyte Ratio with Early Postoperative Acute Kidney Injury Following Isolated Off-Pump Coronary Artery Bypass Grafting

Objective: Acute kidney injury (AKI) is a frequent complication after off-pump coronary artery bypass grafting (OPCAB) that complicates recovery, increases treatment cost and mortality. Neutrophil to lymphocyte ratio (NLR) is a systemic inflammatory marker easily derived from complete blood count that has many prognostic potentials. The purpose of this study was to evaluate if there is an association of preoperative NLR with early postoperative AKI following isolated OPCAB. Methods: This cross-sectional study was carried out in the Department of Cardiac Surgery, National Institute of Cardiovascular Diseases (NICVD) on a total of 60 patients aged 31-70 years with no preoperative renal dysfunction undergoing isolated OPCAB between August 2021 and July 2022. Group A included 30 patients with preoperative NLR &lt; 2.65 and Group B included 30 patients with preoperative NLR ≥ ≥≥2.65. Patients were monitored for development of early postoperative AKI according to serum creatinine criteria of Kidney Disease Improving Global Outcomes (KDIGO) 2012 guideline. Results: Two patients from group A and twenty patients from group B developed early postoperative AKI (p &lt; 0.001). Events of AKI were significantly higher in group B patients at all postoperative time points. Multivariate binary logistic regression analysis revealed preoperative NLR ≥ ≥≥2.65 as an independent predictor of early post OPCAB AKI (p = 0.004, OR = 13.746). In receiver operating curve (ROC) analysis area under curve (AUC) was 0.933 (95% CI 0.874-0.992, p &lt; 0.001). It showed 90.91% sensitivity and 73.7% specificity at the pre-set cut off value of NLR at 2.65 where optimal predictability of post-OPCAB AKI occurred with 66.67% positive predictive value, 93.33% negative predictive value and 80% accuracy. Conclusion: Preoperative NLR is significantly associated with early postoperative AKI following isolated OPCAB and therefore it should be incorporated in routine clinical practice for early prediction of AKI and implementing timely preventive strategies. (Bangladesh Heart Journal 2024; 39(2): 151-160

Early therapeutic drug monitoring of methotrexate and its association with acute kidney injury: A retrospective cohort study.

High-dose methotrexate (HDMTX) use can be limited by the development of acute kidney injury (AKI). Early AKI detection is paramount to prevent further renal injury and irreversible toxicities. This study sought to determine whether early elimination patterns of MTX would be useful as a biomarker of AKI in HDMTX treatment. This retrospective cohort study included two sites that collected ≥2 MTX levels within 16 h from completion of MTX infusion. Early levels were tagged and MTX elimination half-life (t½) were calculated from combinations of two of three different early time periods. Receiver operating characteristic (ROC) curves were synthesized for each elimination t½ (biomarker) with respect to AKI and delayed methotrexate elimination (DME); the biomarker with the highest area under the ROC curve (AUC) was tested in a multiple variable logistic regression model. Data from 169 patients who received a total of 556 courses of HDMTX were analyzed. ROC analysis revealed MTX elimination t½ calculated from the second and third time periods had the highest AUC for AKI at 0.62 (interquartile range [IQR] 0.56-0.69) and DME at 0.86 (IQR 0.73-1.00). After adjusting for age, sex, dose (mg/m2), infusion duration, HDMTX course, and baseline estimated glomerular filtration rate, it remained significant for AKI with an OR of 1.29 and 95% confidence interval of 1.03-1.65. Early MTX elimination t½ measured within 16 h of infusion completion was significantly associated with the development of AKI and serves as an early clearance biomarker that may identify patients who benefit from increased hydration, augmented leucovorin rescue, and glucarpidase administration.

Electronic Alert Systems for Patients With Acute Kidney Injury

The acute kidney injury (AKI) electronic alert (e-alert) system was hypothesized to improve the outcomes of AKI. However, its association with different patient outcomes and clinical practice patterns remains systematically unexplored. To assess the association of AKI e-alerts with patient outcomes (mortality, AKI progression, dialysis, and kidney recovery) and clinical practice patterns. A search of Embase and PubMed on March 18, 2024, and a search of the Cochrane Library on March 20, 2024, to identify all relevant studies. There were no limitations on language or article types. Studies evaluating the specified outcomes in adult patients with AKI comparing AKI e-alerts with standard care or no e-alerts were included. Studies were excluded if they were duplicate cohorts, had insufficient outcome data, or had no control group. Two investigators independently extracted data and assessed bias. The systematic review and meta-analysis followed the PRISMA guidelines. Random-effects model meta-analysis, with predefined subgroup analysis and trial sequential analyses, were conducted. Primary outcomes included mortality, AKI progression, dialysis, and kidney recovery. Secondary outcomes were nephrologist consultations, post-AKI exposure to nonsteroidal anti-inflammatory drugs (NSAID), post-AKI angiotensin-converting enzyme inhibitor and/or angiotensin receptor blocker (ACEI/ARB) prescription, hospital length of stay, costs, and AKI documentation. Thirteen unique studies with 41 837 unique patients were included (mean age range, 60.5-79.0 years]; 29.3%-48.5% female). The risk ratios (RRs) for the AKI e-alerts group compared with standard care were 0.96 for mortality (95% CI, 0.89-1.03), 0.91 for AKI stage progression (95% CI, 0.84-0.99), 1.16 for dialysis (95% CI, 1.05-1.28), and 1.13 for kidney recovery (95% CI, 0.86-1.49). The AKI e-alerts group had RRs of 1.45 (95% CI, 1.04-2.02) for nephrologist consultation, 0.75 (95% CI, 0.59-0.95) for post-AKI NSAID exposure. The pooled RR for post-AKI ACEI/ARB exposure in the AKI e-alerts group compared with the control group was 0.91 (95% CI, 0.78-1.06) and 1.28 (95% CI, 1.04-1.58) for AKI documentation. Use of AKI e-alerts was not associated with lower hospital length of stay (mean difference, -0.09 [95% CI, -0.47 to 0.30] days) or lower cost (mean difference, US $655.26 [95% CI, -$656.98 to $1967.5]) but was associated with greater AKI documentation (RR, 1.28 [95% CI, 1.04-1.58]). Trial sequential analysis confirmed true-positive results of AKI e-alerts on increased nephrologist consultations and reduced post-AKI NSAID exposure and its lack of association with mortality. In this systematic review and meta-analysis, AKI e-alerts were not associated with a lower risk for mortality but were associated with changes in clinical practices. They were associated with lower risk for AKI progression. Further research is needed to confirm these results and integrate early AKI markers or prediction models to improve outcomes.

Interpretable machine learning model for early prediction of acute kidney injury in patients with rhabdomyolysis

Abstract Background Rhabdomyolysis (RM) is a complex set of clinical syndromes. RM-induced acute kidney injury (AKI) is a common illness in war and military operations. This study aimed to develop an interpretable and generalizable model for early AKI prediction in patients with RM. Methods Retrospective analyses were performed on 2 electronic medical record databases: the eICU Collaborative Research Database and the Medical Information Mart for Intensive Care III database. Data were extracted from the first 24 hours after patient admission. Data from the two datasets were merged for further analysis. The extreme gradient boosting (XGBoost) model with the Shapley additive explanation method (SHAP) was used to conduct early and interpretable predictions of AKI. Results The analysis included 938 eligible patients with RM. The XGBoost model exhibited superior performance (area under the receiver operating characteristic curve [AUC] = 0.767) compared to the other models (logistic regression, AUC = 0.711; support vector machine, AUC = 0.693; random forest, AUC = 0.728; and naive Bayesian, AUC = 0.700). Conclusion Although the XGBoost model performance could be improved from an absolute perspective, it provides better predictive performance than other models for estimating the AKI in patients with RM based on patient characteristics in the first 24 hours after admission to an intensive care unit. Furthermore, including SHAP to elucidate AKI-related factors enables individualized patient treatment, potentially leading to improved prognoses for patients with RM.

Advancements in Trauma-Induced Acute Kidney Injury: Diagnostic and Therapeutic Innovations.

Acute kidney injury following trauma impacts patient recovery critically, necessitating an integrated approach to emergency care and nephrology. This review aims to provide a comprehensive understanding of trauma-induced nephropathy, highlighting recent advancements in pathophysiological insights, diagnostic techniques, and strategic interventions. Our key findings emphasize the role of biomarkers, like Neutrophil Gelatinase-Associated Lipocalin and Liver Fatty Acid-Binding Protein, and imaging techniques, such as contrast-enhanced ultrasound, in early AKI detection. Preventive strategies, including aggressive fluid resuscitation, avoidance of nephrotoxic agents, and hemodynamic optimization, are essential for mitigating AKI progression. Integrating these approaches into trauma care frameworks aims to enhance patient outcomes and set a foundation for future research and clinical improvements.