Kidney Disease Improving Global Outcomes Research Articles

23 Pre-surgical visceral adipose tissue may be a novel pre-surgical risk factor for acute kidney injury among clear cell renal cell cancer patients undergoing radical nephrectomy

Abstract Background Patients with renal cancer undergoing partial (PN) or radical nephrectomy (RN) are at risk for acute kidney injury (AKI). Established risk factor for AKI include baseline comorbidities (e.g., obesity, hypertension), normal renal parenchymal loss, and ischemia-reperfusion injury. Pre-surgical body composition may be an overlooked modifiable patient characteristic that influences risk of AKI. We hypothesized that patients with higher visceral adipose tissue quantity or lower skeletal muscle quantity would have a higher risk of AKI. Methods The RESOLVE study at Memorial Sloan Kettering Cancer Center is a retrospective study of 1239 patients with stage I-III clear cell renal cell carcinoma (ccRCC) undergoing PN or RN from 2000 to 2020. We excluded from analysis patients with solitary kidney, those without preoperative serum creatinine (sCr) measurements, and those without a sCr measurement within seven days following nephrectomy, yielding a study population of 1,200 ccRCC patients with longitudinal sCr assessment (n=754 PN; n=446 PN). AKI was defined as a binary variable using the Kidney Disease – Improving Global Outcomes (KDIGO) criteria, based on a threshold of either a 1.5x relative or 0.3 mg/dl absolute increase in sCr within seven days. The cross-sectional areas and radiodensities of visceral adipose and skeletal muscle tissues were determined from pre-surgical computed tomography (CT) scans at the third lumbar vertebrae using Automatica software. We used generalized linear models with a binomial family and identity link to estimate seven-day risk differences (RD) and 95% confidence intervals in subgroups defined by surgery type. Results AKI was more frequent among patients undergoing RN (66% vs 26% among PN). Male patients, those with higher eGFR prior to surgery, those with lower stage/smaller tumors, and those with a history of hyperlipidemia more frequently experienced AKI in the post-operative period. No associations were observed with other reported comorbidities (diabetes, hypertension). While no association was observed between BMI and risk of AKI, visceral adipose and skeletal muscle variables were significantly associated with risk of AKI in univariate models. After adjustment for age, sex, comorbidities, and other body composition variables, only higher visceral adipose tissue quantity remained significantly associated with increased risk of AKI [RD per 40 unit increase (95% CI): 5.2 (1.3, 9.2)]. Muscle characteristics were not associated with AKI in multivariable models. Among patients undergoing PN, we observed a higher frequency of AKI among male patients, those with higher stage/larger tumors, and those with longer ischemia times. No significant associations were observed with comorbidity histories. In univariate models, visceral adipose tissue quantity and quality as well as skeletal muscle quantity were associated with AKI risk; however, after adjustment for age, sex, comorbidities, and other body composition variables, we observed no significant associations between any body composition feature and AKI in patients undergoing PN. Conclusions Associations between pre-surgical body composition and risk of AKI vary by surgery type. Visceral adipose tissue quantity was associated with risk of AKI among patients undergoing RN, but not PN. This finding may be relevant for patient counseling, consideration for nephron-sparing surgery, and development of interventions to lower visceral adipose tissue quantity. Future studies should evaluate the impact of both pre-surgical and post-surgical change in body composition in relation on chronic kidney disease after nephrectomy.

Cardiovascular, renal and mortality risk by the KDIGO heatmap in japan

Abstract Background This study aimed to assess the prognosis of people with chronic kidney disease (CKD) in Japan using the Kidney Disease Improving Global Outcomes (KDIGO) heatmap. Methods The prognoses of individuals with estimated glomerular filtration rates (eGFR) < 90 ml/min/1.73 m2 were evaluated based on the KDIGO heatmap using an electronic medical record database in Japan. The primary outcome was major adverse cardiovascular events (MACE), a composite of myocardial infarction (MI), stroke, heart failure (HF) hospitalization, and in-hospital death (referred to as MACE1). Additionally, ad hoc MACE2 (MI hospitalization, stroke hospitalization, HF hospitalization, and in-hospital death) was examined. The secondary outcome was the renal outcome. Results Of the 543 606 individuals included, the mean age was 61.6 ± 15.3 years, 50.1% were male, and 40.9% lacked urine protein results. The risk of MACEs increased independently with both eGFR decline and increasing proteinuria from the early KDIGO stages: Hazard ratios (with 95% confidence interval) of MACE1 and MACE2, compared to G2A1 were 1.16 (1.12–1.20) and 1.17 (1.11–1.23), respectively, for G3aA1, and 1.17 (1.12–1.21) and 1.35 (1.28–1.43), respectively, for G2A2. This increased up to 2.83 (2.54–3.15) and 3.43 (3.00–3.93), respectively, for G5A3. Risks of renal outcomes also increased with CKD progression. Conclusions This study is the first to demonstrate the applicability of the KDIGO heatmap in assessing cardiovascular and renal risk in Japan. The risk increased from the early stages of CKD, indicating the importance of early diagnosis and intervention through appropriate testing.

Advances in primary glomerulonephritis.

Primary glomerulonephritis comprises several renal-limited diseases that can cause haematoproteinuria, chronic kidney disease, nephrosis and end stage kidney disease. The most common of these are IgA nephropathy (IgAN), primary membranous nephropathy (PMN), Focal Segmental Glomerulosclerosis (FSGS) and Minimal Change Disease (MCD). Although rare, these diseases cause a significant burden to health care systems, given the high cost of treating End Stage Kidney Disease (ESKD) with dialysis or transplantation. Until recently, the pathogenesis of primary gloerulonephritis has remained obscure. However, recent advances in understanding of how these diseases evolve has led to the introduction of novel therapeutic agents. Trials are underway or have recently completed that have huge implications for the standard of care for the primary glomerulonephritidies, and should dramatically reduce the number of patients who progress onto end stage kidney disease. This article reviews the international Kidney Disease Improving Global Outcomes (KDIGO) guidelines for the treatment of IgAN, PMN, FSGS and MCD, as well as recent research on pathogenesis and treatment.

Beyond the Valve: Incidence, Outcomes, and Modifiable Factors of Acute Kidney Injury in Patients with Infective Endocarditis Undergoing Valve Surgery—A Retrospective, Single-Center Study

Background/Objectives: Infective endocarditis (IE) often requires surgical intervention, with postoperative acute kidney injury (AKI), posing a significant concern. This retrospective study aimed to investigate AKI incidence, its impact on short-term mortality, and identify modifiable factors in patients with IE scheduled for valve surgery. Methods: This single-center study enrolled 130 consecutive IE patients from 2013 to 2021 undergoing valve surgery. The creatinine levels were monitored pre- and postoperatively, and AKI was defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Patient demographics, comorbidities, procedural details, and complications were recorded. Primary outcomes included AKI incidence; the relevance of creatinine levels for AKI detection; and the association of AKI with 30-, 60-, and 180-day mortality. Modifiable factors contributing to AKI were explored as secondary outcomes. Results: Postoperatively, 35.4% developed AKI. The highest creatinine elevation occurred on the second postoperative day. Best predictive value for AKI was a creatinine level of 1.35 mg/dL on the second day (AUC: 0.901; sensitivity: 0.89, specificity: 0.79). Elevated creatinine levels on the second day were robust predictors for short-term mortality at 30, 60, and 180 days postoperatively (AUC ranging from 0.708 to 0.789). CK-MB levels at 24 h postoperatively and minimum hemoglobin during surgery were identified as independent predictors for AKI in logistic regression. Conclusions: This study highlights the crucial role of creatinine levels in predicting short-term mortality in surgical IE patients. A specific threshold (1.35 mg/dL) provides a practical marker for risk stratification, offering insights for refining perioperative strategies and optimizing outcomes in this challenging patient population.

Urine Output and AKI in Neonates/Younger Children: A Prospective Study of Cardiac Surgery Patients with Indwelling Urinary Catheters.

Pediatric acute kidney injury (AKI) is associated with significant morbidity and mortality, yet a precise definition, especially concerning urine output (UO) thresholds, remains unproven. We evaluate UO thresholds for AKI in neonates and children aged 1-24 months with indwelling urinary catheters undergoing cardiac surgery. A six-year prospective cohort study (2018-2023) after cardiac surgery was conducted at a reference center in Brazil. All patients had indwelling urinary catheters up to 48 hours after surgery and at least two serum creatinine (sCr) measurements, including one before surgery. The main objective of this study was to determine the optimal UO thresholds for AKI definition and staging in neonates and younger children compared with the currently used criteria-neonatal and adult Kidney Disease Improving Global Outcomes (KDIGO) definitions. The outcome was a composite of severe AKI (stage 3 AKI diagnosed by the sCr criterion only), kidney replacement therapy, or hospital mortality. The study included 1,024 patients: 253 in the neonatal group and 772 in the younger children group. In both groups, the lowest UO at 24 hours as a continuous variable had good discriminatory capacity for the composite outcome (AUC-ROC 0.75 [95% CI 0.70-0.81] and 0.74 [95% CI 0.68-0.79]). In neonates, the best thresholds were 3.0, 2.0 and 1.0 mL/kg/hour, and in younger children, the thresholds were 1.8, 1.0 and 0.5 mL/kg/hour. These values were used for modified AKI staging for each age group. In neonates, this modified criterion was associated with the best discriminatory capacity (AUC-ROC 0.74 [0.67-0.80] vs. 0.68 [0.61-0.75], P<0.05) and net reclassification improvement (NRI) in comparison with the neonatal KDIGO criteria. In younger children, the modified criteria had good discriminatory capacity but were comparable to the adult KDIGO criteria, and the NRI was near zero. Using indwelling catheters for UO measurements, our study reinforced that the current KDIGO criteria may require adjustments to better serve the neonate population. Additionally, using the UO criteria, we validated the adult KDIGO criteria in children aged 1-24 months.

Relationship between intra-operative urine output and postoperative acute kidney injury in paediatric cardiac surgery: A retrospective cohort study.

Intra-operative urine output (UO) has been shown to predict postoperative acute kidney injury (AKI) in adults; however, its significance in children undergoing cardiac surgery remains unknown. To explore the association between intra-operative UO and postoperative AKI in children with congenital heart disease. A retrospective observational study. A tertiary hospital. Children aged >28 days and <6 years who underwent cardiac surgery at Fuwai Hospital from 1 April 2022 to 30 August 2022. AKI was identified by the highest serum creatinine value within postoperative 7 days using Kidney Disease Improving Global Outcomes (KDIGO) criteria. In total, 1184 children were included. The incidence of AKI was 23.1% (273/1184), of which 17.7% (209/1184) were stage 1, 4.2% (50/1184) were stage 2, and others were stage 3 (1.2%, 14/1184). Intra-operative UO was calculated by dividing the total intra-operative urine volume by the duration of surgery and the actual body weight measured before surgery. There was no significant difference in median [range] intra-operative UO between the AKI and non-AKI groups (2.6 [1.4 to 5.4] and 2.7 [1.4 to 4.9], respectively, P = 0.791), and multivariate logistic regression analyses showed that intra-operative UO was not associated with postoperative AKI [adjusted odds ratio (OR) 0.971; 95% confidence interval (CI), 0.930 to 1.014; P = 0.182]. Regarding the clinical importance of severe forms of AKI, we further explored the association between intra-operative UO and postoperative moderate-to-severe AKI (adjusted OR 0.914; 95% CI, 0.838 to 0.998; P = 0.046). Intra-operative UO was not associated with postoperative AKI during paediatric cardiac surgery. However, we found a significant association between UO and postoperative moderate-to-severe AKI. This suggests that reductions in intra-operative urine output below a specific threshold may be associated with postoperative renal dysfunction. Clinicaltrials.gov identifier: NCT05489263.

A novel real-time model for predicting acute kidney injury in critically ill patients within 12 hours.

A major challenge in prevention and early treatment of acute kidney injury (AKI) is the lack of high-performance predictors in critically ill patients. Therefore, we innovatively constructed U-AKIpredTM for predicting AKI in critically ill patients within 12h of panel measurement. The prospective cohort study included 680 patients in the training set and 249 patients in the validation set. After performing inclusion and exclusion criteria, 417 patients were enrolled in the training set and 164 patients were enrolled in the validation set finally. AKI was diagnosed by Kidney Disease Improving Global Outcomes (KDIGO) criteria. Twelve urinary kidney injury biomarkers (mALB, IgG, TRF, α1MG, NAG, NGAL, KIM-1, L-FABP, TIMP2, IGFBP7, CAF22 and IL-18) exhibited good predictive performance for AKI within 12h in critically ill patients. U-AKIpredTM, combined with three crucial biomarkers (α1MG, L-FABP and IGFBP7) by multivariate logistic regression analysis, exhibited better predictive performance for AKI in critically ill patients within 12h than the other twelve kidney injury biomarkers. The area under the curve (AUC) of the U-AKIpredTM, as a predictor of AKI within 12h, was 0.802 (95% CI: 0.771-0.833, P<0.001) in the training set and 0.844 (95% CI: 0.792-0.896, P<0.001) in validation cohort. A nomogram based on the results of the training and validation sets of U-AKIpredTM was developed which showed optimal predictive performance for AKI. The fitting effect and prediction accuracy of U-AKIpredTM was evaluated by multiple statistical indicators. To provide a more flexible predictive tool, the dynamic nomogram (https://www.xsmartanalysis.com/model/U-AKIpredTM) was constructed using a web-calculator. Decision curve analysis (DCA) and a clinical impact curve were used to reveal that U-AKIpredTM with the three crucial biomarkers had a higher net benefit than these twelve kidney injury biomarkers respectively. The net reclassification index (NRI) and integrated discrimination index (IDI) were used to improve the significant risk reclassification of AKI compared with the 12 kidney injury biomarkers. The predictive efficiency of U-AKIpredTM was better than the NephroCheck® when testing for AKI and severe AKI. U-AKIpredTM is an excellent predictive model of AKI in critically ill patients within 12h and would assist clinicians in identifying those at high risk of AKI.

The incidence, risk factors, and prognosis of acute kidney injury in patients after cardiac surgery.

Acute kidney injury (AKI) represents a significant complication following cardiac surgery, associated with increased morbidity and mortality rates. Despite its clinical importance, there is a lack of universally applicable and reliable methods for the early identification and diagnosis of AKI. This study aimed to examine the incidence of AKI after cardiac surgery, identify associated risk factors, and evaluate the prognosis of patients with AKI. This retrospective study included adult patients who underwent cardiac surgery at Changhai Hospital between January 7, 2021, and December 31, 2021. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Perioperative data were retrospectively obtained from electronic health records. Logistic regression analyses were used to identify independent risk factors for AKI. The 30-day survival was assessed using the Kaplan-Meier method, and differences between survival curves for different AKI severity levels were compared using the log-rank test. Postoperative AKI occurred in 257 patients (29.6%), categorized as stage 1 (179 patients, 20.6%), stage 2 (39 patients, 4.5%), and stage 3 (39 patients, 4.5%). The key independent risk factors for AKI included increased mean platelet volume (MPV) and the volume of intraoperative cryoprecipitate transfusions. The 30-day mortality rate was 3.2%. Kaplan-Meier analysis showed a lower survival rate in the AKI group (89.1%) compared to the non-AKI group (100%, P < 0.001). AKI was notably prevalent following cardiac surgery in this study, significantly impacting survival rates. Notably, MPV and administration of cryoprecipitate may have new considerable predictive significance. Proactive identification and management of high-risk individuals are essential for reducing postoperative complications and mortality.

Clinical Profile and Predictors Affecting Outcome in Community-Acquired Acute Kidney Injury: A 3 Months Follow-Up Study

Background Community-Acquired Acute Kidney Injury (CA-AKI) is often a devastating clinical syndrome allied with high hospital mortality. Moreover, only limited prospective data exist on the outcomes of CA-AKI. Hence, this follow-up study was conducted to assess clinical profiles and the factors affecting outcomes in CA-AKI. Materials and Methods A prospective study enrolling 283 participants was conducted from the year 2021 to 2022. AKI patients defined as per Kidney Disease Improving Global Outcomes (KDIGO) criteria were included. Data were collected on demographics, clinical features, and etiological factors. Patients were followed for three months. Univariate and multinomial analyses were done to predict outcomes. The Cox regression model was fitted to identify predictors of mortality. Results The mean age of patients was 41.67±16.21 years with male predominance. Most of the patients required non-ICU (81.9%) care. Around 36% and 39.6 % of AKI patients were oliguric and required dialysis, respectively. Most patients had a single etiology, with sepsis being the most common cause. Most patients were in KDIGO stage 3, followed by stage 2. At three months of follow-up, 40.6%, 12.3%, and 4.2% had complete, partial, and non-recovery, respectively, and 30.4% died. Age, single etiology, hepatorenal syndrome, sepsis, requirement of mechanical ventilation and vasopressors, comorbidities and glomerulonephritis were significantly associated with mortality. Conclusion CA-AKI is significantly associated with higher mortality, even for those patients who require non-ICU care on presentation. This highlights the pressing need for AKI prevention, early detection, and intervention to mitigate reversible risk factors and optimize clinical outcomes.

Leveraging Quantitative Systems Pharmacology and Artificial Intelligence to advance treatment of Chronic Kidney Disease Mineral Bone Disorder.

Chronic kidney disease mineral bone disorder (CKD-MBD) is a complex clinical syndrome responsible for the accelerated cardiovascular mortality seen in individuals afflicted with CKD. Current approaches to therapy have failed to improve clinical outcomes adequately, likely due to targeting surrogate biochemical parameters as articulated by the guideline developer, KDIGO (Kidney Disease: Improving Global Outcomes). We hypothesized that using a Systems Biology Approach combining machine learning with mathematical modeling, we could test a novel approach to therapy targeting the abnormal movement of mineral out of bone and into soft tissue that is characteristic of CKD-MBD. The mathematical model describes the movement of calcium and phosphate between body compartments in response to standard therapeutic agents. The machine learning technique we applied is Reinforcement Learning (RL). We compared calcium, phosphate, PTH, and mineral movement out of bone and into soft tissue under four scenarios: standard approach (KDIGO), achievement of KDIGO guidelines using RL (RLKDIGO), targeting abnormal mineral flux (RLFLUX), and combining achievement of KDIGO guidelines with minimization of abnormal mineral flux (RLKDIGOFLUX). We demonstrate through simulations that explicitly targeting abnormal mineral flux significantly decreases abnormal mineral movement compared to standard approach while achieving acceptable biochemical outcomes. These investigations highlight the limitations of current therapeutic targets, primarily secondary hyperparathyroidism, and emphasize the central role of deranged phosphate homeostasis in the genesis of the CKD-MBD syndrome.

Pattern of Monthly Percentage of Hemodialysis Children Achieving the KDIGO Recommended Hemoglobin Targets: A Twelve-Month Prospective Study to Assess the Trend of Anemia

Abstract Background Anemia is one of the common problems in children on maintenance hemodialysis (HD). It leads to poor quality of life and when severe, it is associated with cardiovascular dysfunction, cardiomyopathy, and death. Proper treatment of anemia in these patients results in better physical and mental performance. So, our study aimed to assess the trend of anemia among HD children by following the monthly percentage of patients capable of achieving Hb level between 11-12g/dl. Methods For optimum treatment of anemia, the Kidney Disease Improving Global Outcomes (KDIGO) guidelines (2012) recommended to measure Hb every month in HD children targeting monthly Hb concentration of 11-12 g/dl. So, we conducted this 12-months prospective study to assess the trend of anemia among HD children at Pediatric Dialysis Unit of Ain Shams University by following the monthly percentage of patients capable of achieving Hb level between 11-12g/dl. Results This study was done over 12 month-period from April 1st, 2020, till March 31st, 2021. A total of 78 patients were included with a mean age at the time of enrollment in the study of 12.16 ± 3.3 years. They were 45 (57.7%) males and 33 (42.3%) females. All patients were receiving 3 hours every other day HD session for 3 sessions a week with a HD duration range of 3.0 - 140.88 months and a median of 16.51 months. All patients were receiving proper doses of recombinant human erythropoietin (rHuEPO) and intravenous iron therapy. Our study showed that the monthly reported percentages of patients achieved Hb level between 11-12g/dl ranged from 14.7% to 40.8% and that of patients with Hb level &amp;lt;11g/dl ranged between 51.4 – 73.5%. It also revealed statistical evidence of significant association between the presence of anemia in our patients at the time of enrollment in the study and HD durations &amp;lt; 6 months (p &amp;lt; 0.05). Conclusion Despite proper HD treatment and proper doses of recombinant human erythropoietin (rHuEPO) and intravenous iron therapy, anemia is still a prevalent problem among our HD children.

Assessment of a Protocol for Reducing Indwelling Urinary Catheter Usage: Reduced Infection Without Increased Acute Kidney Injury.

Introduction In 2019, a level one trauma center in St. Louis, Missouri launched a campaign to reduce the use of indwelling urinary catheters (IUC) in the trauma population.Our study assesses whether the campaign achieved the intended effect of reducing catheter-associated urinary tract infection (CAUTI) and whether this came at the cost of increased acute kidney injury (AKI). Methods We examined a cohort of patients from before and after the IUC reduction campaign.We compared days with IUC, UTI, CAUTI, and AKI, both recorded in the registry and based on a direct review of laboratory results.Significance testing is performed with the Student's t-test for continuous variablesand Fisher's exact test for categorical variables.For multivariate analysis, multivariate linear regression is used for continuous outcomes, and multivariate logistic regression is used for binary categorical outcomes. Results On average, the post-campaign cohort was older and more severely injured.There was a modest decrease in IUC usage following the campaign, which was significant when adjusted for common trauma covariates, B=-0.93; p=0.04.There were 10 (0.4%) cases of CAUTI in the pre-intervention group versus 0 post-intervention (p=0.002).Pyuria was significantly lower post-intervention: 118 (40.3%) versus 84 (29.3%), p=0.007.This remained significant on multivariate analysis: odds ratio (OR): 0.52, p=0.008.There were no significant differences in creatinine (Cr) absolute values or temporal trends over the course of admission between the cohorts.There was no increased AKI measured by kidney disease improving global outcomes (KDIGO) criteria. Conclusion The IUC reduction protocol was associated with a significant decrease in CAUTI without a significant increase in AKI.

Risk of acute kidney injury after lower urinary tract reconstruction with early NSAID therapy: A propensity matched retrospective analysis

The opioid epidemic response led to increased use of postoperative, non-opioid analgesia. Some pediatric urologists do not routinely use non-steroidal anti-inflammatory drugs (NSAIDs) for fear of causing acute kidney injury (AKI). While previous studies have demonstrated the safety and efficacy of NSAIDs in children, safety after lower urinary tract reconstruction has not been well characterized. ptUsing the Kidney Disease: Improving Global Outcomes (KDIGO) criteria for AKI (increase in creatinine ≥0.3mg/dL or increase in creatinine ≥1.5x baseline or urine output <0.5mL/kg/hr for 6h), we hypothesized there would be a difference in the incidence of postoperative AKI between patients who did and did not receive NSAIDs following surgery. Patients 2-18 years old who underwent lower urinary tract reconstruction (i.e., bladder augmentation and/or creation of a catheterizable channel) from 2009 to 2021 and had documented urine output were retrospectively reviewed. Chronic kidney disease (CKD) stage was calculated from creatinine and cystatin C within 6 months of surgery using the CKiD U25 equations. Patients who received NSAIDs were propensity matched on 11 characteristics with patients undergoing similar surgeries who did not receive NSAIDs. The primary outcome was incidence of AKI within 48h of surgery. The unmatched cohorts included 243 patients. Propensity matching identified 166 patients in the NSAID arm and 41 in the no NSAID arm. 26 patients with CKD stage 2-3 were included. There was no significant difference in the incidence of postoperative AKI based on any KDIGO criteria (17.1% no NSAID versus 16.3% NSAID, p=0.87). Median postoperative opioids fell from 0.88mg/kg in the no NSAID arm to 0.37mg/kg morphine equivalents in the NSAID arm, although this was not statistically significant. Log-rank testing by Kaplan-Meier analysis demonstrated no difference in time to incidence of low urine output between the groups (p=0.32). In the whole population not stratified by NSAID use, no differences were seen in AKI between those with and without CKD (16.7% with versus 17.9% without CKD). There was no difference in the incidence of postoperative AKI among patients who did and did not receive NSAIDs after lower urinary tract reconstruction, excluding those with advanced CKD. These results support that postoperative NSAIDs were an unlikely source of AKI. However, AKI remained a risk following these surgeries, regardless of NSAID use, likely owing to underlying disease, longer operations, and fluid shifts.

Fine-grained subphenotypes in acute kidney injury populations based on deep clustering: Derivation and interpretation

BackgroundAcute kidney injury (AKI) is associated with increased mortality in critically ill patients. Due to differences in the etiology and pathophysiological mechanism, the current AKI criteria put it an embarrassment to evaluate clinical therapy and prognosis. ObjectiveWe aimed to identify subphenotypes based on routinely collected clinical data to expose the unique pathophysiologic patterns. MethodsA retrospective study was conducted based on the Medical Information Mart for Intensive Care IV (MIMIC-IV) and the eICU Collaborative Research Database (eICU-CRD), and a deep clustering approach was conducted to derive subphenotypes. We conducted further analysis to uncover the underlying clinical patterns and interpret the subphenotype derivation. ResultsWe studied 14,189 and 19,382 patients with AKI within 48 h of ICU admission in the two datasets, respectively. Through our approach, we identified seven distinct AKI subphenotypes with mortality heterogeneity in each cohort. These subphenotypes displayed significant variations in demographics, comorbidities, levels of laboratory measurements, and survival patterns. Notably, the subphenotypes could not be effectively characterized using the Kidney Disease: Improving Global Outcomes (KDIGO) criteria alone. Therefore, we uncovered the unique underlying characteristics of each subphenotype through model-based interpretation. To assess the usability of the subphenotypes, we conducted an evaluation, which yielded a micro-Area Under the Receiver Operating Characteristic (AUROC) of 0.81 in the single-center cohort and 0.83 in the multi-center cohort within 48-hour of admission. ConclusionWe derived highly characteristic, interpretable, and usable AKI subphenotypes that exhibited superior prognostic values.

Perioperative risk factors for acute kidney injury in major abdominal surgeries: a retrospective observatioal study

Aims: Acute kidney injury (AKI), particularly as a postoperative complication related to surgery, has been independently associated with morbidity and mortality. AKI also develops at a significant rate after major abdominal surgery. In this study, it was aimed to identify the risk factors contributing to the development of AKI following major abdominal surgery. Methods: The study was retrospectively planned. Patients who underwent major abdominal surgery were included in the study. Patients’ demographic data, preoperative laboratory data, intraoperative data, and postoperative data were recorded from patient files. The diagnosis and severity of postoperative acute kidney injury (PO-AKI) were assessed using serum creatinine and/or urine output criteria in accordance with the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. The patients were divided into two groups: AKI and non-AKI. Results: A total of 64 patients with complete data were included in the study. Among these patients, 6 developed AKI (9.3%). The mean age in the AKI group was found to be statistically significantly higher (p: 0.043). The Frailty index was significantly higher in the AKI group (p: 0.020). Additionally, it was observed that the use of aspirin and angiotensin-converting enzyme inhibitor (ACEI) / angiotensin receptor blocker (ARB) was statistically significantly higher in the AKI group (p: 0.022, p: 0.044, respectively). When patients were evaluated in terms of intraoperative parameters, the amount of colloid used, the amount of ES used, and vasopressor usage were found to be statistically significantly higher in the AKI group (p

The Effects of Early-Phase, Low- or Standard-Intensity Continuous Renal Replacement Therapy on Acid-Base Control and Clinical Outcomes: An Observational Study.

The Kidney Disease Improving Global Outcomes (KDIGO) clinical practice guideline recommends administering an effluent volume of 20-25 mL/kg/h during continuous renal replacement therapy (CRRT) for acute kidney injury. Recent evidence on CRRT initiation showed that less intervention might be beneficial for renal recovery. This study aimed to explore the association between early-phase low CRRT intensity and acid-base balance corrections and clinical outcomes. This was a single-centre, retrospective, observational study at a tertiary intensive care unit (ICU) in Japan. All adult patients requiring CRRT in the ICU were included. Eligible patients were classified into the Low group (dialysate flow rate [QD] 10.0-19.9 mL/kg/h) and the Standard group (QD ≥20 mL/kg/h) by the intensity of CRRT at the beginning. The primary outcomes were acid-base parameters 6 h after CRRT initiation. We used an inverse probability of treatment weighting analysis to estimate the association between the intensity group and the outcomes. Overall, 194 patients were classified into the Low group (n = 144) and the Standard group (n = 50). The Standard group presented with more severe acid-base disturbances, including lower pH and base excess (BE) at baseline. At 6 h after CRRT initiation, pH, BE, and strong ion difference values were comparable, even after adjusting for baseline severity. Despite the efficient correction, no evident differences were observed in clinical outcomes between the two groups. The initial standard intensity appeared to be efficient in correcting acid-base imbalance at the early phase of CRRT; however, further studies are needed to assess the impact on clinical outcomes.

Post-Diarrheal Acute Kidney Injury During an Epidemic in Monsoon – A Retrospective Study from a Tertiary Care Hospital

Background: Acute kidney injury (AKI) is a severe complication of acute diarrheal diseases; however, there is limited data on post-diarrheal AKI (PD-AKI) epidemiology and outcomes. This study aimed to investigate the clinicodemographic profile and outcomes of PD-AKI in our hospital. Materials and Methods: We retrospectively analyzed data from 93 patients admitted with PD-AKI during a diarrheal illness epidemic. Patients were stratified based on the Kidney Disease: Improving Global Outcomes (KDIGO) AKI stage and quick Sequential Organ Failure Assessment (qSOFA) score. Clinicodemographic data and outcomes were recorded and analyzed. Results: The mean age of the patients was 45.7 ± 11.9 years, with a majority being men (n = 55, 59%). All patients presented with watery diarrhea, 85% (n = 79) had vomiting, and 66% (n = 61) presented in shock. At presentation, 59% were oliguric, while 32% were anuric. KDIGO stage 3 AKI was observed in 71% (n = 66) of patients. Dialytic support was required in 29% (n = 27) of cases. The mortality rate was 6.5% (n = 6), mostly due to refractory shock, while the remaining patients recovered. Risk factor analysis demonstrated a higher qSOFA score, and peak serum creatinine levels were associated with an increased likelihood of requiring renal replacement therapy and delayed renal recovery. Conclusion: This study provides valuable insights into the clinicodemographic characteristics and outcomes of PD-AKI. The high prevalence of severe AKI emphasizes the importance of early recognition and appropriate management strategies for these patients.

A multicenter clinical study of critically ill patients with sepsis complicated with acute kidney injury in Beijing: incidence, clinical characteristics and outcomes

To investigate the epidemiological characteristics and prognosis of critically ill patients with sepsis combined with acute kidney injury (AKI) in intensive care unit (ICU) in Beijing, and to analyze the risk factors associated with in-hospital mortality among these critically ill patients. Data were collected from the Beijing AKI Trial (BAKIT) database, including 9 049 patients consecutively admitted to 30 ICUs in 28 tertiary hospitals in Beijing from March 1 to August 31, 2012. Patients were divided into non-AKI and non-sepsis group, AKI and non-sepsis group, non-AKI and sepsis group, AKI and sepsis group. Clinical data recorded included demographic characteristics, primary reasons for ICU admission, comorbidities, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation II(APACHE II) within 24 hours of ICU admission, physiological and laboratory indexes, treatment in the ICU, AKI staging based on the Kidney Disease: Improving Global Outcomes (KDIGO), as well as the prognostic indicators including length of stay in ICU, length of stay in hospital, ICU and in-hospital mortality. The primary endpoint was discharge or in-hospital death. Multivariate Logistic regression analysis was used to investigate the risk factors for hospital death in ICU patients. Kaplan-Meier survival curve was drawn to analyze the cumulative survival of ICU patients during hospitalization. A total of 3 107 critically ill patients were ultimately enrolled, including 1 259 cases in the non-AKI and non-sepsis group, 931 cases in the AKI and non-sepsis group, 264 cases in the non-AKI and sepsis groups, and 653 cases in the AKI and sepsis group. Compared with the other three group, patients in the AKI and sepsis group were the oldest, had the lowest mean arterial pressure (MAP), and the highest APACHE II score, SOFA score, blood urea nitrogen (BUN), and serum creatinine (SCr) levels, and they also had the highest proportion of receiving mechanical ventilation, requiring vasopressor support, and undergoing renal replacement therapy (RRT), all P < 0.01. Of these 3 107 patients, 1 584 (51.0%) were diagnosed with AKI, and the incidence of AKI in patients with sepsis was significantly higher than in those without sepsis [71.2% (653/917) vs. 42.5% (931/2 190), P < 0.01]. The highest proportion of KDIGO 0 stage was observed in the non-sepsis group (57.5%), while the highest proportion of KDIGO 3 stage was observed in the sepsis group (32.2%). Within the same KDIGO stage, the mortality of patients with sepsis was significantly higher than that of non-sepsis patients (0 stage: 17.8% vs. 3.1%, 1 stage: 36.3% vs. 7.4%, 2 stage: 42.7% vs. 17.1%, 3 stage: 54.6% vs. 28.6%, AKI: 46.1% vs. 14.2%). The ICU mortality (38.7%) and in-hospital mortality (46.1%) in the AKI and sepsis group were significantly higher than those in the other three groups. Kaplan-Meier survival curves further showed that the cumulative survival rate of patients with AKI and sepsis during hospitalization was significantly lower than that of the other three groups (53.9% vs. 96.9%, 85.8%, 82.2%, Log-Rank: χ 2 = 379.901, P < 0.001). Subgroup analysis showed that among surviving patients, length of ICU stay and total length of hospital stay were significantly longer in the AKI and sepsis group than those in the other three groups (both P < 0.01). Multivariate regression analysis showed that age, APACHE II score and SOFA score within 24 hours of ICU admission, coronary heart disease, AKI, sepsis, and AKI combined with sepsis were independent risk factors for ICU mortality in patients (all P < 0.05). After adjusting for covariates, AKI, sepsis, and sepsis combined with AKI were significantly associated with higher ICU and in-hospital mortality, with the highest ICU mortality [adjusted odds ratio (OR) = 14.82, 95% confidence interval (95%CI) was 8.10-27.12; Hosmer-Lemeshow test: P = 0.816] and in-hospital mortality (adjusted OR = 7.40, 95%CI was 4.94-11.08; Hosmer-Lemeshow test: P = 0.708) observed in patients with sepsis combined with AKI. The incidence of AKI is high in sepsis patients, and those with both AKI and sepsis have a higher disease burden, more abnormalities in physiological and laboratory indicators, and significantly increased ICU and in-hospital mortality. Among surviving patients, the length of ICU stay and total length of hospital stay are also longer in the AKI and sepsis group. Age, APACHE II score and SOFA score within 24 hours of ICU admission, coronary heart disease, AKI, and sepsis are independent risk factors for in-hospital mortality in ICU patients.

Principles of nutrition in chronic kidney disease in children - a review of the clinical trials and recommendations

Introduction: Children with chronic kidney disease (CKD) require a specialized diet to manage their condition and support healthy growth and development. A proper diet for children with CKD aims to control the intake of certain nutrients, such as protein, lipid, calcium, phosphorus, potassium, sodium, and vitamin D, while ensuring they receive adequate nutrition for growth and development. Aim of the study: This article discusses the epidemiology, causes and pathomechanism of CKD in children. It also presents existing clinical trials and dietary recommendations from societies such as Kidney Disease: Improving Global Outcomes (KDIGO) 2024, Kidney Disease Outcomes Quality Initiative (KDOQI) and Pediatric Renal Nutrition Taskforce (PRNT) and identifies potential sources of selected macronutrients and micronutrients in children's diets. Materials and methods: Comprehensive literature searches were performed across the main electronic databases of PubMed, Google Scholar, KDIGO2024, KDQQI and PRNT recommendations for studies published in the English language about dietary recommendations for children with CKD. Results: The approach to nutrition for children with CKD is still evolving, and specific macronutrient and micronutrient ratios should be established based on the clinical condition, the child's age, and body weight. Care should be taken to ensure that the child's diet is varied, and a healthy eating style should be promoted.

Machine learning for prediction of chronic kidney disease progression: Validation of the Klinrisk model in the CANVAS Program and CREDENCE trial.

To validate the Klinrisk machine learning model for prediction of chronic kidney disease (CKD) progression in patients with type 2 diabetes in the pooled CANVAS/CREDENCE trials. We externally validated the Klinrisk model for prediction of CKD progression, defined as 40% or higher decline in estimated glomerular filtration rate (eGFR) or kidney failure. Model performance was assessed for prediction up to 3 years with the area under the receiver operating characteristic curve (AUC), Brier scores and calibration plots of observed and predicted risks. We compared performance of the model with standard of care using eGFR (G1-G4) and urine albumin-creatinine ratio (A1-A3) Kidney Disease Improving Global Outcomes (KDIGO) heatmap categories. The Klinrisk model achieved an AUC of 0.81 (95% confidence interval [CI] 0.78-0.83) at 1 year, and 0.88 (95% CI 0.86-0.89) at 3 years. The Brier scores were 0.020 (0.018-0.022) and 0.056 (0.052-0.059) at 1 and 3 years, respectively. Compared with the KDIGO heatmap, the Klinrisk model had improved performance at every interval (P < .01). The Klinrisk machine learning model, using routinely collected laboratory data, was highly accurate in its prediction of CKD progression in the CANVAS/CREDENCE trials. Integration of the model in electronic medical records or laboratory information systems can facilitate risk-based care.