Neonatal and Paediatric Heart and Renal Outcomes Network: design of a multi-centre retrospective cohort study

AbstractBackground:Cardiac surgery-associated acute kidney injury is common. In order to improve our understanding of acute kidney injury, we formed the multi-centre Neonatal and Pediatric Heart and Renal Outcomes Network. Our main goals are to describe neonatal kidney injury epidemiology, evaluate variability in diagnosis and management, identify risk factors, investigate the impact of fluid overload, and explore associations with outcomes.Methods:The Neonatal and Pediatric Heart and Renal Outcomes Network collaborative includes representatives from paediatric cardiac critical care, cardiology, nephrology, and cardiac surgery. The collaborative sites and infrastructure are part of the Pediatric Cardiac Critical Care Consortium. An acute kidney injury module was developed and merged into the existing infrastructure. A total of twenty-two participating centres provided data on 100–150 consecutive neonates who underwent cardiac surgery within the first 30 post-natal days. Additional acute kidney injury variables were abstracted by chart review and merged with the corresponding record in the quality improvement database. Exclusion criteria included >1 operation in the 7-day study period, pre-operative renal replacement therapy, pre-operative serum creatinine >1.5 mg/dl, and need for extracorporeal support in the operating room or within 24 hours after the index operation.Results:A total of 2240 neonatal patients were enrolled across 22 centres. The incidence of acute kidney injury was 54% (stage 1 = 31%, stage 2 = 13%, and stage 3 = 9%).Conclusions:Neonatal and Pediatric Heart and Renal Outcomes Network represents the largest multi-centre study of neonatal kidney injury. This new network will enhance our understanding of kidney injury and its complications.

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Long Term Renal Outcomes in Children with Acute Kidney Injury Post-Cardiac Surgery

Kidney International Reports ◽

10.1016/j.ekir.2021.04.018 ◽

2021 ◽

Author(s):

Sidharth Kumar Sethi ◽

Rajesh Sharma ◽

Aditi Gupta ◽

Abhishek Tibrewal ◽

Romel Akole ◽

...

Keyword(s):

Acute Kidney Injury ◽

Cardiac Surgery ◽

Kidney Injury ◽

Renal Outcomes ◽

Post Cardiac Surgery

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Hydroxyethyl Starch 130/0.42 Effect’s on Renal Function in Patients After Cardiac Surgery: A Retrospective Cohort Analysis

10.21203/rs.3.rs-100124/v1 ◽

2020 ◽

Author(s):

Benedict Morath ◽

Andreas Meid ◽

Johannes Rickmann ◽

Jasmin Soethoff ◽

Markus Verch ◽

...

Keyword(s):

Acute Kidney Injury ◽

Renal Function ◽

Cardiac Surgery ◽

Kidney Function ◽

Hydroxyethyl Starch ◽

Retrospective Cohort ◽

Cohort Analysis ◽

Kidney Injury ◽

Retrospective Cohort Analysis ◽

The Impact

Abstract Background: Fluid management is an everyday challenge in intensive care units worldwide. Data from recent trials suggest that the use of hydroxyethyl starch leads to a higher rate of acute kidney injury and mortality in septic patients. Evidence on the safety of hydroxyethyl starch used in postoperative cardiac surgery patients is lacking Methods: The aim was to determine the impact of postoperatively administered hydroxyethylstarch 130/0.42 on renal function and 90-day mortality compared to with or without balanced crystalloids in patients after elective cardiac surgery. A retrospective cohort analysis was performed including 2245 patients undergoing elective coronary artery bypass grafting or, aortic valve replacement, or a combination of both between 2015 - 2019. Acute kidney injury was defined according to the ‘kidney disease improving global outcomes’ criteria. Multivariate logistic regression yielded adjusted associations of postoperative hydroxyethyl starch administration with acute kidney injury during hospital stay and 90-day mortality. Linear mixed-effects models predicted trajectories of estimated glomerular filtration rates over the postoperative period to explore the impact of dosage and timing of hydroxyethyl starch administration.Results: A total of 1009 patients (45.0 %) suffered from acute kidney injury. Significantly less acute kidney injury of any stage occurred in patients receiving hydroxyethyl starch compared to patients receiving only crystalloids for fluid resuscitation (43.7 % vs. 51.2 % p=0.008). In multivariate analysis, the administration of hydroxyethyl starch showed a protective effect (OR 0.89 95% confidence interval (CI) (0.82-0.96)) which was less prominent in patients receiving only crystalloids (OR 0.98, 95% CI (0.95-1.00)). No association between hydroxyethyl starch and 90-day mortality (OR 1.05 95% CI (0.88-1.25)) was detected. Renal function trajectories were dose-dependent and biphasic and hydroxyethyl starch could even slow down the late postoperative decline of kidney function.Conclusion: This study showed no association between hydroxyethyl starch and the postoperative occurrence of acute kidney injury and may add evidence to the discussion about the use of hydroxyethyl starch in cardiac surgery patients. In addition, hydroxyethyl starch administered early after surgery in adequate low doses might even prevent the decline of the kidney function after cardiac surgery.

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Impact of Early versus Late Initiation of Renal Replacement Therapy in Patients with Cardiac Surgery-Associated Acute Kidney Injury: Meta-Analysis with Trial Sequential Analysis of Randomized Controlled Trials

BioMed Research International ◽

10.1155/2018/6942829 ◽

2018 ◽

Vol 2018 ◽

pp. 1-13

Author(s):

Jie Cui ◽

Da Tang ◽

Zhen Chen ◽

Genglong Liu

Keyword(s):

Acute Kidney Injury ◽

Cardiac Surgery ◽

Sequential Analysis ◽

Meta Analysis ◽

Kidney Injury ◽

Early Initiation ◽

Trial Sequential Analysis ◽

Initiation Time ◽

Late Initiation ◽

The Impact

Background. Previous studies have examined the effect of the initiation time of renal replacement therapy (RRT) in patients with cardiac surgery-associated acute kidney injury (CSA-AKI), but the findings remain controversial. The aim of this meta-analysis was to systematically and quantitatively compare the impact of early versus late initiation of RRT on the outcome of patients with CSA-AKI.Methods. Four databases (PubMed, the Cochrane Library, ISI Web of Knowledge, and Embase) were systematically searched from inception to June 2018 for randomized clinical trials (RCTs). Two investigators independently performed the literature search, study selection, data extraction, and quality evaluation. Meta-analysis and trial sequential analysis (TSA) were used to examine the impact of RRT initiation time on all-cause mortality (primary outcome). The Grading of Recommendations Assessment Development and Evaluation (GRADE) was used to evaluate the level of evidence.Results. We identified 4 RCTs with 355 patients that were eligible for inclusion. Pooled analyses indicated no difference in mortality for patients receiving early and late initiation of RRT (relative risk [RR] = 0.61, 95% confidence interval [CI] = 0.33 to 1.12). However, the results were not confirmed by TSA. Similarly, early RRT did not reduce the length of stay (LOS) in the intensive care unit (ICU) (mean difference [MD] = -1.04; 95% CI = -3.34 to 1.27) or the LOS in the hospital (MD = -1.57; 95% CI = -4.62 to 1.48). Analysis using GRADE indicated the certainty of the body of evidence was very low for a benefit from early initiation of RRT.Conclusion. Early initiation of RRT had no beneficial impacts on outcomes in patients with CSA-AKI. Future larger and more adequately powered prospective RCTs are needed to verify the benefit of reduced mortality associated with early initiation of RRT.Trial Registration. This trial is registered with PROSPERO registration number CRD42018084465, registered on 11 February 2018.

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The KDIGO acute kidney injury guidelines for cardiac surgery patients in critical care: a validation study

BMC Nephrology ◽

10.1186/s12882-018-0946-x ◽

2018 ◽

Vol 19 (1) ◽

Cited By ~ 6

Author(s):

Samuel H. Howitt ◽

Stuart W. Grant ◽

Camila Caiado ◽

Eric Carlson ◽

Dowan Kwon ◽

...

Keyword(s):

Acute Kidney Injury ◽

Critical Care ◽

Cardiac Surgery ◽

Validation Study ◽

Kidney Injury

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Comparison of predication of Acute Kidney Injury after cardiac surgery by health care providers versus the biomarker [TIMP-2]*[IGFBP7] and scoring systems. Protocol for a prospective single center observational study (PREDICTAKI)

10.1101/2020.07.13.20148643 ◽

2020 ◽

Author(s):

Wim Vandenberghe ◽

Lien Van Laethem ◽

Alexander Zarbock ◽

Melanie Meersch ◽

Eric A.J. Hoste

Keyword(s):

Acute Kidney Injury ◽

Cardiac Surgery ◽

Healthcare Providers ◽

Kidney Injury ◽

List Type ◽

Care Providers ◽

Single Center ◽

Single Center Study ◽

The Impact ◽

Center Study

AbstractIntroductionAcute kidney injury occurs in up to one third of patients after cardiac surgery and is an important contributor for adverse outcome. Previous research has demonstrated the benefit of a bundle of preventive measurements to reduce AKI in a subgroup of patients with high risk for AKI development. Urinary stress biomarkers [TIMP-2]*[IGFBP7] are used to identify these patients who are at risk for AKI. The trial aims to investigate the potential discrepancy between biomarker results and clinical estimation of occurrence of AKI on ICU in clinical practice.Methods and analysisWe plan to include 100 adult patients after cardiac surgery with cardiopulmonary bypass in a prospective, single center clinical trial. After cardiac surgery, different type of healthcare professional in ICU will provide a prediction of AKI occurrence and severity in the next 48 hours by filling in a questionnaire just before and after [TIMP-2]*[IGFBP7] biomarker analysis. Primary, this trial investigates the potential discrepancy in AKI prediction between clinical estimation by healthcare providers, biomarker results, and previous described score systems. Secondly, the impact of knowledge of the biomarker result on the quality of prediction by healthcare providers will be evaluated.Ethics and disseminationThis prospective, single center study has been approved by the medical ethical committee of the Ghent University Hospital (28th May 2019, trial registration number B670201939991). Informed consent was obtained for patients and healthcare providers.Summary strength and limitations-Influence of knowledge of a kidney biomarker on healthcare providers’ assessment of risk for AKI in clinical setting-Different types of healthcare providers with various expertise-It is a single center study with limited number of patients

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Machine Learning for the Prediction of Progression in Patients with Acute Kidney Injury in Critical Care

10.21203/rs.3.rs-412422/v1 ◽

2021 ◽

Author(s):

Lifan Zhang ◽

Canzheng Wei ◽

Yunxia Feng ◽

Aijia Ma ◽

Yan Kang

Keyword(s):

Machine Learning ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Critical Care ◽

Intensive Care ◽

Logistic Regression Model ◽

Kidney Injury ◽

Gradient Boosting ◽

Extreme Gradient Boosting ◽

Stage 1

Abstract Background: Acute kidney injury (AKI) is a serve and harmful syndrome in the intensive care unit. The purpose of this study is to develop a prediction model that predict whether patients with AKI stage 1/2 will progress to AKI stage 3. Methods: Patients with AKI stage 1/2, when they were ﬁrst diagnosed with AKI in the Medical Information Mart for Intensive Care (MIMIC-III), were included. We excluded patients who had underwent RRT or progressed to AKI stage 3 within 72 hours of the ﬁrst AKI diagnosis. We also excluded patients with chronic kidney disease (CKD). We used the Logistic regression and machine learning extreme gradient boosting (XGBoost) to build two models which can predict patients who will progress to AKI stage 3. Established models were evaluated by cross-validation, receiver operating characteristic curve (ROC), and precision-recall curves (PRC). Results: We included 25711 patients, of whom 2130 (8.3%) progressed to AKI stage 3. Creatinine, multiple organ failure syndromes (MODS), blood urea nitrogen (BUN), sepsis, and respiratory failure were the most important in AKI progression prediction. The XGBoost model has a better performance than the Logistic regression model on predicting AKI stage 3 progression (AU-ROC, 0.926; 95%CI, 0.917 to 0.931 vs. 0.784; 95%CI, 0.771 to 0.796, respectively). Conclusions: The XGboost model can better identify patients with AKI progression than Logistic regression model. Machine learning techniques may improve predictive modeling in medical research. Keywords: Acute kidney injury; Critical care; Logistic Models; Extreme gradient boosting

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Stage 1 acute kidney injury is independently associated with infection following cardiac surgery

Journal of Thoracic and Cardiovascular Surgery ◽

10.1016/j.jtcvs.2019.11.004 ◽

2019 ◽

Cited By ~ 3

Author(s):

Benjamin R. Griffin ◽

J. Pedro Teixeira ◽

Sophia Ambruso ◽

Michael Bronsert ◽

Jay D. Pal ◽

...

Keyword(s):

Acute Kidney Injury ◽

Cardiac Surgery ◽

Kidney Injury ◽

Stage 1

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Acute kidney injury: a COVID-19 update

Journal of Kidney Care ◽

10.12968/jokc.2021.6.1.31 ◽

2021 ◽

Vol 6 (1) ◽

pp. 31-34

Author(s):

Claire Main

Keyword(s):

Acute Kidney Injury ◽

Critical Care ◽

Board Member ◽

Major Trauma ◽

Kidney Injury ◽

Health Board ◽

Executive Board ◽

The Impact

Claire Main, Interim Manager of Critical Care and Major Trauma at Cardiff and Vale University Health Board and ANN UK executive board member, gives an update on acute kidney injury and the impact of the COVID-19 pandemic

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