scholarly journals Early-Phase Urine Output and Severe-Stage Progression of Oliguric Acute Kidney Injury in Critical Care

2021 ◽  
Vol 8 ◽  
Author(s):  
Haoquan Huang ◽  
Xiaohui Bai ◽  
Fengtao Ji ◽  
Hui Xu ◽  
Yanni Fu ◽  
...  
Keyword(s):  
Critical Care ◽  
Early Phase ◽  
Inflection Point ◽  
Kidney Injury ◽  
Stage Progression ◽  
Severe Stage ◽  
Subgroup Analyses ◽  
Progression Risk ◽  
Stage 1 ◽  
The Relationship

Background: The relationship between urine output (UO) and severe-stage progression in the early phase of acute kidney injury (AKI) remains unclear. This study aimed to investigate the relationship between early-phase UO6−12h [UO within 6 h after diagnosis of stage 1 AKI by Kidney Disease: Improving Global Outcomes (KDIGO) UO criteria] and severe-stage progression of AKI and to identify a reference value of early-phase UO6−12h for guiding initial therapy in critical care.Methods: Adult patients with UO < 0.5 ml/kg/h for the first 6 h after intensive care unit (ICU) admission (meeting stage 1 AKI by UO) and UO6−12h ≥ 0.5 ml/kg/h were identified from the Medical Information Mart for Intensive Care (MIMIC) III database. The primary outcome was progression to stage 2/3 AKI by UO. After other variables were adjusted through multivariate analysis, generalized additive model (GAM) was used to visualize the relationship between early-phase UO6−12h and progression to stage 2/3 AKI by UO. A two-piecewise linear regression model was employed to identify the inflection point of early-phase UO6−12h above which progression risk significantly leveled off. Sensitivity and subgroup analyses were performed to assess the robustness of our findings.Results: Of 2,984 individuals, 1,870 (62.7%) with KDIGO stage 1 UO criteria progressed to stage 2/3 AKI. In the multivariate analysis, early-phase UO6−12h showed a significant association with progression to stage 2/3 AKI by UO (odds ratio, 0.40; 95% confidence interval, 0.34–0.46; p < 0.001). There was a non-linear relationship between early-phase UO6−12h and progression of AKI. Early-phase UO6−12h of 1.1 ml/kg/h was identified as the inflection point, above which progression risk significantly leveled off (p = 0.780). Patients with early-phase UO6−12h ≥ 1.1 ml/kg/h had significantly shorter length of ICU stay (3.82 vs. 4.17 days, p < 0.001) and hospital stay (9.28 vs. 10.43 days, p < 0.001) and lower 30-day mortality (11.05 vs. 18.42%, p < 0.001). The robustness of our findings was confirmed by sensitivity and subgroup analyses.Conclusions: Among early-stage AKI patients in critical care, there was a non-linear relationship between early-phase UO6−12h and progression of AKI. Early-phase UO6−12h of 1.1 ml/kg/h was the inflection point above which progression risk significantly leveled off.

scholarly journals Early-phase cumulative hypotension duration and severe-stage progression in oliguric acute kidney injury with and without sepsis: an observational study

Critical Care ◽  
2016 ◽  
Vol 20 (1) ◽  
Author(s):  
Junichi Izawa ◽  
Tetsuhisa Kitamura ◽  
Taku Iwami ◽  
Shigehiko Uchino ◽  
Masanori Takinami ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Observational Study ◽  
Early Phase ◽  
Kidney Injury ◽  
Stage Progression ◽  
Severe Stage

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

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

MO364ASSOCIATION OF AKI-EVENT DEFINED BY DIFFERENT DEFINITIONS WITH IN-HOSPITAL MORTALITY

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Fateme Nateghi ◽  
Konstantinos Makris ◽  
Pierre Delanaye ◽  
Hans Pottel
Keyword(s):  
Logistic Regression ◽  
Hospital Mortality ◽  
Hospital Admissions ◽  
Kidney Injury ◽  
Relative Increase ◽  
Local Health ◽  
Absolute Increase ◽  
Severe Stage ◽  
Stage 1 ◽  
The Impact

Abstract Background and Aims Studies have shown that millions of hospitalized patients suffer from Acute Kidney Injury (AKI) per year which increases mortality risk for these patients. Different definitions for AKI have been proposed during the past years such as RIFLE (2002) and AKIN (2004). In 2012, KDIGO published a clinical practice guideline harmonizing AKIN and RIFLE into one general guideline which classifies AKI into 3 stages, where stage 1 is defined as an absolute increase of SCr ≥ 0.3 mg/dl over 48 hours or a relative increase in SCr ≥ 50% from baseline within the previous 7 days. A recent study [Sparrow et al., 2019] evaluated the impact of further categorizing AKI stage 1 into 2 stages based on SCr criteria. The study separates KDIGO AKI stage 1 and AKIN stage 1 into 2 stages (KDIGO-4 and AKIN-4) based on the different SCr criteria. Having different AKI definitions makes it challenging to analyze AKI incidence and associated outcomes among studies. The present study aimed to investigate the incidence of AKI events defined by 4 different definitions (standard AKIN and KDIGO, and modified AKIN-4 and KDIGO-4) and its association with in-hospital mortality. Method Retrospective clinical data available for all adult (≥18 years old) hospital admissions to a local health district in Athens, Greece between October 1999 and March 2019 was used in the analysis. We excluded patients whose time between admission and discharge was less than 7 days. Also, patients with less than 5 Scr measurements were omitted from the analysis resulting in the final cohort of 7242 admissions. We used the AKIN, KDIGO, AKIN-4, and KDIGO-4 definitions to check the incidence of AKI. As our second goal, we assessed associations of AKI-events with in-hospital mortality, adjusted for characteristics (age, sex, AKI staging) using multivariable logistic regression. Results The incidence of in-hospital AKI using the modified KDIGO-4 was 6.72% for stage 1a, 15.71% for stage 1b, 8.06% for stage 2, and 2.97% for stage 3; however, these percentages for AKIN-4 were 11.5%, 5.83%,1.75%, and 0.33% for stage 1a, stage 1b, stage 2, and stage 3, respectively. Using the standard KDIGO and AKIN definition, 19.08 and 14.05 % developed stage 1, respectively. To find the association between AKI stages and in-hospital mortality, we considered the most severe stage of AKI reached by a patient. Results of logistic regression models show that in-hospital mortality increased as the stage of AKI events increased for both KDIGO-4 and AKIN-4 (Table 1). Table 2 shows the same results using the original KDIGO and AKIN definitions. Conclusion The results of both definitions (AKIN-4 and KDIGO-4) show a significant association with mortality, but KDIGO-4 has a larger odds ratio meaning that AKI classification based on KDIGO-4 has a stronger association with mortality than AKI classification based on AKIN-4. However, based on our results, splitting stage 1 to stage 1a and stage 1b does not seem to make a difference; hence, using KDIGO-4 as a replacement for KDIGO would not have a significant impact on capturing AKI events.

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

2019 ◽  
Vol 29 (4) ◽  
pp. 511-518 ◽  
Author(s):  
Katja M. Gist ◽  
Joshua J. Blinder ◽  
David Bailly ◽  
Santiago Borasino ◽  
David J. Askenazi ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Critical Care ◽  
Cardiac Surgery ◽  
Kidney Injury ◽  
Multi Centre Study ◽  
Renal Outcomes ◽  
Stage 1 ◽  
The Impact ◽  
Neonatal Kidney ◽  
Cardiac Critical Care

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.

scholarly journals Fatal Outcomes of COVID-19 in Patients with Severe Acute Kidney Injury

2020 ◽  
Vol 9 (6) ◽  
pp. 1718 ◽  
Author(s):  
Jeong-Hoon Lim ◽  
Sun-Hee Park ◽  
Yena Jeon ◽  
Jang-Hee Cho ◽  
Hee-Yeon Jung ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Distress Syndrome ◽  
Kidney Injury ◽  
Organ Damage ◽  
Acute Kidney Injury Network ◽  
Medical Data ◽  
Independent Risk Factors ◽  
Stage 1 ◽  
The Relationship ◽  
Low Serum

The outcome of coronavirus disease 2019 (COVID-19) is associated with organ damage; however, the information about the relationship between acute kidney injury (AKI) and COVID-19 is still rare. We evaluated the clinical features and prognosis of COVID-19 patients with AKI according to the AKI severity. Medical data of hospitalized COVID-19 patients in two university-based hospitals during an outbreak in Daegu, South Korea, were retrospectively analyzed. AKI and its severity were defined according to the Acute Kidney Injury Network. Of the 164 hospitalized patients with COVID-19, 30 patients (18.3%) had AKI; 14, 4, and 12 patients had stage 1, 2, and 3, respectively. The median age was significantly higher in AKI patients than in non-AKI patients (75.5 vs. 67.0 years, p = 0.005). There were 17 deaths (56.7%) among AKI patients; 4 (28.6%), 1 (25.0%), and 12 (100.0%), respectively. In-hospital mortality was higher in AKI patients than in non-AKI patients (56.7% vs. 20.8%, p < 0.001). After adjusting for potential confounding factors, stage 3 AKI was associated with higher mortality than either non-AKI or stage 1 AKI (hazard ratio (HR) = 3.62 (95% confidence interval (CI) = 1.75–7.48), p = 0.001; HR = 15.65 (95% CI = 2.43–100.64), p = 0.004). Among the AKI patients, acute respiratory distress syndrome and low serum albumin on admission were considered independent risk factors for stage 3 AKI (both p < 0.05). Five patients with stage 3 AKI underwent dialysis and eventually died. In conclusion, COVID-19 patients with severe AKI had fatal outcomes.

scholarly journals Body Mass Index Is Associated with the Severity and All-Cause Mortality of Acute Kidney Injury in Critically Ill Patients: An Analysis of a Large Critical Care Database

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Benji Wang ◽  
Diwen Li ◽  
Yuqiang Gong ◽  
Binyu Ying ◽  
Bihuan Cheng ◽  
...  
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Proportional Hazards ◽  
Kidney Injury ◽  
Cox Proportional Hazards ◽  
Overweight And Obesity ◽  
Obese Patients ◽  
Subgroup Analyses ◽  
All Cause Mortality ◽  
The Relationship

Background. Acute kidney injury (AKI) is a common clinical syndrome carrying high morbidity and mortality. Body mass index (BMI) is a common health indicator, and a high BMI value-obesity has been shown to be associated with the outcomes of several diseases. However, the relationship between different BMI categories and mortality in all critically ill patients with AKI is unclear and needs further investigation. Therefore, we evaluated the ability of BMI to predict the severity and all-cause mortality of AKI in critically ill patients. Methods. We extracted clinical data from the MIMIC-III v1.4 database. All adult patients with AKI were initially screened. The baseline data extracted within 24 hours after ICU admission were presented according to WHO BMI categories. Logistic regression models and the Cox proportional hazards models were, respectively, constructed to assess the relationship between BMI and the severity and all-cause mortality of AKI. The generalized additive model (GAM) was used to identify nonlinear relationships as BMI was a continuous variable. The subgroup analyses were performed to further analyze the stability of the association between BMI category and 365-day all-cause mortality of AKI. Result. A total of 15,174 patients were extracted and were divided into four groups according to BMI. Obese patients were more likely to be young and male. In the fully adjusted logistic regression model, we found that overweight and obesity were significant predictors of AKI stage III (OR, 95 CI: 1.17, 1.05–1.30; 1.32, 1.18–1.47). In the fully adjusted Cox proportional hazards model, overweight and obesity were associated with significantly lower 30-day, 90-day, and 365-day all-cause mortality. The corresponding adjusted HRs (95 CIs) for overweight patients were 0.87 (0.77, 0.99), 0.84 (0.76, 0.93), and 0.80 (0.74, 0.88), and for obese patients, they were 0.87 (0.77, 0.98), 0.79 (0.71, 0.88), and 0.73 (0.66, 0.80), respectively. The subgroup analyses further presented a stable relationship between BMI category and 365-day all-cause mortality. Conclusions. BMI was independently associated with the severity and all-cause mortality of AKI in critical illness. Overweight and obesity were associated with increased risk of AKI stage III; however, they were predictive of a relatively lower mortality risk in these patients.

scholarly journals Acute Kidney Injury in Critical Care COVID-19 Patients on Invasive Mechanical Ventilation: The Potential Preventive Role of Dexamethasone

2022 ◽  
Author(s):  
Olynka Vega Vega
Keyword(s):  
Mechanical Ventilation ◽  
Acute Kidney Injury ◽  
Critical Care ◽  
Lower Incidence ◽  
Cox Regression ◽  
Invasive Mechanical Ventilation ◽  
Kidney Injury ◽  
Dexamethasone Treatment ◽  
Cox Regression Analysis ◽  
Severe Stage

Abstract Background. A high incidence of acute kidney injury (AKI) has been reported in COVID-19 patients in critical care units and those undergoing invasive mechanical ventilation (IMV). The introduction of dexamethasone as treatment for severe COVID-19 has improved mortality, but its effects in other organs remain under study. Methods. In this prospective observational cohort study, we evaluated the incidence of AKI in critically ill COVID-19 patients undergoing mechanical ventilation, and the association of dexamethasone treatment with the incidence, severity, and outcomes of AKI. The association between dexamethasone treatment and AKI was evaluated by multivariate logistic regression. The association of the combination of dexamethasone treatment and AKI on mortality was evaluated by Cox-regression analysis. Results. We included 552 patients. AKI was diagnosed in 311 (56%), of which 196 (63%) corresponded to severe (stage 2 or 3) AKI, and 46 (14.8%) received renal replacement therapy (RRT). Two hundred and sixty-seven (48%) patients were treated with dexamethasone. This treatment was associated to lower incidence of AKI (OR 0.34, 95%CI 0.22-0.52, p<0.001) after adjusting for age, body mass index, laboratory parameters, SOFA score, and vasopressor use. Dexamethasone treatment significantly reduced mortality in patients with severe AKI (HR 0.63, 95%CI 0.41-0.96, p=0.032). Conclusions. The incidence of AKI is high in COVID-19 patients under IMV. Dexamethasone treatment is associated with a lower incidence of AKI and a lower mortality in the group with severe AKI.

scholarly journals Renal replacement therapy in critical care in patients with acute kidney injury

2018 ◽  
Vol 51 (2) ◽  
pp. 141-148
Author(s):  
Shigeo Negi ◽  
Daisuke Koreeda ◽  
Masaki Higashiura ◽  
Takuro Yano ◽  
Sou Kobayashi ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Critical Care ◽  
Renal Replacement Therapy ◽  
Replacement Therapy ◽  
Kidney Injury

scholarly journals Plasma angiopoietin-2 is associated with age-related deficits in cognitive sub-scales in Ugandan children following severe malaria

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Benson J. Ouma ◽  
Paul Bangirana ◽  
John M. Ssenkusu ◽  
Dibyadyuti Datta ◽  
Robert O. Opoka ◽  
...  
Keyword(s):  
Severe Malaria ◽  
Parental Education ◽  
Preschool Education ◽  
Kidney Injury ◽  
Malaria Episode ◽  
Enzyme Linked Immunosorbent Assay ◽  
Testing Time ◽  
Age Related ◽  
Angiopoietin 2 ◽  
The Relationship

Abstract Background Elevated angiopoietin-2 (Angpt-2) concentrations are associated with worse overall neurocognitive function in severe malaria survivors, but the specific domains affected have not been elucidated. Methods Ugandan children with severe malaria underwent neurocognitive evaluation a week after hospital discharge and at 6, 12 and 24 months follow-up. The relationship between Angpt-2 concentrations and age-adjusted, cognitive sub-scale z-scores over time were evaluated using linear mixed effects models, adjusting for disease severity (coma, acute kidney injury, number of seizures in hospital) and sociodemographic factors (age, gender, height-for-age z-score, socio-economic status, enrichment in the home environment, parental education, and any preschool education of the child). The Mullen Scales of Early Learning was used in children < 5 years and the Kaufman Assessment Battery for Children 2nd edition was used in children ≥ 5 years of age. Angpt-2 levels were measured on admission plasma samples by enzyme-linked immunosorbent assay. Adjustment for multiple comparisons was conducted using the Benjamini–Hochberg Procedure of False Discovery Rate. Results Increased admission Angpt-2 concentration was associated with worse outcomes in all domains (fine and gross motor, visual reception, receptive and expressive language) in children < 5 years of age at the time of severe malaria episode, and worse simultaneous processing and learning in children < 5 years of age at the time of severe malaria who were tested when ≥ 5 years of age. No association was seen between Angpt-2 levels and cognitive outcomes in children ≥ 5 years at the time of severe malaria episode, but numbers of children and testing time points were lower for children ≥ 5 years at the time of severe malaria episode. Conclusion Elevated Angpt-2 concentration in children with severe malaria is associated with worse outcomes in multiple neurocognitive domains. The relationship between Angpt-2 and worse cognition is evident in children < 5 years of age at the time of severe malaria presentation and in selected domains in older years.

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