Obesity and recovery from acute kidney injury (Ob AKI): a prospective cohort feasibility study

Risk factors and outcome variables of cardiorenal syndrome type 1 from the nephrologist's perspective

Background and aim

In cardiorenal syndrome (CRS) type 1, acute cardiac failure or acute decompensation of chronic heart failure causes acute kidney injury (AKI). Every individual AKI episode increases the risk for chronic kidney disease (CKD) in the long term. In this study, we aimed to evaluate epidemiological characteristics and outcome variables of CRS type 1 individuals from the nephrologist’s perspective.

Methods

The study was performed in a retrospective, observational manner. All AKI patients treated at the Brandenburg Hospital of the Medical School of Brandenburg between January and December 2019 were screened for diagnostic criteria of CRS type 1. Endpoints were in-hospital death, need for dialysis, and renal recovery.

Results

During the screening, 198 out of 1189 (16.6%) AKI subjects were assigned to the diagnosis CRS type 1. The overall in-hospital mortality was 19.2%; 9.6% of the patients required dialysis due to AKI. Complete recovery of kidney function was observed in 86 individuals (43.4%); incomplete recovery occurred in 55 patients (27.8%). Mortality-predictive variables were AKIN stage 2, longer ICU treatment, and insulin-dependent diabetes. Regarding dialysis, AKIN stage 3 and higher potassium at the time of diagnosis were predictive. Subjects with longer in-hospital stay recovered more often from CRS type 1.

Conclusions

The incidence of CRS type 1 is high (∼16% of all in-hospital AKI subjects) and the mortality is higher than the average mortality of AKI in general. At the same time, complete recovery of kidney function occurs less frequent. The kidney-related follow-up management of CRS type 1 needs to be significantly optimized to improve the long-term outcome of affected patients.

The Impact of Obesity on Renal Trauma Outcome: An Analysis of the National Trauma Data Bank from 2013 to 2016

BACKGROUND

The obesity paradox has been recently demonstrated in trauma patients, where improved survival was associated with overweight and obese patients compared to patients with normal weight, despite increased morbidity. Little is known whether this effect is mediated by lower injury severity. We aim to explore the association between body mass index (BMI) and renal trauma injury grade, morbidity, and in-hospital mortality.

METHODS

A retrospective cohort of adults with renal trauma was conducted using 2013-2016 National Trauma Data Bank. Multiple regression analyses were used to assess outcomes of interest across BMI categories with normal weight as reference, while adjusting for relevant covariates including kidney injury grade.

RESULTS

We analyzed 15181 renal injuries. Increasing BMI above normal progressively decreased the risk of high-grade renal trauma (HGRT). Subgroup analysis showed that this relationship was maintained in blunt injury, but there was no association in penetrating injury. Overweight (OR 1.02, CI 0.83-1.25, p = 0.841), class I (OR 0.92, CI 0.71-1.19, p = 0.524), and class II (OR 1.38, CI 0.99-1.91, p = 0.053) obesity were not protective against mortality, whereas class III obesity (OR 1.46, CI 1.03-2.06, p = 0.034) increased mortality odds. Increasing BMI by category was associated with a stepwise increase in odds of acute kidney injury, cardiovascular events, total hospital length of stay (LOS), intensive care unit LOS, and ventilator days.

CONCLUSIONS

Increasing BMI was associated with decreased risk of HGRT in blunt trauma. Overweight and obesity were associated with increased morbidity but not with a protective effect on mortality. The obesity paradox does not exist in kidney trauma when injury grade is accounted for.

Body mass index and chronic kidney disease outcomes after acute kidney injury: a prospective matched cohort study

BACKGROUND

Acute kidney injury (AKI) and obesity are independent risk factors for chronic kidney disease (CKD). This study aimed to determine if obesity modifies risk for CKD outcomes after AKI.

METHODS

This prospective multisite cohort study followed adult survivors after hospitalization, with or without AKI. The primary outcome was a combined CKD event of incident CKD, progression of CKD and kidney failure, examined using time-to-event Cox proportional hazards models, adjusted for diabetes status, age, pre-existing CKD, cardiovascular disease status and intensive care unit admission, and stratified by study center. Body mass index (BMI) was added as an interaction term to examine effect modification by body size.

RESULTS

The cohort included 769 participants with AKI and 769 matched controls. After median follow-up of 4.3 years, among AKI survivors, the rate of the combined CKD outcome was 84.7 per1000-person-years with BMI ≥30 kg/m2, 56.4 per 1000-person-years with BMI 25-29.9 kg/m2, and 72.6 per 1000-person-years with BMI 20-24.9 kg/m2. AKI was associated with a higher risk of combined CKD outcomes; adjusted-HR 2.43 (95%CI 1.87-3.16), with no evidence that this was modified by BMI (p for interaction = 0.3). After adjustment for competing risk of death, AKI remained associated with a higher risk of the combined CKD outcome (subdistribution-HR 2.27, 95%CI 1.76-2.92) and similarly, there was no detectable effect of BMI modifying this risk.

CONCLUSIONS

In this post-hospitalization cohort, we found no evidence for obesity modifying the association between AKI and development or progression of CKD.

Prospective model for predicting renal recovery in cardiac surgery patients with acute kidney injury requiring renal replacement therapy

Aim

To develop a model for predicting renal recovery in cardiac surgery patients with acute kidney injury (AKI) requiring renal replacement therapy (RRT).

Methods

Data from a prospective randomized controlled trial, conducted in a tertiary hospital to compare the survival effect of two dosages of hemofiltration for continuous RRT in cardiac surgery patients between 20 March 2012 and 9 August 2015, were used to develop the model. The outcome was renal recovery defined as alive and dialysis‐free 90 days after RRT initiation. Multivariate logistic regression with a stepwise backward selection of variables based on Akaike Information Criterion was applied to develop the model, which was internally validated using bootstrapping. Model discrimination, calibration and clinical value were assessed using the concordance index (C‐Index), calibration plots and decision curve analysis, respectively.

Results

Totally, 211 patients with AKI requiring RRT (66.8% male) with median age of 57 years were included. The incidence of renal recovery was 33.2% (n = 70). The model included six variables: body mass index stratification, baseline estimated glomerular filtration rate, hypertension, sepsis, mean arterial pressure and mechanical ventilation. The C‐Index for this model was 0.807 (95% CI, 0.744–0.870). After correction by the bootstrap, the C‐Index was 0.780 (95% CI, 0.720–0.845). The calibration plots indicated good consistency between actual observations and model prediction of renal recovery. Decision curve analysis demonstrated the model was clinical usefulness.

Conclusion

We developed and validated a model to predict the chance of renal recovery in cardiac surgery patients with AKI requiring RRT.

This validated model based on prospective cohort data to predict the chance of renal recovery in cardiac surgery patients, especially after acute dialysis provides values to alert clinical decision and information for post AKI care.

Prediction Models for AKI in ICU: A Comparative Study

PURPOSE

To assess the performance of models for early prediction of acute kidney injury (AKI) in the Intensive Care Unit (ICU) setting.

PATIENTS AND METHODS

Data were collected from the Medical Information Mart for Intensive Care (MIMIC)-III database for all patients aged ≥18 years who had their serum creatinine (SCr) level measured for 72 h following ICU admission. Those with existing conditions of kidney disease upon ICU admission were excluded from our analyses. Seventeen predictor variables comprising patient demographics and physiological indicators were selected on the basis of the Kidney Disease Improving Global Outcomes (KDIGO) and medical literature. Six models from three types of methods were tested: Logistic Regression (LR), Support Vector Machines (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Decision Machine (LightGBM), and Convolutional Neural Network (CNN). The area under receiver operating characteristic curve (AUC), accuracy, precision, recall and F-measure (F1) were calculated for each model to evaluate performance.

RESULTS

We extracted the ICU records of 17,205 patients from MIMIC-III dataset. LightGBM had the best performance, with all evaluation indicators achieving the highest value (average AUC = 0.905, F1 = 0.897, recall = 0.836). XGBoost had the second best performance and LR, RF, SVM performed similarly (P = 0.082, 0.158 and 0.710, respectively) on AUC. The CNN model achieved the lowest score for accuracy, precision, F1 and AUC. SVM and LR had relatively low recall compared with that of the other models. The SCr level had the most significant effect on the early prediction of AKI onset in LR, RF, SVM and LightGBM.

CONCLUSION

LightGBM demonstrated the best capability for predicting AKI in the first 72 h of ICU admission. LightGBM and XGBoost showed great potential for clinical application owing to their high recall value. This study can provide references for artificial intelligence-powered clinical decision support systems for AKI early prediction in the ICU setting.

Individualized acute kidney injury after care

PURPOSE OF REVIEW

The aim of this study was to summarize the current evidence around the impact of individualizing patient care following an episode of acute kidney injury (AKI) in the ICU.

RECENT FINDINGS

Over the last years, evidence has demonstrated that the follow-up care after episodes of AKI is lacking and standardization of this process is likely needed. Although this is informed largely by large retrospective cohort studies, a few prospective observational trials have been performed. Medication reconciliation and patient/caregiver education are important tenants of follow-up care, regardless of the severity of AKI. There is evidence the initiation and/or reinstitution of renin-angiotensin-aldosterone agents may improve patient's outcomes following AKI, although they may increase the risk for adverse events, especially when reinitiated early. In addition, 3 months after an episode of AKI, serum creatinine and proteinuria evaluation may help identify patients who are likely to develop progressive chronic kidney disease over the ensuing 5 years. Lastly, there are emerging differences between those who do and do not require renal replacement therapy (RRT) for their AKI, which may require more frequent and intense follow-up in those needing RRT.

SUMMARY

Although large scale evidence-based guidelines are lacking, standardization of post-ICU-AKI is needed.

The roles of melatonin on kidney injury in obese and diabetic conditions

Obesity is a common and complex health problem worldwide and can induce the development of Type 2 diabetes. Chronic kidney disease (CKD) is a complication occurring as a result of obesity and diabetic conditions that lead to an increased mortality rate. There are several mechanisms and pathways contributing to kidney injury in obese and diabetic conditions. The expansion of adipocytes triggers proinflammatory cytokines release into blood circulation and bind with the receptors at the cell membranes of renal tissues leading to kidney injury. Obesity-mediated inflammation, oxidative stress, apoptosis, and mitochondrial dysfunction are the important causes and progression of CKD. Melatonin (N-acetyl-5-methoxytryptamine) is a neuronal hormone that is synthesized by the pineal gland and plays an essential role in regulating several physiological functions in the human body. Moreover, melatonin has pleiotropic effects such as antioxidant, anti-inflammation, antiapoptosis. In this review, the relationship between obesity, diabetic condition, and kidney injury and the renoprotective effect of melatonin in obese and diabetic conditions from in vitro and in vivo studies have been summarized and discussed.

Obese trauma patients have increased need for dialysis

PURPOSE

Obesity is a risk factor for the development of acute kidney injury but its effect on the need for dialysis in trauma has not been elucidated. Additionally, the contribution that obesity has towards risk of mortality in trauma is unclear. We hypothesized that patients with a higher body mass index (BMI) will have a higher risk for need of dialysis and mortality after trauma.

METHODS

This is a retrospective analysis using the National Trauma Data Bank. All patients ≥ 8 years old were grouped based on BMI: normal (18.5-24.99 kg/m²), obese (30-34.99 kg/m²), severely obese (35-39.99 kg/m²) and morbidly obese (≥ 40 kg/m²). The primary outcome was hemodialysis initiation. The secondary outcome was mortality during the index hospitalization.

RESULTS

From 988,988 trauma patients, 571,507 (57.8%) had a normal BMI, 233,340 (23.6%) were obese, 94,708 (9.6%) were severely obese, and 89,433 (9.0%) were morbidly obese. The overall rate of hemodialysis was 0.3%. After adjusting for covariates, we found that obese (OR 1.36, CI 1.22-1.52, p < 0.001), severely obese (OR 1.89, CI 1.66-2.15, p < 0.001) and morbidly obese (OR 2.04, CI 1.82-2.29, p < 0.001) patients had a stepwise increased need for hemodialysis after trauma. Obese patients had decreased (OR 0.92, CI 0.88-0.95, p < 0.001), severely obese had similar (OR 1.02, CI 0.97-1.08, p = 0.50) and morbidly obese patients had increased (OR 1.06, CI 1.01-1.12, p = 0.011) risk of mortality after trauma.

CONCLUSIONS

Obesity was associated with an increased risk for dialysis after trauma. Mortality risk was reduced in obese, similar in severely obese, and increased in morbidly obese trauma patients suggesting an inflection threshold BMI for risk of mortality in trauma.