Prolonged exposure to continuous renal replacement therapy in patients with acute kidney injury

Impact of the prognostic nutritional index on renal replacement therapy-free survival and mortality in patients on continuous renal replacement therapy

BACKGROUND

The survival of critically ill patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT) is highly dependent on their nutritional status.

OBJECTIVES

The prognostic nutritional index (PNI) is an indicator used to assess nutritional status and is calculated as: PNI = (serum albumin in g/dL) × 10 + (total lymphocyte count in/mm3) × 0.005. In this retrospective study, we investigated the correlation between this index and clinical outcomes in critically ill patients with AKI receiving CRRT.

METHODS

We analyzed data from 2076 critically ill patients admitted to the intensive care unit at Changhua Christian Hospital, a tertiary hospital in central Taiwan, between January 1, 2010, and April 30, 2021. All these patients met the inclusion criteria of the study. The relationship between PNI and renal replacement therapy-free survival (RRTFS) and mortality was examined using logistic regression models, Cox proportional hazard models, and propensity score matching. High utilization rate of parenteral nutrition (PN) was observed in our study. Subgroup analysis was performed to explore the interaction effect between PNI and PN on mortality.

RESULTS

Patients with higher PNI levels exhibited a greater likelihood of achieving RRTFS, with an adjusted odds ratio of 2.43 (95% confidence interval [CI]: 1.98-2.97, p-value < 0.001). Additionally, these patients demonstrated higher survival rates, with an adjusted hazard ratio of 0.84 (95% CI: 0.72-0.98) for 28-day mortality and 0.80 (95% CI: 0.69-0.92) for 90-day mortality (all p-values < 0.05), compared to those in the low PNI group. While a high utilization rate of parenteral nutrition (PN) was observed, with 78.86% of CRRT patients receiving PN, subgroup analysis showed that high PNI had an independent protective effect on mortality outcomes in AKI patients receiving CRRT, regardless of their PN status.

CONCLUSIONS

PNI can serve as an easy, simple, and efficient measure of lymphocytes and albumin levels to predict RRTFS and mortality in AKI patients with require CRRT.

Validation of prediction model for successful discontinuation of continuous renal replacement therapy: a multicenter cohort study

BACKGROUND

Continuous renal replacement therapy (CRRT) has become the standard modality of renal replacement therapy (RRT) in critically ill patients. However, consensus is lacking regarding the criteria for discontinuing CRRT. Here we validated the usefulness of the prediction model for successful discontinuation of CRRT in a multicenter retrospective cohort.

METHODS

One temporal cohort and four external cohorts included 1,517 patients with acute kidney injury who underwent CRRT for >2 days from 2018 to 2020. The model was composed of four variables: urine output, blood urea nitrogen, serum potassium, and mean arterial pressure. Successful discontinuation of CRRT was defined as the absence of an RRT requirement for 7 days thereafter.

RESULTS

The area under the receiver operating characteristic curve (AUROC) was 0.74 (95% confidence interval, 0.71-0.76). The probabilities of successful discontinuation were approximately 17%, 35%, and 70% in the low-score, intermediate-score, and highscore groups, respectively. The model performance was good in four cohorts (AUROC, 0.73-0.75) but poor in one cohort (AUROC, 0.56). In one cohort with poor performance, attending physicians primarily controlled CRRT prescription and discontinuation, while in the other four cohorts, nephrologists determined all important steps in CRRT operation, including screening for CRRT discontinuation.

CONCLUSION

The overall performance of our prediction model using four simple variables for successful discontinuation of CRRT was good, except for one cohort where nephrologists did not actively engage in CRRT operation. These results suggest the need for active engagement of nephrologists and protocolized management for CRRT discontinuation.

Machine Learning-Aided Decision-Making Model for the Discontinuation of Continuous Renal Replacement Therapy

INTRODUCTION

Continuous renal replacement therapy (CRRT) is a primary form of renal support for patients with acute kidney injury in an intensive care unit. Making an accurate decision of discontinuation is crucial for the prognosis of patients. Previous research has mostly focused on the univariate and multivariate analysis of factors in CRRT, without the capacity to capture the complexity of the decision-making process. The present study thus developed a dynamic, interpretable decision model for CRRT discontinuation.

METHOD

The study adopted a cohort of 1,234 adult patients admitted to an intensive care unit in the MIMIC-IV database. We used the eXtreme Gradient Boosting (XGBoost) machine learning algorithm to construct dynamic discontinuation decision models across 4 time points. SHapley Additive exPlanation (SHAP) analysis was conducted to exhibit the contributions of individual features to the model output.

RESULT

Of the 1,234 included patients with CRRT, 596 (48.3%) successfully discontinued CRRT. The dynamic prediction by the XGBoost model produced an area under the curve of 0.848, with accuracy, sensitivity, and specificity of 0.782, 0.786, and 0.776, respectively. The performance of the XGBoost model was far superior to other test models. SHAP demonstrated that the features that contributed most to the model results were the Sequential Organ Failure Assessment score, serum lactate level, and 24-h urine output.

CONCLUSION

Dynamic decision models supported by machine learning are capable of dealing with complex factors in CRRT and effectively predicting the outcome of discontinuation.

Anticipation of recovery of native renal function and liberation from renal replacement therapy in critically ill patients with severe acute kidney injury

Background

Renal replacement therapy (RRT) is used to manage critically ill patients with severe acute kidney injury (AKI-D), and it is undoubtedly life-sustaining for most patients. However, the prolonged unnecessary use of these techniques may be harmful. At present, no consensus guidelines provide specific recommendations for clinicians on when (optimal timing of discontinuation) and how (liberation or weaning) to stop RRT in intensive care unit (ICU) patients with recovering native kidney function.

Methods and results

Numerous variables such as clinical parameters, classical surrogate markers for glomerular filtration rate, novel biomarkers of kidney function and damage, and new imaging techniques in AKI-D have been described to predict successful discontinuation of RRT. Most available studies are limited by study design, heterogeneity of variable assessment and thresholds of biomarkers, and lack of prospective validation. At present, the decision on discontinuation of RRT in ICU patients is based on three clinical scenarios: (a) intrinsic kidney function (defined as spontaneous urine output > 500 ml/24 h, timed creatinine clearance > 15 to 20 ml/min) has adequately improved to match the demands and continued RRT is no longer consistent with goals of care (transition to intermittent RRT); (b) the acute illness that prompted RRT has improved; (c) the clinical practice of switching haemodynamic stable patients with persistent AKI-D from continuous RRTs to intermittent RRTs is variable, but de-escalation of RRT (frequency, dose) may facilitate mobilization and discharge of ICU patients.

Conclusions

The predictive ability of novel kidney biomarkers, surrogate markers of kidney function, and direct measurements of kidney function should be evaluated in future studies.