Dataset Information

Impact of electrolyte-rich dialysate during continuous renal replacement therapy on serum phosphate and potassium in ICU patients.

ABSTRACT:

Background

Hypophosphatemia and hypokalemia occur frequently during continuous renal replacement therapy (CRRT). We evaluated serum phosphate and potassium levels in patients administered three different types of dialysis solution.

Methods

The study population consisted of 324 intensive care unit patients who underwent CRRT between January 2015 and December 2018. Patients were divided into three groups: group 1 (n = 105) received Hemosol B0 (no potassium or phosphate); group 2 (n = 78) received Hemosol B0 and potassium-containing solution (MultiBic); and group 3 (n = 141) received phosphate- and potassium-containing solution (Phoxilium), Hemosol B2, Prismasol 2, and Prismasol 4. A different protocol was followed in each group.

Results

The incidence rate of hypophosphatemia was 55% lower in group 3 compared to group 1 (incidence rate ratio (IRR) 0.45, 95% confidence interval (CI): 0.33 to 0.61) and 61% lower compared to group 2 (IRR 0.39, 95% CI: 0.29 to 0.53). Group 3 also had a 50% lower incidence rate of hypokalemia compared to group 1 (IRR 0.50, 95% CI: 0.29 to 0.88). The negative slope in phosphate level in group 3 was greater than that in group 1 (ß = 0.19, 95% CI: 0.02 to 0.37, p = 0.032), while the negative slope in the potassium level was greater in group 2 than in group 1(ß = 0.10, 95% CI: 0.03 to 0.17, p = 0.008). Additional intravenous calcium was not used in any case, and most cases of acid-base disturbances were well controlled.

Conclusions

The use of phosphate- and potassium-containing with a proper CRRT protocol prevented decreases in serum phosphate and potassium levels, thus also preventing hypophosphatemia and hypokalemia, and additional replacement during CRRT.

SUBMITTER: Cho A

PROVIDER: S-EPMC7485827 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Impact of electrolyte-rich dialysate during continuous renal replacement therapy on serum phosphate and potassium in ICU patients.

Cho AJin A Lee Young-Ki YK Park Hayne Cho HC

PloS one 20200911 9

<h4>Background</h4>Hypophosphatemia and hypokalemia occur frequently during continuous renal replacement therapy (CRRT). We evaluated serum phosphate and potassium levels in patients administered three different types of dialysis solution.<h4>Methods</h4>The study population consisted of 324 intensive care unit patients who underwent CRRT between January 2015 and December 2018. Patients were divided into three groups: group 1 (n = 105) received Hemosol B0 (no potassium or phosphate); group 2 (n ...[more]

PMID: 32915900

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Project description:Estimating glomerular filtration (eGFR) after Continuous Renal Replacement Therapy (CRRT) is important to guide drug dosing and to assess the need to re-initiate CRRT. Standard eGFR equations cannot be applied as these patients neither have steady-state serum creatinine concentration nor average muscle mass. In this study we evaluate the combination of dynamic renal function with CT-scan based correction for aberrant muscle mass to estimate renal function immediately after CRRT cessation. We prospectively included 31 patients admitted to an academic intensive care unit (ICU) with a total of 37 CRRT cessations and measured serum creatinine before cessation (T1), directly (T2) and 5 h (T3) after cessation and the following two days when eGFR stabilized (T4, T5). We used the dynamic creatinine clearance calculation (D3C) equation to calculate eGFR (D3CGFR) and creatinine clearance (D3Ccreat) between T2-T3. D3Ccreat was corrected for aberrant muscle mass when a CT-scan was available using the CRAFT equation. We compared D3CGFR to stabilized CKD-EPI at T5 and D3CCreat to 4-h urinary creatinine clearance (4-h uCrCl) between T2-T3. We retrospectively validated these results in a larger retrospective cohort (NICE database; 1856 patients, 2064 cessations). The D3CGFR was comparable to observed stabilized CKD-EPI at T5 in the prospective cohort (MPE = - 1.6 ml/min/1.73 m2, p30 = 76%) and in the retrospective NICE-database (MPE = 3.2 ml/min/1.73 m2, p30 = 80%). In the prospective cohort, the D3CCreat had poor accuracy compared to 4-h uCrCl (MPE = 17 ml/min/1.73 m2, p30 = 24%). In a subset of patients (n = 13) where CT-scans were available, combination of CRAFT and D3CCreat improved bias and accuracy (MPE = 8 ml/min/1.73 m2, RMSE = 18 ml/min/1.73 m2) versus D3CCreat alone (MPE = 18 ml/min/1.73 m2, RMSE = 32 ml/min/1.73 m2). The D3CGFR improves assessment of eGFR in ICU patients immediately after CRRT cessation. Although the D3CCreat had poor association with underlying creatinine clearance, inclusion of CT derived biometric parameters in the dynamic renal function algorithm further improved the performance, stressing the role of muscle mass integration into renal function equations in critically ill patients.

Project description:BackgroundContinuous renal replacement therapy (CRRT) is the favored renal replacement therapy in critically ill patients. Predicting clinical outcomes for CRRT patients is difficult due to population heterogeneity, varying clinical practices, and limited sample sizes.ObjectiveWe aimed to predict survival to ICUs and hospital discharge in children and young adults receiving CRRT using machine learning (ML) techniques.Derivation cohortPatients less than 25 years of age receiving CRRT for acute kidney injury and/or volume overload from 2015 to 2021 (80%).Validation cohortInternal validation occurred in a testing group of patients from the dataset (20%).Prediction modelRetrospective international multicenter study utilizing an 80/20 training and testing cohort split, and logistic regression with L2 regularization (LR), decision tree, random forest (RF), gradient boosting machine, and support vector machine with linear kernel to predict ICU and hospital survival. Model performance was determined by the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC) due to the imbalance in the dataset.ResultsOf the 933 patients included in this study, 538 (54%) were male with a median age of 8.97 years and interquartile range (1.81-15.0 yr). The ICU mortality was 35% and hospital mortality was 37%. The RF had the best performance for predicting ICU mortality (AUROC, 0.791 and AUPRC, 0.878) and LR for hospital mortality (AUROC, 0.777 and AUPRC, 0.859). The top two predictors of ICU survival were Pediatric Logistic Organ Dysfunction-2 score at CRRT initiation and admission diagnosis of respiratory failure.ConclusionsThese are the first ML models to predict survival at ICU and hospital discharge in children and young adults receiving CRRT. RF outperformed other models for predicting ICU mortality. Future studies should expand the input variables, conduct a more sophisticated feature selection, and use deep learning algorithms to generate more precise models.

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Dataset Information

Impact of electrolyte-rich dialysate during continuous renal replacement therapy on serum phosphate and potassium in ICU patients.

Background

Methods

Results

Conclusions

Publications

Impact of electrolyte-rich dialysate during continuous renal replacement therapy on serum phosphate and potassium in ICU patients.

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