Hypotension within one-hour from starting CRRT is associated with in-hospital mortality

Shawwa, Khaled; Kompotiatis, Panagiotis; Jentzer, Jacob C.; Wiley, Brandon M.; Williams, Amy W.; Dillon, John; Albright, Robert C.; Kashani, Kianoush

doi:10.1016/j.jcrc.2019.07.004

Cited by 44 publications

(31 citation statements)

References 47 publications

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“…Our finding was in line with existing evidence that the chief complication of CRRT is hypotension, which can cause major adverse events, such as myocardial infarction and stroke [39,40]. An existing study involving 1743 patients showed that the incidence of hypotension within one hour of starting CRRT was 64.6%, and that the in-hospital mortality rate was as high as 51% [41]. Although CRRT has good hemodynamic tolerance for critically ill patients, reducing patients' BP and further worsening of their renal function may sometimes be unavoidable during CRRT [42].…”

Section: Discussionsupporting

confidence: 91%

Factors Associated with In-Hospital Mortality after Continuous Renal Replacement Therapy for Critically Ill Patients: A Systematic Review and Meta-Analysis

Lee

Son

2020

IJERPH

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Continuous renal replacement therapy (CRRT) is a broadly-accepted treatment for critically ill patients with acute kidney injury to optimize fluid and electrolyte management. Despite intensive dialysis care, there is a high mortality rate among these patients. There is uncertainty regarding the factors associated with in-hospital mortality among patients requiring CRRT. This review evaluates how various risk factors influence the in-hospital mortality of critically ill patients who require CRRT. Five databases were surveyed to gather relevant publications up to 30 June 2020. We identified 752 works, of which we retrieved 38 in full text. Finally, six cohort studies that evaluated 1190 patients were eligible. The in-hospital mortality rate in these studies ranged from 38.6 to 62.4%. Our meta-analysis results showed that older age, lower body mass index, higher APACHE II and SOFA scores, lower systolic and diastolic blood pressure, decreased serum creatinine level, and increased serum sodium level were significantly associated with increased in-hospital mortality in critically ill patients who received CRRT. These results suggest that there are multiple modifiable factors that influence the risk of in-hospital mortality in critically ill patients undergoing CRRT. Further, healthcare professionals should take more care when CRRT is performed on older adults.

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Section: Discussionsupporting

confidence: 91%

Factors Associated with In-Hospital Mortality after Continuous Renal Replacement Therapy for Critically Ill Patients: A Systematic Review and Meta-Analysis

Lee

Son

2020

IJERPH

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“…Unexpected hypotensive events after starting CRRT are a critical issue because they contribute to worse outcomes, as noted in the above association with high ICU mortality [5,6]. Machine learning models such as LGBM and DNN successfully predicted the risk of hypotension and performed better than conventional scoring models such as SOFA, APACHE II, and MOSAIC.…”

Section: Discussionmentioning

confidence: 98%

“…Their outcomes are much worse because they frequently have several comorbidities and imbalanced uid and electrolytes [1][2][3][4]. Although CRRT is started at the right time, complications such as hemodynamic and metabolic crises can aggravate patient outcomes [5][6][7][8]. This issue indicates that starting CRRT may not guarantee a survival bene t in critically ill patients.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Model to Predict Hypotension After Starting Continuous Renal Replacement Therapy

Kang

Kim

et al. 2020

Preprint

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Background: Hypotension after starting continuous renal replacement therapy (CRRT) is associated with worse outcome, but it is difficult to predict because several factors have interactive and complex effects on the risk. The present study applied machine learning algorithms to develop models to predict hypotension after initiating CRRT.Methods: Among 2,349 adult patients who started CRRT due to acute kidney injury, 70% and 30% were randomly assigned into the training and testing sets, respectively. Hypotension was defined as a reduction in mean arterial pressure (MAP) ≥20 mmHg from the initial value within 6 hours. The area under the receiver operating characteristic curves (AUROCs) in machine learning models, such as support vector machine (SVM), deep neural network (DNN), and light gradient boosting machine (LGBM), were compared with those in disease-severity scores such as the Sequential Organ Failure Assessment and Acute Physiology and Chronic Health Evaluation II.Results: The DNN model showed the highest AUROC (0.822 [0.789–0.856]), and the LGBM and SVM models followed with AUROCs of 0.810 (0.776–0.845) and 0.807 (0.772–0.842), respectively; all machine learning AUROC values were higher than those obtained from disease-severity scores (AUROCs <0.6). Although different definitions of hypotension were used such as a reduction of MAP ≥30 mmHg or a reduction occurring within 1 hour, the AUROCs of machine learning models were higher than those of disease-severity scores. These machine learning models were well calibrated.Conclusion: Machine learning models successfully predict hypotension after starting CRRT and can serve as the basis of systems to predict hypotension before starting CRRT.

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“…MAKE has been used in a few randomized controlled trials in AKI 23,24 and is slowly making its way into observational literature as well. [25][26][27] However, additional work is still needed to evaluate the patientcenteredness of the doubling of Scr criterion, which is often the most common MAKE criterion met. Future work may identify better end points that incorporate cause and clinical context (eg, suspected hemodynamic vs parenchymal injury).…”

Section: Variation In Different Clinical Contextsmentioning

confidence: 99%

AKI—A Relevant Safety End Point?

McCoy

Chertow

2020

American Journal of Kidney Diseases

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Acute kidney injury (AKI) is a common outcome evaluated in clinical studies, often as a safety end point in a variety of cardiovascular, kidney disease, and other clinical trials. AKI end points that include modest increases in serum creatinine levels from baseline may not associate with patient-centered outcomes such as initiation of dialysis, sustained decline in kidney function, or death. Surprisingly, data from several randomized controlled trials have suggested that in certain settings, the development of AKI may be associated with favorable outcomes. AKI safety end points that are nonspecific and may not associate with patient-centered outcomes could result in beneficial therapies being inappropriately withheld or never developed for commercial use. We review several issues related to commonly used AKI definitions and suggest that future work in AKI use more patient-centered AKI end points such as major adverse kidney events at 30 days or other later time points.

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Hypotension within one-hour from starting CRRT is associated with in-hospital mortality

Cited by 44 publications

References 47 publications

Factors Associated with In-Hospital Mortality after Continuous Renal Replacement Therapy for Critically Ill Patients: A Systematic Review and Meta-Analysis

Factors Associated with In-Hospital Mortality after Continuous Renal Replacement Therapy for Critically Ill Patients: A Systematic Review and Meta-Analysis

Machine Learning Model to Predict Hypotension After Starting Continuous Renal Replacement Therapy

AKI—A Relevant Safety End Point?

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