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All issues Volume 57 / No 1 (March 2025) J Extra Corpor Technol, 57 1 (2025) 14-17 Full HTML
Open Access
Issue
J Extra Corpor Technol
Volume 57, Number 1, March 2025
Page(s) 14 - 17
DOI https://doi.org/10.1051/ject/2024041
Published online 07 March 2025

© The Author(s), published by EDP Sciences, 2025

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Introduction

Cardiopulmonary shock contributes to the development of end-organ hypoperfusion [1]. Although the therapy for this type of shock includes the administration of intravenous vasoactive medications, percutaneous coronary artery interventions, and/or mechanical ventilation, patients who continue to deteriorate may require mechanical circulatory support (MCS) [2]. MCS swiftly augments tissue perfusion and assists to normalize the pathophysiology observed in these conditions [2].

Although the reperfusion of tissues with MCS is beneficial, this therapy risks development of reperfusion injury due to the prior hypoperfusion period as well as due to further development of reactive oxygen/nitrogen species, cytokines release, and hyperinflammatory responses exacerbating tissue injury [2, 3]. Acute kidney injury frequently develops in patients requiring MCS [3–5]. However, the etiologies for the need of RRT during MCS are unclear [6, 7]. The purpose of this investigation was to examine the association of patient comorbidities receiving MCS with the need for RRT.

Materials and methods

Following IRB approval, a retrospective analysis of patient characteristics, comorbidities, and the incidence of RRT were studied from January 2017 to October 2023 in 129 patients receiving 159 MCS devices (Table 1) at Ochsner Health-Jefferson Highway Campus in New Orleans, Louisiana. There were no patient exclusion criteria. Patient characteristics and recorded comorbidities (Table 2) underwent machine learning to determine associations in the need for RRT [8].

Table 1

List of mechanical circulatory support devices.

Table 2

Baseline characteristics and reported comorbidities for renal replacement therapy in patients requiring mechanical circulatory support.

Statistics

Baseline characteristics and comorbidities (Table 2) underwent machine learning to explore these relationships for the need of RRT. The machine learning used in this prediction study included Decision-Tree (Recursive Partitioning), Bootstrap Forest, Boosted Tree, K Nearest Neighbors, Neural Support Vectors Machines, Discriminant, Fit Least Squares, Fit Stepwise, Logistic Regressions, Generalized Regression, Native Bayes, and Partial Least Squares [8]. P values for frequentist tests were set for statistical significance at <0.05. The statistical program, JMP® Pro 17.2 (SAS Institute, Cary, NC) was utilized for this study [8].

Results

In this study of patients requiring MCS, the incidence of RRT was 36% with a 95% confidence interval (CI) 29–44%. The incidence of hospital mortality in patients requiring RRT was 79% CI 66.7–87.5% (χ2 = 29, P < .0001) but was 35.3% CI 26.7–44.9% in MCS patients not requiring RRT. The types of MCS devices used in this study are shown in Table 1. Baseline patient characteristics and recorded comorbidities in patients requiring MCS are shown in Table 2. The baseline characteristics and comorbidities underwent machine learning associated with the outcome of interest, the need for RRT. Age, and two novel comorbidities, patients with a history immunomodulation, and patients with pacemaker/internal cardiac defibrillator (ICD) were statistically associated with the need for RRT (χ2 = 44, P = 0.0003; Table 2). The c-index statistic for this model was 0.81. Based on the results of this model, two contingency tables were constructed to further explore the two novel comorbidities with the need for RRT (Tables 3 and 4). Patients who had a history of immunomodulation were noted to have an incidence of 48% in the need for RRT during MCS (Table 3). Patients with a history of pacemaker/ICDs also had a high incidence (47%) in requiring RRT during MCS (Table 4). Patients with both comorbidities had a 66% incidence in the need for RRT.

Table 3

Contingency table of the association of renal replacement therapy in patients with a history of immunomodulation during mechanical circulatory support.

Table 4

Contingency table of the association of renal replacement therapy in patients with pre-existing pacemaker or internal cardiac defibrillator (ICD) during mechanical circulatory support.

We further explored the role of anticoagulation used in the two novel groups when combined (Interest groups) and the results of that analysis are shown in Table 5. In MCS patients receiving unfractionated heparin (UFH), a 43% incidence in the need for RRT was observed in this cohort of patients. Four patients who did not receive anticoagulation therapy all required RRT, in contrast to three patients not requiring RRT when low molecular weight heparin (LMWH) was used (χ2 = 10.1, P = 0.0064). While these findings were observed in a small subset of patients, the results warrant further investigation into anticoagulation practices used in this patient population.

Table 5

Contingency table of the association of renal replacement therapy by anticoagulant therapy during mechanical circulatory support.

Discussion

The use of MCS therapies is becoming an important component of supportive care in intensive care units [5]. Although initial support for patients frequently includes vasoactive support medications and/or mechanical ventilation, patients that continue to deteriorate or become refractory to medical therapy may require MCS [1, 2].

Although the causes of cardiogenic shock are numerous, a low cardiac output state exists, that when unsuccessfully treated, results in end organ hypoperfusion [5]. In our study, we observed two novel preexisting risk factors for the need of RRT during MCS; patients with preexisting inflammatory disorders requiring therapy, and patients with pre-existing pacemaker/ICDs. As we observed a higher incidence in the need for RRT in patients with these two disorders, this association suggests that an increased systemic inflammatory state exists that escalated the need for RRT [7], as in these two groups, the administration of UFH was not protective in reducing the need for RRT.

UFH is frequently used for anticoagulation during MCS which was based upon prior experience in procedures requiring cardiopulmonary bypass [9]. However with long-term UFH administration, heparin resistance and immune-mediated platelet activation leading to heparin-induced thrombocytopenia can develop [10]. In hypercoagulable states, such as observed in patients with renal failure, following major surgery, or histories of congestive heart failure, or autoimmune diseases, Kaur, Arsene, and colleagues recommend UFH should be used with caution [11]. Implantable cardiac devices have also been shown to generate an inflammatory response [12]. Taken together, the inflammatory components in UFH may contribute to the inflammatory state and increase the need for RRT. Studies with newer generation anticoagulants need to be conducted following development of bedside monitoring techniques to allow timely adjustment of anticoagulant therapy based upon real-time coagulation parameters [9, 10, 13].

Limitations

Limitations of retrospective studies suffer from completeness of medical record data. However, the strength of this study was the near 100% data collection due to the recent development of electronic medical records. Another limitation of this study is potential bias due to confounding. However, the strength of this study was the statistical method used to adjust for all confounders through the application of machine learning against the outcome of interest, need for RRT. Machine learning performs better than traditional statistical analyses, especially when analyzing multifaceted data sets. The ability to utilize machine modeling provides a powerful tool to express information [14].

Conclusions

The incidence of RRT was high in this patient population. The mortality rate was high in patients requiring RRT. Moreover, these findings also suggest that other options for systemic anticoagulation during MCS should be considered. The novel associations of patients who have received prior immunotherapy or with pre-existing pacemaker/ICDs requiring MCS suggest an increased systemic inflammatory state exists that escalates the need for RRT. Further investigation into how these background inflammatory conditions contribute to the need for RRT during MCS is warranted.

Funding

The authors received no funding to complete this research.

Conflicts of interest

The authors declare no conflict of interest.

Data availability statement

All available data are incorporated into the article.

Author contribution statement

Kelsey Gore, MA, BSRT, RRT: Design, Data harvest, Editorial review of the manuscript.

Dean Linder, Jr. CCP, LP: Editorial review of the manuscript.

Juan José Martinez Duque MD: Data harvest, Editorial review of the manuscript.

Junxi Wang BS: Data harvest, Editorial review of the manuscript.

Brett Wester, DO: Editorial review of the manuscript.

Tiffany Otero, MD: Editorial review of the manuscript.

Shaun Yockelson, MD: Editorial review of the manuscript.

Adrian Alexis Ruiz, MD: Editorial review of the manuscript.

Bobby D. Nossaman, MD: Research design, Statistics, Data harvest, Editorial review of the manuscript.

Ethics approval

IRB approval 2023.201-MCS.

References

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Cite this article as: Gore K, Linder D, Duque JJM, Wang J, Wester B, Otero T, Yockelson S, Ruiz A & Nossaman BD. Limiting the gamble: Risk and predictability for renal replacement therapy in patients receiving mechanical circulatory support. J Extra Corpor Technol 2025, 57, 14–17. https://doi.org/10.1051/ject/2024041.

All Tables

Table 1

List of mechanical circulatory support devices.

In the text
Table 2

Baseline characteristics and reported comorbidities for renal replacement therapy in patients requiring mechanical circulatory support.

In the text
Table 3

Contingency table of the association of renal replacement therapy in patients with a history of immunomodulation during mechanical circulatory support.

In the text
Table 4

Contingency table of the association of renal replacement therapy in patients with pre-existing pacemaker or internal cardiac defibrillator (ICD) during mechanical circulatory support.

In the text
Table 5

Contingency table of the association of renal replacement therapy by anticoagulant therapy during mechanical circulatory support.

In the text

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