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All issues Volume 56 / No 4 (December 2024) J Extra Corpor Technol, 56 4 (2024) 174-184 Full HTML
Open Access
Issue
J Extra Corpor Technol
Volume 56, Number 4, December 2024
Page(s) 174 - 184
DOI https://doi.org/10.1051/ject/2024020
Published online 20 December 2024

© The Author(s), published by EDP Sciences, 2024

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

The use of extracorporeal life support (ECLS) following cardiac surgery is utilized in 3–5% of all neonatal and pediatric cardiac surgeries with a 43–52% survival [1, 2]. Neonates with univentricular physiology who undergo a Norwood operation represent an especially high-risk population [3–6]. The tenuous nature of their postoperative physiology requires significant cardiopulmonary support and at times ECLS to maintain adequate hemodynamics and oxygen delivery. Previous reports indicate that 8–22% of neonates will require ECLS post-Norwood operation [4, 5, 7–9], with an overall survival rate of 30–60% [4, 5, 7–9].

When ECLS is used postoperatively, patients are supported with venoarterial-ECLS. These ECLS circuits utilize an efficient oxygenator resulting in high partial pressure of oxygen (PaO2) that can exceed 400 mmHg. Exposure to supranormal levels of oxygen is termed hyperoxia. Hyperoxia has been well studied in different clinical situations, including after resuscitation from cardiac arrest, perinatal asphyxia, myocardial infarctions, traumatic brain injury, and following cardiopulmonary bypass (CPB). Studies in both adults and children have demonstrated an association with increased morbidity and mortality [1, 10–18]. Furthermore, minimizing PaO2 while on CPB in cyanotic patients with complete mixing congenital heart lesions has been shown to result in less end-organ damage, inflammation, and oxidative stress when compared to those exposed to higher oxygen concentrations [1, 19, 20]. Although the negative effect of hyperoxia and its association with adverse outcomes is known, adequate oxygen delivery is necessary and the level at which PaO2 may become deleterious may differ depending on the clinical situation, duration of exposure, patient’s age, underlying pathophysiology, and disease process [1, 10, 14, 21–23].

Given the lack of a clear definition of hyperoxia, we aimed to evaluate a high-risk homogenous patient population, specifically neonates with univentricular physiology who underwent Norwood operation and required ECLS in the postoperative period. Our primary aim was to determine if hyperoxia while on ECLS is associated with mortality using a derived cut-point within our cohort. Our secondary aim was to determine if hyperoxia during ECLS was associated with morbidity including Functional Status Scale (FSS), acute kidney injury (AKI), and prolonged postoperative length of stay (PPLOS).

Materials and methods

This is a single-center retrospective cohort study including all neonates with univentricular physiology who underwent a Norwood operation and required ECLS in the postoperative period between January 1st, 2010, and December 31st, 2020, at Children’s Healthcare of Atlanta (CHOA), a large quaternary children’s hospital. An internal surgical and ECLS database/registry were queried, and eligible patients were identified. Procedures were followed in accordance with the ethical standards of the CHOA Institutional Review Board (IRB# 00001119, approval 07/19/2021), and the Helsinki Declaration of 1975. Informed consent was waived.

Data and definitions

All consecutive patients who underwent Norwood operation and required ECLS in the index postoperative ICU hospitalization were included. Patients who failed to separate from CPB and initiated ECLS in the operating room were excluded (n = 6). Also, patients who underwent a hybrid procedure prior to undergoing a Norwood’ operation were excluded from our study analysis (n = 3). These 2 exclusion criteria were chosen to make the patient population in the study as homogenous as possible. None of our patients underwent a concomitant AVV repair at the time of Norwood’s operation. Demographic features and clinical characteristics, including chromosomal abnormalities, genetic syndrome, primary cardiac diagnosis, type of systemic ventricle, source of pulmonary blood flow [modified Blalock-Taussig-Thomas (m-BTT) shunt vs. Sano shunt/right ventricle to pulmonary artery (RV-PA) conduit], preoperative respiratory support, creatinine, preoperative and intraoperative echocardiogram [assessing atrioventricular valve regurgitation (AVVR), systemic ventricular function, and ascending aorta diameter], preoperative and postoperative vasoactive inotropic scores (VIS) at dedicated postoperative times points; operative variables, including CPB, aortic cross-clamp (XC), and circulatory arrest times; and ECLS variables (cannulation site, ECLS duration, and ECLS complications) were collected. All arterial blood gases (ABGs) were obtained from the patient’s right radial arterial line (institutional standard of care includes placement of a right radial arterial line to monitor hemodynamics and arterial blood gases) during and after the Norwood operation. ABG data was obtained prior to ECLS initiation, and during the first 48 h while on ECLS.

Outcomes

The primary outcome was all-cause ECLS mortality. The secondary outcomes included FSS (preoperative compared to discharge), AKI (Stage II or III, as defined by the KDIGO scoring criteria) [24], and PPLOS, defined a-priori as the fourth quartile of the postoperative length of stay (≥55 days). Length of stay may be biased by mortality, because those who die may have a shorter length of stay, which would erroneously appear as a good outcome. Two methods were used to control for this bias. In standard logistic regression, the length of stay for mortality was defined as prolonged, regardless of duration. In a second analysis, a composite rank-based outcome was created for days alive ICU-free (AIF). In this method, the AIF composite endpoint equals the number of ICU-free days over the first 28 postoperative days. Those with mortality were assigned a score of −1 [25].

Functional Status Scale (FSS)

The FSS consists of six main domains: mental status, sensory, communications, motor function, feeding, and respiratory. Functional status for each domain was categorized from normal (1) to very severe dysfunction (5), with total FSS scores ranging from 6 to 30 [26]. Functional status scoring for this study involved retrospectively scoring baseline status (i.e., on admission) and again at hospital discharge utilizing appropriate documentation. FSS score determination was blinded from hyperoxia status. Newborns who had never achieved a stable baseline function were assigned a score of 6. This was operationalized by assigning a baseline FSS score of 6 to all admissions for infants 0–2 days old and to transfers from another facility for infants 3–6 days old as previously reported [27–30]. New morbidity was defined as an increase in the total score of ≥3 points, and unfavorable functional outcome was defined as an increase of ≥5 points [31].

Clinical management

In our center, in the period 2010–2020, there were multiple different iterations in the layout of the ECLS circuit, and we used different manufacturers for different circuit components/parts. All circuits were blood-primed before the start of ECLS with packed red blood cells, 25% albumin, sodium bicarbonate, calcium gluconate, and heparin. It is common practice for ABGs to be obtained at the discretion of the clinical team, commonly approximately 30 min after initial ECLS cannulation, and then hourly for the first several hours. Subsequently, blood gases are obtained every 3–6 h and shortly after an adjustment in ECLS support. Target gas exchange parameters are not dictated by protocol at our center. Goal PaO2 ranges have no established normal and the variation we describe is derived from measurements occurring during clinical care. We target goal arterial oxygen saturations >80%, and to ensure adequacy of cardiac output, we target pre-membrane saturations >50% using Spectrum Medical Perfusion Monitor M3 and M4, Fort Mill, SC, USA. Goal PaCO2 was typically 35–45 mmHg, and goal pH was typically 7.35–7.45. While on ECLS, our center’s approach was not to mechanically limit or clamp any source of pulmonary blood flow (i.e., m-BTT or Sano shunt).

Statistical analysis

Variables were described using medians with interquartile ranges (IQR) or counts with percentages. Patient characteristics were compared between hyperoxia and non-hyperoxia groups. Comparisons were made using chi‐square tests or Fisher’s exact tests for categorical variables and Wilcoxon rank-sum tests for continuous variables. Average PaO2 while on CPB was calculated for individual patients. The correlation coefficient with a 95% confidence interval (95% CI) was calculated. ROC curve and area under the curve (AUC) analyses were performed to identify the optimal cut-off values of mean PaO2 for predicting mortality within 30 days after the operation. All variables were entered into binary logistic regression analyses with pre-identified hyperoxia status as the outcome. The associations between hyperoxia status and adverse outcomes (i.e., Stage II or III AKI, PPLOS, and mortality) were assessed using binary logistics and multivariable logistics regression controlling for those explanatory variables with a p-value < 0.05. Odds ratios (OR) and adjusted odds ratios (aOR) with 95% CI were presented. The association between average PaO2 on ECLS and duration of ECLS was further assessed using Pearson correlation. Overall FSS and subdomain FSS were reported as mean and standard deviation (SD) and paired Student’s t-test was used to compare scores at admission and at discharge. All p-values < .05 were considered significant (two-tailed). All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC) and R statistical software (version 4.0.2; R Core Team, 2020).

Results

Patient demographics and characteristics for overall cohort

During the period, there were 269 neonates with univentricular physiology who underwent Norwood operation. Of these, 65/269 (24%) required ECLS support (Figure 1). The median age at the time of surgery was 6 (IQR 4, 7) days, and the median weight was 3.2 (IQR 2.8, 3.5) kg. The most frequent cardiac diagnosis was hypoplastic left heart syndrome in 50/65 (77%) of cases, and mitral atresia with aortic atresia was the most common variant in 26/50 (51%). Patient demographics and clinical characteristics are presented in Table 1. Of note, none of our patients underwent a concomitant AVV repair at the time of Norwood’s operation.

thumbnail Figure 1

Flow chart of neonates requiring extracorporeal life support post-Norwood operation stratified based on PaO2 levels in the first 48-hours while on ECLS.
Table 1

Patient demographics and clinical characteristic for neonates requiring extracorporeal life support post-Norwood operation.

Cut-point analysis

Using ROC analysis, PaO2 > 182 mmHg had the optimal discriminatory ability for operative mortality (sensitivity of 68%, and specificity of 70%) and was therefore used to define hyperoxia in our exploratory analysis (Figure 2). The AUC for average PaO2 during CPB and subsequent mortality was 0.69, (95% CI: 0.58–0.81; p = 0.001). When using the PaO2 > 182 mmHg threshold 34/65 were in the hyperoxia group. On univariable analyses, this designation of hyperoxia was associated with more Sano shunts/RV-PA conduits (82% vs. 29%, p < 0.001), had longer median CPB times (187 vs. 165 min, p = 0.023), had higher median VIS-scores in the first 24-hours and hours 24–48, [(25 vs. 20, p = 0.027), and (30 vs. 23, p = 0.017) respectively], higher rates of central ECLS-cannulation (85% vs. 47%, p = 0.003), shorter median duration from CICU arrival to ECLS-cannulation (13.3 vs. 232.6 h, p = 0.003), higher serum lactate within 2-hours from ECLS-canulation (14.65 vs. 5.8, p = 0.01), and had higher flows in the first 4-hours of ECLS (152.7 vs. 124.1, p < 0.05). Although the CICU, postoperative, and overall hospital length of stay was shorter in the hyperoxia group, the mortality rate was significantly higher (77% vs. 39%, p = 0.005) Table 2. The causes of comorbidity and death are listed in Table 3. Of the 65 patients who required post-Norwood ECLS, only 6 patients (9.2%) required reintervention [5 aortic arch augmentation/revision of DKS (Damus Kaye Stansel), and 1 patient required shunt revision].

thumbnail Figure 2

Receiver operating characteristic curve (ROC) identifying the optimal discriminatory cut-point for operative mortality was PaO2 = 182 mmHg (sensitivity 68%, and specificity 70%).
Table 2

Patient demographics and clinical characteristics for neonates requiring extracorporeal life support post-Norwood operation stratified by PaO2 levels into hyperoxia group (PaO2 > 182 mmHg) and non-hyperoxia Group (PaO2 ≤ 182 mmHg).

Table 3

Causes of comorbidity and death, and reintervention for patients requiring ECLS post-Norwood Operation.

Patient demographics and characteristics for overall cohort stratified by timing of ECLS initiation

We then stratified patients into two groups based on the timing of initiation of ECLS post-Norwood (<5 days post-Norwood vs. ≥5 days post-Norwood). Patients in the early group had higher median PaO2 in the first 48 h of ECLS (274.6 mmHg, IQR 166.24, 313.12 vs. 101.79 mmHg, IQR 67.70, 201.60, p < 0.001), had higher rates of central vs. peripheral cannulation (85% vs. 37%, p < 0.0001), had higher serum lactate within 2 h of ECLS initiation 12.85 (IQR 5.12, 15.23) vs. 5.74 (IQR 3.0, 12.20), p = 0.02, and had shorter CICU length of stay (LOS), postoperative LOS, and overall hospital LOS. A full comparison between the 2 groups is shown in Supplemental Table 1.

Functional Status Scale (FSS)

The mean total FSS score for survivors in the non-hyperoxia group increased from 6 (SD 0) on admission/baseline to 8.4 (SD 1.2) at discharge (p < 0.0001), while the mean total FSS score for survivors in the hyperoxia-group increased from 6 (SD 0) on admission/baseline to 8.8 (SD 1.4) at discharge (p = 0.0008). Comparisons between different FSS domains on admission and discharge are presented in Table 4. The mean FSS score difference between the two groups was 0.4 (95% CI: −0.9, 1.6, p = 0.512). Of the 27 overall survivors, 19/27 (70%) were from the non-hyperoxia group and 8/27 (30%) were from the hyperoxia group. We failed to identify an association between designation as “hyperoxia” and new morbidity, or unfavorable outcome (Table 5).

Table 4

Functional Status Scale (FSS) for post-Norwood ECLS survivors on admission and discharge stratified by PaO2 levels into hyperoxia group (PaO2 > 182 mmHg) and non-hyperoxia group (PaO2 ≤ 182 mmHg).

Table 5

New morbidity and unfavorable functional outcome for overall survivors who required ECLS post-Norwood operation stratified by PaO2 levels into hyperoxia and non-hyperoxia groups based on functional status scale change from admission to discharge.

Outcomes analysis

In univariable analysis, using the ROC curve, PaO2 > 182 mmHg was associated with higher odds of mortality [OR 5.2 (95% CI: 1.8–15.0), p = 0.003]. However, the association was insignificant when controlling for the source of pulmonary blood flow, CPB time, and post-Norwood VIS score at 48 h [OR 3.1 (95% CI: 0.8–12.3), p = 0.104]. No difference in stage II or III AKI or PPLOS was detected between the hyperoxia and non-hyperoxia-groups (Table 6). The association of average PaO2 and CPB time is graphically demonstrated in Figure 3, with a correlation coefficient of 0.4 (95% CI: 0.1–0.6, p = 0.003).

thumbnail Figure 3

Scatterplot illustrating the association of average PaO2, ECLS duration, and mortality in neonates requiring ECLS support post-Norwood operation.
Table 6

Outcomes of neonates requiring extracorporeal life support post-Norwood operation using univariable and multivariable regression analysis.

Discussion

Despite advances in cardiac surgery and extracorporeal technology, morbidity and mortality persist. Many of the risk factors for poor outcomes, including weight and surgical complexity are not modifiable. Thus, there is value in identifying practice-based risk factors to improve outcomes. We describe the relationship between hyperoxia in the first 48-hours while on ECLS and mortality in an unadjusted analysis with an OR of 5.15. However, this association did not persist when adjusting for confounding variables (source of pulmonary blood flow, CPB time, and post-Norwood VIS score at 48 h). It is possible that this lack of association was due to inadequate sample size. There was no significant association seen with AKI or PPLOS. Although oxygen administration was not standardized, there were important differences in the treatment groups. The hyperoxia group had different operative strategies and higher markers of illness, however received earlier ECLS with greater support.

In other critical illness settings, an association between excessive oxygen delivery with poor clinical outcomes has been reported. In patients requiring ECLS for cardiac arrest, hyperoxia (as defined by a mean PaO2 > 193 Torr) was associated with 30-day mortality and the need for dialysis [1, 21, 32]. Several reports of neonates with asphyxia have demonstrated an association between hyperoxia and a risk of brain injury and mortality [1, 33, 34]. In a prior report we showed that a substantial portion of infants undergoing cardiac surgery using CPB were exposed to hyperoxia and patients in the hyperoxia group had four-fold greater odds of mortality within 30 days of surgery [14]. This current report supports earlier findings that hyperoxia is likely associated with worse outcomes. However, understanding of particular populations at risk remains unclear as some studies fail to demonstrate an association between hyperoxia and mortality [35].

Despite previous studies, there is no generally accepted definition of pathologic hyperoxia. Injurious hyperoxia may vary by patient population and clinical context [32]. As we know, the oxygen content of blood consists of bound oxygen to hemoglobin, and dissolved oxygen in the form of PaO2. Despite knowing that the bound oxygen by far is the main contributor for oxygen content in blood, the dissolved oxygen (PaO2) is what is important at the cellular level. Poor outcomes may occur when PaO2 exceeds a certain threshold of antioxidation systems of the body. This is biologically plausible as endogenous antioxidants may prevent oxidative stress at lower PaO2. When high amounts of oxygen are introduced to previously ischemic tissues, this leads to the generation of reactive oxygen species (ROS) and activation of inflammatory pathways via cytokines and other immunological signaling pathways. The generation of oxygen free radicals causes damage to the cell membrane integrity due to lipid peroxidation and protein changes, ultimately resulting in premature cell death [36]. Production of ROS can result in the dysfunction of organ systems including the immune system. This dysregulation may result in multiorgan dysfunction in the form of renal failure, cardiac dysfunction, and respiratory failure. These may ultimately increase the overall risk of morbidity and mortality [37–42]. In patients who have experienced cardiac arrest or resuscitation aftershock, an increase in ROS may deplete plasma antioxidant potential which may lower the threshold for subsequent oxidative injury [32]. This effect may be more pronounced in neonates and infants as they are known to have immature antioxidant defenses and thus may be more susceptible to ROS [1]. The effect of hyperoxia may be further pronounced in patients with cyanotic heart disease as they have significantly lower PaO2 at baseline. It is not known if the antioxidant systems of the body are downregulated in patients with lower baseline PaO2. Although unknown, it is plausible that these patients are more vulnerable to supraphysiologic oxygen.

Interestingly we found that the hyperoxia cohort did not have longer times from the OR/CICU arrival to initiation of ECLS, and 4 h after initiation on ECLS, they had a higher median rate of flow (Table 2). This suggests that the hyperoxia cohort did not have a delay in support or inadequate ECLS support. However, the hyperoxia cohort conversely had a higher serum lactate prior to ECLS initiation. It is difficult to account for these differences, however they support the benefits of a prospective and controlled study.

Because there is no generally accepted definition of hyperoxia in this population, we used an ROC curve analysis to determine which PaO2 values may be associated with an adverse outcome. A similar strategy was employed in previous reports. Sznycer-Taub et al. evaluated hyperoxia in infant cardiac patients supported on VA-ECMO and found that a PaO2 of 193 Torr in the first 48 hours was determined to have an association with 30-day mortality [1]. Using a similar strategy, Beshish showed that a PaO2 of 313 Torr for infants undergoing cardiac surgery utilizing CPB was associated with 30-day mortality [14]. Our cut-off definition of hyperoxia was very close to that identified by Sznycer-Taub although the patient population was slightly different, as the former captured all infants on postoperative VA-ECMO. Our study supports the findings of this prior report as we evaluated a more homogenous and larger patient population who required ECLS following Norwood operation (n = 65) using a similar hyperoxia definition.

Limitations

Our findings are subject to all limitations inherent to single-center retrospective cohort studies. Although PaO2 levels were obtained at dedicated time intervals, it is not possible to discern the effect of time spent in a hyperoxia state as opposed to the effects of acutely high PaO2 levels. Additionally, there may be some bias as to which patients are exposed to hyperoxia. Our center does not have a standard protocol dictating goal PaO2 levels, however, this study builds support for such a practice. The majority of our cohort had a PaO2 level over 200 mmHg while on ECLS limiting our ability to study the relationship between lower oxygen tension levels and outcomes. This data may not be generalizable to centers that target lower PaO2 values. The retrospective nature of this study prevented our description of other surrogate markers of cardiac output such as ECLS flows, pulsatility, or Qp:Qs. There may be concerns about generalizability, as our incidence of ECLS (24%) was higher than the 8–20% in other reports [4, 5, 7–9]. This may be due to a lower threshold for ECLS at our center, higher complexity of patients, or variations in surgical strategy. Notably, despite the higher rate of ECLS, Norwood operation survival in our center (86%) is similar to STS benchmark public outcome reporting (88%) [43, 44]. It is important to note that some baseline characteristics differed in the hyperoxia group, notably including time to cannulation and site of cannulation. It is potential that these factors were strongly associated with patient outcomes and are variables that must be considered in future investigations. It is unknown if cannulation position affects oxygen delivery and hyperoxia exposure and is a potential topic for future studies. Many of these limitations can be addressed in a multicenter validation study, which our group is currently pursuing, and ultimately a randomized controlled trial. We also acknowledge that after controlling for confounders, hyperoxia (PaO2 > 182 mmHg) was not associated with outcomes. This may be due to a small sample size and can be addressed in a multicenter validation study.

Conclusions

Of the 65 patients who required ECLS post-Norwood operation, 27 (42%) survived hospital discharge. Using a derived cut point, hyperoxia was associated with 5× higher odds of mortality in unadjusted analysis. When adjusted for confounding variables, there was no association with mortality. Hyperoxia was not associated with the development of AKI, PPLOS, or a new functional status morbidity. Multicenter and prospective evaluation of this modifiable risk factor is imperative to improve the care of this high-risk cohort.

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

A. B. and D. K. designed the study. Data collection was completed by S. E., A. E., A. H., S. P., A. A., A. H., J. D., A. A., and A. B. Y. X., and D. K. analyzed the data. A.B. wrote the initial manuscript, and all authors contributed to subsequent revisions and the final version.

Ethics approval

This study was approved by the Children’s Healthcare of Atlanta Institutional Review Board: Study ID No. (IRB# 00001119), approved on 07/19/2021.

Supplementary Material

Supplemental Table 1: Patient Demographics and Clinical Characteristics for Neonates Requiring Extracorporeal Life Support post-Norwood Operation Stratified by Timing of ECLS initiation (<5 days post-Norwood vs. >5 days post-Norwood). Access here

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Cite this article as: Beshish AG, Aljiffry A, Xiang Y, Evans S, Scheel A, Harriott A, Patel S, Amedi A, Harding A, Davis J, Shashidharan S & Kwiatkowski DM. Determining the association of hyperoxia while on extracorporeal life support with mortality in neonates following Norwood operation. J Extra Corpor Technol 2024, 56, 174–184. https://doi.org/10.1051/ject/2024020.

All Tables

Table 1

Patient demographics and clinical characteristic for neonates requiring extracorporeal life support post-Norwood operation.

In the text
Table 2

Patient demographics and clinical characteristics for neonates requiring extracorporeal life support post-Norwood operation stratified by PaO2 levels into hyperoxia group (PaO2 > 182 mmHg) and non-hyperoxia Group (PaO2 ≤ 182 mmHg).

In the text
Table 3

Causes of comorbidity and death, and reintervention for patients requiring ECLS post-Norwood Operation.

In the text
Table 4

Functional Status Scale (FSS) for post-Norwood ECLS survivors on admission and discharge stratified by PaO2 levels into hyperoxia group (PaO2 > 182 mmHg) and non-hyperoxia group (PaO2 ≤ 182 mmHg).

In the text
Table 5

New morbidity and unfavorable functional outcome for overall survivors who required ECLS post-Norwood operation stratified by PaO2 levels into hyperoxia and non-hyperoxia groups based on functional status scale change from admission to discharge.

In the text
Table 6

Outcomes of neonates requiring extracorporeal life support post-Norwood operation using univariable and multivariable regression analysis.

In the text

All Figures

thumbnail Figure 1

Flow chart of neonates requiring extracorporeal life support post-Norwood operation stratified based on PaO2 levels in the first 48-hours while on ECLS.
In the text
thumbnail Figure 2

Receiver operating characteristic curve (ROC) identifying the optimal discriminatory cut-point for operative mortality was PaO2 = 182 mmHg (sensitivity 68%, and specificity 70%).
In the text
thumbnail Figure 3

Scatterplot illustrating the association of average PaO2, ECLS duration, and mortality in neonates requiring ECLS support post-Norwood operation.
In the text

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