Renal memory in the Glenn-Fontan acute kidney injury continuum: A window for early renal protection

Renal memory in the Glenn-Fontan acute kidney injury continuum: A window for early renal protection | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Renal memory in the Glenn-Fontan acute kidney injury continuum: A window for early renal protection Eitan Keizman, Asaf Mandel, Yshia Langer, Salmas Watad, Hiba Abuelhija, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6632404/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Acute kidney injury (AKI) is a common and serious complication following Fontan completion in children with single ventricle physiology. While risk factors for post-Fontan AKI are well studied, it remains unknown whether prior AKI after the Glenn procedure can predict subsequent renal injury, potentially informing risk stratification and management. Methods This retrospective cohort study included 98 pediatric patients who underwent Fontan surgery between 2009 and 2016. AKI after both Glenn and Fontan procedures was assessed using KDIGO and pRIFLE classification systems. Statistical analyses included odds ratios, cross-tabulations, and correlation tests to evaluate the relationship between post-Glenn and post-Fontan AKI. Results Among patients who developed AKI after Glenn, 87.5% (KDIGO) and 80% (pRIFLE) experienced AKI again after Fontan. Patients with Glenn-related AKI were over 14 times more likely to develop post-Fontan AKI (OR = 14.36, p = 0.001). Notably, 100% of patients with severe (“failure” category) Glenn AKI developed Fontan AKI, and 75% remained in the severe category. Despite weak correlation coefficients, categorical analysis highlighted a clinically significant predictive relationship. Only 2% required ECMO post-Fontan, and overall mortality was 5.1%. Conclusions AKI following the Glenn procedure is a strong predictor of subsequent AKI after Fontan completion. This finding suggests a possible continuum of renal vulnerability across staged palliation, supporting the concept of "renal memory." Integrating prior renal response into pre-Fontan risk assessment could enable early intervention and tailored perioperative strategies. Acute Kidney Injury Congenital Heart Disease Single Ventricle Glenn Fontan Figures Figure 1 Figure 2 Introduction The currently accepted management of single ventricle defects, regardless of the underlying cardiac anatomy, consists of a three-stage surgical palliation process, with the goal of reaching a circulation in sequence [1]. While the first stage intervention depends on the anatomy and associated physiology of the CHD, the second and third stages, namely, Glenn and Fontan procedures, are generally similar to all patients who are destined to a single ventricle palliation. Acute kidney injury (AKI) is a common and clinically significant complication following Fontan completion, reported in up to 52% of patients [2,3,4]. Children undergoing the Fontan procedure are particularly susceptible to AKI due to reduced glomerular filtration rates secondary to chronic low cardiac output and systemic venous hypertension inherent to the Fontan physiology, in which the systemic venous return is directly connected to the pulmonary arteries without a sub pulmonary ventricle [5]. Multiple retrospective cohort studies have demonstrated that AKI after Fontan is associated with several risk factors [6], including elevated preoperative pulmonary vascular resistance, prolonged cardiopulmonary bypass (CPB) times, and, notably, the unique hemodynamics of the total cavo-pulmonary connection, even in off-pump procedures [7-10]. The occurrence of AKI in this population has been linked to adverse postoperative outcomes such as increased need for inotropic support, extended durations of mechanical ventilation and hospitalization, and higher rates of Fontan failure and takedown [11-13]. While numerous studies have characterized the incidence and risk factors for AKI following individual surgical stages in single ventricle palliation, a critical gap exists in our understanding of how renal injury patterns may persist or evolve across the staged procedures. This study addresses this gap by investigating whether AKI following the Glenn procedure serves as a predictor for subsequent AKI after Fontan completion. The clinical significance of establishing such a relationship cannot be overstated, as it would fundamentally change preoperative risk assessment before Fontan surgery and potentially alter perioperative management strategies. Identifying children at elevated risk for post-Fontan AKI based on their previous renal response could enable targeted preventive interventions, more vigilant monitoring, and potentially earlier nephrology consultation in this vulnerable population. Furthermore, understanding the continuum of renal vulnerability across surgical stages may provide insight into the underlying pathophysiological mechanisms of AKI in the unique hemodynamic environment of single ventricle circulation, potentially informing novel renoprotective approaches that span the entire surgical palliation process rather than focusing on isolated procedures. The aim of this study was to evaluate whether such an association exists, and to determine its magnitude. Methods Study Design, Ethics, and Patients This retrospective cohort study included all patients who underwent the Fontan procedure at the Edmond and Lily Safra Children's Hospital between October 2009 and May 2016. The study was approved by the Institutional Review Board (IRB) of the Chaim Sheba Medical Center, Tel Hashomer, Israel. The requirement for informed consent was waived. The exclusion criteria were incomplete data regarding either previous Glenn procedure or post-operative AKI after the Glenn or the Fontan procedures. Data Collection Demographic and perioperative data were collected from electronic medical records, including age and weight at time of surgery, time elapsed between surgeries, type of Fontan procedure and size of Gore-Tex conduit used. Intraoperative variables included CPB time and aortic cross-clamp time. Postoperative variables included urine output and renal function tests to determine AKI, need for extracorporeal membrane oxygenation (ECMO) and in-hospital mortality. Definition and Assessment of Acute Kidney Injury AKI was assessed using two standardized classification systems: the Kidney Disease: Improving Global Outcomes (KDIGO) criteria and the Pediatric Risk, Injury, Failure, Loss, End-stage renal disease (pRIFLE) criteria [14, 15]. Each patient was categorized based on the worst postoperative renal function during hospitalization. For further analysis, a binary AKI variable was created, in which AKI was defined as any classification other than "none". Figure 1 depicts the stages of renal failure according to which our patients were classified. We employed both KDIGO and pRIFLE classification systems to comprehensively assess AKI. The KDIGO criteria provides standardized staging based on absolute and relative changes in serum creatinine, making it sensitive to acute changes regardless of baseline function. The pRIFLE classification was specifically developed for pediatric populations and incorporates estimated creatinine clearance, thereby accounting for developmental changes in renal function across different age groups—particularly relevant as the Glenn procedure is typically performed in infancy while the Fontan is completed in early childhood. Using both systems enhanced the robustness of our findings while allowing for comparison with the broader literature on pediatric AKI. Statistical analysis Data were analyzed using IBM SPSS Statistics for Windows, Version 28.0 (IBM Corp., Armonk, NY, USA). All variables were assessed for completeness, and descriptive statistics were calculated for the full cohort of patients with available data. Continuous variables were presented as means ± standard deviations (SD), medians, and interquartile ranges (IQR) when appropriate. Categorical variables were summarized as frequencies and percentages. Cases with missing data for key variables were excluded from respective analyses using listwise deletion. No imputation was performed. All statistical tests were two-sided, and a p-value of <0.05 was considered statistically significant unless otherwise stated. Comparison of AKI Outcomes: Fontan vs. Glenn The association between AKI following Glenn and Fontan procedures was investigated using multiple complementary statistical approaches. Each AKI classification system was analyzed separately. Cross-tabulations were constructed to examine the distribution of patients across AKI categories after both procedures. Fisher's exact test was utilized to assess the statistical significance of the association between post-Glenn and post-Fontan AKI, with odds ratios (OR) calculated to quantify the strength of association. Chi-square analyses were performed to evaluate categorical distribution patterns across the full spectrum of AKI severity classifications. For correlation analyses, both Pearson's product-moment correlation coefficient (r) and Spearman's rank correlation coefficient (ρ) were calculated to assess linear and monotonic relationships, respectively, between post-Glenn and post-Fontan AKI severity. Transition probabilities were computed to determine the likelihood of developing post-Fontan AKI conditional on post-Glenn AKI status. This was further stratified by analyzing transitions between specific severity categories to identify patterns of persistent or progressive renal dysfunction. Given the ordinal nature of the AKI classification systems and potential subgroup sample size limitations, results were interpreted with consideration for both statistical significance and clinical relevance. Association Between AKI Severity and Intraoperative Variables To evaluate the relationship between AKI severity (KDIGO and pRIFLE) and CPB or aortic cross-clamp times (both continuous), we used Eta correlation coefficients , as these are suitable for associations between an ordinal dependent variable and a continuous independent variable. The presence and direction of linear trends were examined, and statistical significance was assessed based on asymptotic standard errors. Results A total of 112 pediatric patients undergoing Fontan procedure were initially identified. Of these, 98 patients (87.5%) had complete datasets and were included in the final analysis. The median age at Fontan surgery was 56 months (mean 64.2 ± 34.7 months), with a median weight of 15.0 kg (mean 17.3 ± 7.8 kg). The median interval between Glenn procedure and Fontan was 38.5 months (mean 36.4 ± 41.2 months), and the most common surgical approach was fenestrated Fontan (49.0%), followed by non-fenestrated Fontan (39.8%). Regarding the operative data, the mean CPB time was 72.4 ± 33.6 minutes, and mean aortic cross-clamp time was 7.3 ± 24.3 minutes. Postoperatively, only 2 patients (2.0%) required ECMO support post-Fontan, and the overall postoperative mortality rate was 5.1% (5 out of 98 patients) (Table 1). Incidence of Postoperative Acute Kidney Injury The incidence of AKI post-Fontan varied depending on the classification system used and is presented in Table 2. According to KDIGO criteria, 74.5% of patients developed some degree of AKI: 38.8% were classified as stage 1, 22.4% as stage 2, and 13.3% as stage 3. Using pRIFLE, 82.7% had AKI: 48.0% at the "risk" level, 22.4% as "injury", and 12.2% as "failure". The distribution of AKI post-Glenn and post-Fontan is presented in Figure 2. KDIGO Classification Analysis The KDIGO classification showed that 87.5% of patients who had AKI following the Glenn procedure also developed AKI after the Fontan procedure. The odds ratio of 14.36 (p = 0.001) demonstrates that patients with any degree of KDIGO-defined AKI after the Glenn procedure were over 14 times more likely to develop AKI after the Fontan procedure compared to those without post-Glenn AKI (Table 3). pRIFLE Classification Analysis Using pRIFLE criteria, a similar pattern was observed, with 80% of patients who experienced AKI after the Glenn procedure subsequently developing AKI after the Fontan procedure. Among those in the "injury" or "failure" categories post-Glenn, 65% remained in these severe categories after the Fontan procedure (Table 3). Correlation Between AKI Post-Glenn and Post-Fontan Both Pearson's and Spearman's correlation analyses yielded very weak positive correlations (r = 0.039, p = 0.745; ρ = 0.030, p = 0.801, respectively) between post-Glenn and post-Fontan AKI, regardless of the classification system used. However, these metrics may underestimate the strength of association due to the ordinal nature of the data, small subgroup sizes, and potential non-linearity of the relationship. Despite the lack of statistical significance in correlation coefficients, the high proportion of patients with post-Glenn AKI who subsequently developed post-Fontan AKI, particularly in the more severe categories, suggests a clinically relevant predictive relationship. This discrepancy highlights the importance of considering both statistical significance and clinical relevance when interpreting these results. Cross-tabulation analysis revealed that 93% of patients who experienced AKI (any severity) after the Glenn procedure subsequently developed AKI following the Fontan procedure. Notably, all patients (100%) who were classified in the "failure" category post-Glenn experienced AKI after Fontan, with 75% continuing to demonstrate severe renal dysfunction ("failure" category). Table 4 depicts the statistical correlation between Glenn and Fontan. Discussion This study demonstrates, for the first time to our knowledge, a significant association between AKI following the Glenn procedure and the subsequent development of AKI after Fontan completion. Specifically, patients who experienced AKI post-Glenn had a substantially higher likelihood of developing AKI post-Fontan, with a particularly strong association seen in those with high-grade AKI. This association remained significant across both KDIGO and pRIFLE classification systems, reinforcing the robustness of this finding. The statistical analysis of our data revealed an important methodological consideration when assessing the relationship between post-Glenn and post-Fontan AKI. While both Pearson's and Spearman's correlation analyses yielded very weak positive correlations (r = 0.039, p = 0.745; ρ = 0.030, p = 0.801, respectively) between AKI severity across procedures, we recognize several statistical limitations that may explain this apparent discrepancy with our other findings. First, correlation coefficients are inherently limited in capturing relationships between ordinal categorical variables with few levels and potentially non-linear associations. Second, the relatively small sample size, particularly when stratified across multiple AKI categories, further reduces the statistical power of these correlation tests. Third, the high baseline incidence of post-Fontan AKI even in patients without previous renal injury creates a ceiling effect that mathematically constrains correlation values. Despite these statistical limitations, the clinically significant finding that 87.5% of patients with post-Glenn AKI subsequently developed post-Fontan AKI (OR = 14.36, p = 0.001) provides compelling evidence for a strong predictive relationship that transcends the limitations of simple correlation metrics. This emphasizes the importance of considering multiple complementary statistical approaches when investigating complex clinical phenomena. Establishing risk factors for AKI development is crucial for the postoperative management of Fontan patients as kidney involvement carries poor outcome, Fontan failure and increased mortality [16-18]. Fontan patients who suffered AKI postoperatively have the worst short-term outcomes and an astonishingly high rate of 1-year mortality, reaching numbers as high as 72% [4, 19]. According to previous reports, up to 52% of patients undergoing the Fontan procedure develop AKI in the immediate postoperative course [4,6]. Known risk factors for AKI post Fontan include younger age at surgery, presence of AVVR, elevated pulmonary vascular resistance (PVR)[7,8], and prolonged CPB time [9,10]. However, a possible relationship between AKI post-Fontan and AKI following prior Glenn surgery has not been previously investigated [20]. One explanation for the observed association may lie in the unique cardiac physiology and hemodynamics of single-ventricle circulation. The Fontan and Glenn procedures both culminate in a circulation where pulmonary blood flow is not supported by a pump, driven mostly by elevated systemic venous pressure [3]. This physiology inherently predisposes patients to increased central venous pressure and reduced cardiac output, particularly in the immediate postoperative period—both of which may lower renal perfusion pressure and contribute to AKI [4,21]. The degree of susceptibility may also depend on specific cardiac anatomical features, such as ventricular morphology. While patients with severe AVVR are not typically candidates for Fontan completion, more subtle valvular insufficiency or a dominant right ventricular morphology may still influence hemodynamic stability and renal perfusion [20]. Previous reports have linked right ventricular dominance to poorer short- and long-term outcomes [18]. Beyond the cardiac factors, systemic or metabolic contributors likely play a significant role. Individual sensitivity to nephrotoxic insults—such as contrast media, anesthetic agents, administration of blood products or commonly used antibiotics—could represent a patient-specific predisposition [20]. These substances are frequently used both preoperatively and intraoperatively during the Glenn and Fontan hospitalizations, and a consistent metabolic reaction across exposures may explain the observed continuity in AKI development. If such sensitivity is indeed intrinsic to the patient, this would suggest that renal susceptibility is, at least in part, determined by stable biological characteristics, such as genetic predisposition, preexisting subclinical tubular damage, or altered drug metabolism [20,23]. A third plausible explanation—and one that warrants further investigation—is the concept of “renal memory.” It is conceivable that kidneys previously exposed to the inflammatory and ischemic stress of CPB, combined with altered hemodynamics and volume shifts, sustain a level of subclinical or structural injury that renders them more vulnerable to future insults [24]. If renal parenchymal injury initiated after the Glenn procedure is not fully reversible, subsequent similar physiological stress during the Fontan procedure may precipitate a more pronounced decline in renal function. This notion raises a broader question—if kidneys “remember,” could other end organs, such as the liver or lungs, also exhibit similar vulnerability patterns across staged single-ventricle palliation? In order to better understand the possible phenomena of “renal memory”, the pathophysiology of AKI should be considered in the settings of the somewhat common physiology of a post-Glenn and post-Fontan states. Traditionally, the causes of AKI are classified into prerenal, renal, and postrenal factors. This classification provides information about the underlying pathophysiology of AKI. However, the causes of AKI in the clinical settings are difficult to differentiate clearly. In the settings of recovering from on-pump procedure, the prerenal cause of AKI is the most common etiology and may be prolonged and contribute to a renal parenchymal damage, which progresses and eventually give rise to an intrinsic kidney injury [24]. Previous investigations have shown that in addition to hemodynamic alterations, inflammation and direct nephrotoxic effects on tubular cells play crucial roles in inducing AKI in patients after cardiac surgery [25,26]. This, in addition to the loss of tubular cells and the destruction nephron units occurring at the time of the Glenn procedure, or even from the first palliative procedure such as the Norwood procedure, altogether play a role in this suggested phenomenon of “renal memory” [26,28]. Taken together, these findings raise an important clinical question: is the primary driver of AKI post-Fontan related to the heart and its circulation, to the patient’s inherent systemic or metabolic response, or to a residual renal vulnerability—“renal memory”—from prior surgical insult? It is likely that all three mechanisms interact, compounding the risk of renal injury in a vulnerable subgroup of patients [29]. In light of these insights, consideration of a patient’s renal response to the Glenn procedure should be integrated into the preoperative evaluation before Fontan completion. Recognizing prior AKI as a strong predictor of future renal complications allows for more tailored both peri- and post-operative planning [19]. This may include careful assessment of contrast administration during pre-Fontan evaluation, closer fluid and hemodynamic monitoring, judicious use of nephrotoxic agents, consideration of off-pump strategies where feasible, and proactive nephrology involvement. Ultimately, improving renal outcomes after Fontan surgery may hinge on a more nuanced, longitudinal approach to renal vulnerability that begins long before the final stage of palliation. Limitations This study has several limitations. First, it is a single-center study, which may introduce selection bias and limit the generalizability of the findings. Additionally, its retrospective design is subject to inherent limitations, including potential inaccuracies in data collection and unmeasured confounding variables. As such, a causal relationship between AKI following the Glenn procedure and subsequent AKI after Fontan completion cannot be definitively established. Second, the use of urine output and serum creatinine as the sole markers for renal function is known to be imperfect, particularly in pediatric populations, and may not fully capture the extent of renal injury. Third, the majority of patients in this cohort experienced only mild degrees of AKI, which may limit the generalizability of the findings to those with more severe renal injury. Fourth, the study was limited to in-hospital measurements of creatinine levels, with no long-term follow-up data available on renal function after discharge. Finally, although several potentially modifiable risk factors for AKI were discussed, the study did not evaluate the efficacy of any specific preventive or therapeutic interventions, which will require future prospective studies. Conclusion The results of this study suggest a significant association between AKI following the Glenn procedure and subsequent AKI after Fontan completion. This finding raises the possibility of a form of “renal memory,” potentially driven by shared prerenal and intrinsic renal mechanisms inherent to single-ventricle physiology, as well as cumulative tubular injury beginning as early as the Glenn procedure stage or even earlier than that. Recognizing previous AKI post-Glenn as a potential predictor of adverse renal outcomes post-Fontan is crucial for preoperative risk assessment and postoperative management. Further research is warranted to elucidate the underlying pathophysiological mechanisms and explore strategies for renal protection in this vulnerable patient population. Declarations Ethical Approval and Consent to participate: The study was approved by the hospital IRB. Patient’ consent for participation – not relevant. Consent for publication: All authors consent for publication. Availability of supporting data: Supporting data are available upon reasonable request. Competing interests: The authors declare that they have no conflict of interest. Funding: None. Acknowledgment: None. Author Contribution E.K and U.P wrote wrote the manuscript. U.P and A.M concepted the idea.D.M A.S and E.K performed all the procedures. A.L is the cardiologist. all three edited the manuscript.R.K.L is the primary intensive care physician treating these patients in the postoperative course.Y.L and S.W edited the text and performed data collection. References Davies RR, Pizarro C. Decision-Making for Surgery in the Management of Patients with Univentricular Heart. Front Pediatr. 2015 Jul 27;3:61. doi: 10.3389/fped.2015.00061. PMID: 26284226; PMCID: PMC4515559. Talha Niaz, Elizabeth H. Stephens, MD, Stephen J. Gleich, Joseph A. Dearani, Jonathan N. Johnson,David J. Sas. 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Patient characteristics Patient characteristics at Fontan All patients (n=98) Age, months, mean (SD) 64.27 (34.74) Males, n 59, (60.7%) Weight (kg) 17.33 (7.81) Non-cardiac malformations, n 24 (24.4%) Left ventricular dominance, n 55 (56.1%) Right ventricular dominance, n 43 (43.9%) CPB time, minutes, mean (SD) 72.40 (33.60) Cross-clamp time, minutes, mean (SD) 7.28 (24.27) Goretex size, mm, mean (SD) 19.38 (1.26) Postoperative ECMO, n 2 (2.0%) Mortality, n 5 (5.1%) Table 1. The baseline and surgical characteristics and postoperative outcome of all the patients who underwent Fontan procedure. Abbreviations: CPB=cardiopulmonary bypass; ECMO = extracorporeal membrane oxygenation; PRBC=packed red blood cell. Table 2. Incidence of postoperative acute kidney injury Post Glenn (Stage 2) Post Fontan (Stage 3) KDIGO Stage 1 13 (17.1%) 38 (38.8%) Stage 2 3 (3.9%) 22 (22.4%) Stage 3 1 (1.3%) 13 (13.3%) pRIFLE Risk 29 (39.7%) 47 (48.0%) Injury 4 (5.5%) 22 (22.4%) Failure 0 (0.0%) 12 (12.2%) Loss – – End-stage – – Table 2. This table presents the distribution of AKI severity by stage following the Glenn (Stage 2) and Fontan (Stage 3) procedures, classified by KDIGO and pRIFLE criteria. A notable increase in moderate-to-severe AKI is observed post-Fontan, with KDIGO Stage 2–3 rising from 5.2% to 35.7% and pRIFLE Injury/Failure increasing from 5.5% to 34.6%. These shifts suggest a clear worsening of renal function following Fontan completion. Table 3. Statistical Analysis of the Association Between Post-Glenn and Post-Fontan AKI Statistical Test Classification System Value p-value Interpretation KDIGO Fisher's Exact Test [1,2,3] post-Glenn to [1,2,3] post-Fontan vs [0] post-Glenn to [1,2,3] post-Fontan OR = 14.36 0.001 Highly significant association Fisher's Exact Test [2,3] post-Glenn to [2,3] post-Fontan vs [0,1] post-Glenn to [2,3] post-Fontan OR = 9.47 0.001 Highly significant association Chi-Square Test χ² = 3.644, df = 9 0.933 Not significant, likely due to small subgroup sizes Pearson's Correlation r = 0.039 0.745 Very weak correlation, not significant pRIFLE Fisher's Exact Test [R,I,F] post-Glenn to [R,I,F] post-Fontan vs [None] post-Glenn to [R,I,F] post-Fontan OR = 8.97 0.001 Highly significant association Fisher's Exact Test [I,F] post-Glenn to [I,F] post-Fontan vs [None,R] post-Glenn to [I,F] post-Fontan OR = 8.92 0.001 Highly significant association Chi-Square Test χ² = 8.167, df = 6 0.226 Not significant, but shows clinical trend Spearman's Correlation ρ = 0.030 0.801 Very weak correlation, not significant Pearson's Correlation r = 0.039 0.745 Very weak correlation, not significant Table 3. This table highlights a key methodological insight: although Pearson's and Spearman's correlation tests showed very weak and non-significant associations between AKI severity post-Glenn and post-Fontan, these results are limited by statistical constraints. Correlation analyses are less effective for ordinal data with few categories, small sample sizes, and non-linear trends. Additionally, a ceiling effect—due to a high rate of post-Fontan AKI even in patients without prior AKI—likely suppressed correlation values. Despite this, Fisher’s Exact Tests revealed a strong and highly significant association, underscoring the predictive value of early AKI. Table 4. Transition Probabilities Between AKI States from Glenn to Fontan Procedures Initial State (Post-Glenn) Transition to Post-Fontan AKI Probability KDIGO [0] KDIGO [1,2,3] 0.807 KDIGO [1,2,3] KDIGO [1,2,3] 0.875 pRIFLE [R,I,F] pRIFLE [R,I,F] 0.80 pRIFLE [I,F] pRIFLE [I,F] 0.65 Table 4. This table summarizes the observed probabilities of AKI progression from post-Glenn to post-Fontan using both the KDIGO and pRIFLE classification systems. Patients with no initial AKI (KDIGO [0]) had an 80.7% chance of developing some degree of AKI post-Fontan, while those with pre-existing AKI (KDIGO [1,2,3]) had an even higher progression rate of 87.5%. Similarly, using the pRIFLE system, patients with any AKI post-Glenn (R/I/F) showed an 80% chance of maintaining or worsening their renal status post-Fontan. A more refined pRIFLE subset (I/F) indicated a 65% progression rate. These findings support a high likelihood of AKI persistence or deterioration, particularly in patients with pre-existing renal injury before Fontan completion. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6632404","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":457252742,"identity":"d4dd6321-e1fb-4a22-b82d-a3feac55a3a2","order_by":0,"name":"Eitan Keizman","email":"","orcid":"","institution":"Sheba Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Eitan","middleName":"","lastName":"Keizman","suffix":""},{"id":457252743,"identity":"cb82360e-ff2f-41e0-82eb-57d39afe29b0","order_by":1,"name":"Asaf Mandel","email":"","orcid":"","institution":"Hadassah University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Asaf","middleName":"","lastName":"Mandel","suffix":""},{"id":457252744,"identity":"6d8986db-96d4-4fac-bbce-bd3f0378f7a3","order_by":2,"name":"Yshia Langer","email":"","orcid":"","institution":"Hadassah University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yshia","middleName":"","lastName":"Langer","suffix":""},{"id":457252745,"identity":"2e39f55f-5e6d-46fa-9763-a8de92a1c3b9","order_by":3,"name":"Salmas Watad","email":"","orcid":"","institution":"Hadassah University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Salmas","middleName":"","lastName":"Watad","suffix":""},{"id":457252746,"identity":"d84f9290-77f1-4961-8901-74d1d04b4919","order_by":4,"name":"Hiba Abuelhija","email":"","orcid":"","institution":"Hadassah University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Hiba","middleName":"","lastName":"Abuelhija","suffix":""},{"id":457252747,"identity":"aa3b5ff4-c2f7-4b63-99d0-d46c2a5dd6a3","order_by":5,"name":"Alexander Lowenthal","email":"","orcid":"","institution":"Hadassah University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Lowenthal","suffix":""},{"id":457252748,"identity":"11a4783e-16fb-4969-a63b-b37e42726b89","order_by":6,"name":"Reut Kassif Lerner","email":"","orcid":"","institution":"Sheba Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Reut","middleName":"Kassif","lastName":"Lerner","suffix":""},{"id":457252749,"identity":"847f4414-e0bc-4384-89aa-5b793c5594c6","order_by":7,"name":"David Mishaly","email":"","orcid":"","institution":"Sheba Medical Center","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Mishaly","suffix":""},{"id":457252750,"identity":"89d96037-b618-45e1-986c-31a5e369e48e","order_by":8,"name":"Alain E. Serraf","email":"","orcid":"","institution":"Hadassah University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Alain","middleName":"E.","lastName":"Serraf","suffix":""},{"id":457252751,"identity":"626ee2f1-ef95-46e6-912e-b2037b3b50b5","order_by":9,"name":"Uri Pollak","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYFACxgYGhgKbBAaGBBDvAEQwoYCQFoM0dC0GhGwyOIymhQGPFoPbh9sefDA4n8ffnvz444+aOwz80scvMDzAp+VcYrvhDIPbxRJnnplJ8xx7xiDZl1OA12EGZxjbpHkMbic23EgwY2ZgOwwU4UkgRsu5xPk30j9//PGPeC0HEjfcyDGQ4G0DaWE/gFeL5BlGkF+SEzeeeVMmzdt3mEeyh4fhAD4tfGfYnz34UGGXOO94+uaPP74dluPnYX/48EcFbi1AwIbC4wEigwN4NaBrAQL2BwR0jIJRMApGwQgDAJ5+VskqmqP+AAAAAElFTkSuQmCC","orcid":"","institution":"Hadassah University Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Uri","middleName":"","lastName":"Pollak","suffix":""}],"badges":[],"createdAt":"2025-05-10 04:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6632404/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6632404/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82896477,"identity":"61d761a3-a1fc-4a4a-8d70-5b9f0143812c","added_by":"auto","created_at":"2025-05-16 12:58:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78020,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eKDIGO and pRIFLE classification \u0026nbsp;of acute kidney injury.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePostoperative AKI was defined twice, once with accordance to the Kidney Disease Improving Global Outcomes (KDIGO) criteria, and once with accordance to pediatric Risk, Injury, Failure, Loss or End-stage renal disease (pRIFLE). The pRIFLE criteria was reported in 2004 by the Acute Dialysis Quality Initiative and classifies AKI into three stages of severity, similarly to the KDIGO criteria that is determined by the serum creatinine levels, urine output, and two outcome stages.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: AKI\u003c/em\u003e=\u003cem\u003eacute kidney injury;\u003c/em\u003e \u003cem\u003eeCCT=estimated creatinine clearance; GFR=glomerular filtration rate.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6632404/v1/f62513a7e4dc215875ee5d91.jpg"},{"id":82897598,"identity":"ccfd4076-1994-471b-a846-dfbf22db60eb","added_by":"auto","created_at":"2025-05-16 13:06:11","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":33996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eComparison of acute kidney injury (AKI) severity classifications between Glenn and Fontan stages using pRIFLE (left) and KDIGO (right) criteria.\u003c/em\u003e Heatmaps illustrate the distribution of patients according to AKI severity scores at the Glenn stage (rows) and the Fontan stage (columns). The color intensity reflects the number of patients (scale shown on the right). The majority of patients remained in the same or adjacent AKI categories between stages, with minimal progression to the most severe categories (pRIFLE 3 or KDIGO 3). These data suggest relative stability in AKI classification over time, with some improvement or worsening in individual cases.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6632404/v1/791d2fb6e6f356a51c65c19c.jpg"},{"id":85123398,"identity":"9a6e1573-4a60-4ff1-887a-fbc902eeebf4","added_by":"auto","created_at":"2025-06-21 18:46:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":745297,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6632404/v1/1c4c6a25-01f8-45b6-a575-f582ad4e43c0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Renal memory in the Glenn-Fontan acute kidney injury continuum: A window for early renal protection","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe currently accepted management of single ventricle defects, regardless of the underlying cardiac anatomy, consists of a three-stage surgical palliation process, with the goal of reaching a circulation in sequence [1]. While the first stage intervention depends on the anatomy and associated physiology of the CHD, the second and third stages, namely, Glenn and Fontan procedures, are generally similar to all patients who are destined to a single ventricle palliation.\u003c/p\u003e\n\u003cp\u003eAcute kidney injury (AKI) is a common and clinically significant complication following Fontan completion, reported in up to 52% of patients\u0026nbsp;[2,3,4]. Children undergoing the Fontan procedure are particularly susceptible to AKI due to reduced glomerular filtration rates secondary to chronic low cardiac output and systemic venous hypertension inherent to the Fontan physiology, in which the systemic venous return is directly connected to the pulmonary arteries without a sub pulmonary ventricle [5]. Multiple retrospective cohort studies have demonstrated that AKI after Fontan is associated with several risk factors [6], including elevated preoperative pulmonary vascular resistance, prolonged cardiopulmonary bypass (CPB) times, and, notably, the unique hemodynamics of the total cavo-pulmonary connection, even in off-pump procedures [7-10]. The occurrence of AKI in this population has been linked to adverse postoperative outcomes such as increased need for inotropic support, extended durations of mechanical ventilation and hospitalization, and higher rates of Fontan failure and takedown [11-13].\u003c/p\u003e\n\u003cp\u003eWhile numerous studies have characterized the incidence and risk factors for AKI following individual surgical stages in single ventricle palliation, a critical gap exists in our understanding of how renal injury patterns may persist or evolve across the staged procedures. This study addresses this gap by investigating whether AKI following the Glenn procedure serves as a predictor for subsequent AKI after Fontan completion. The clinical significance of establishing such a relationship cannot be overstated, as it would fundamentally change preoperative risk assessment before Fontan surgery and potentially alter perioperative management strategies. Identifying children at elevated risk for post-Fontan AKI based on their previous renal response could enable targeted preventive interventions, more vigilant monitoring, and potentially earlier nephrology consultation in this vulnerable population. Furthermore, understanding the continuum of renal vulnerability across surgical stages may provide insight into the underlying pathophysiological mechanisms of AKI in the unique hemodynamic environment of single ventricle circulation, potentially informing novel renoprotective approaches that span the entire surgical palliation process rather than focusing on isolated procedures. The aim of this study was to evaluate whether such an association exists, and to determine its magnitude. \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eStudy Design, Ethics, and Patients\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective cohort study included all patients who underwent the Fontan procedure at the Edmond and Lily Safra Children\u0026apos;s Hospital between October 2009 and May 2016. The study was approved by the Institutional Review Board (IRB) of the Chaim Sheba Medical Center, Tel Hashomer, Israel. The requirement for informed consent was waived. The exclusion criteria were incomplete data regarding either previous Glenn procedure or post-operative AKI after the Glenn or the Fontan procedures.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData Collection\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDemographic and perioperative data were collected from electronic medical records, including age and weight at time of surgery, time elapsed between surgeries, type of Fontan procedure and size of Gore-Tex conduit used. Intraoperative variables included CPB time and aortic cross-clamp time. Postoperative variables included urine output and renal function tests to determine AKI, need for extracorporeal membrane oxygenation (ECMO) and in-hospital mortality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDefinition and Assessment of Acute Kidney Injury\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAKI was assessed using two standardized classification systems: the Kidney Disease: Improving Global Outcomes (KDIGO) criteria and the Pediatric Risk, Injury, Failure, Loss, End-stage renal disease (pRIFLE) criteria [14, 15]. Each patient was categorized based on the worst postoperative renal function during hospitalization. For further analysis, a binary AKI variable was created, in which AKI was defined as any classification other than \u0026quot;none\u0026quot;.\u0026nbsp;Figure 1 depicts the stages of renal failure according to which our patients were classified.\u003c/p\u003e\n\u003cp\u003eWe employed both KDIGO and pRIFLE classification systems to comprehensively assess AKI. The KDIGO criteria provides standardized staging based on absolute and relative changes in serum creatinine, making it sensitive to acute changes regardless of baseline function. The pRIFLE classification was specifically developed for pediatric populations and incorporates estimated creatinine clearance, thereby accounting for developmental changes in renal function across different age groups\u0026mdash;particularly relevant as the Glenn procedure is typically performed in infancy while the Fontan is completed in early childhood. Using both systems enhanced the robustness of our findings while allowing for comparison with the broader literature on pediatric AKI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were analyzed using IBM SPSS Statistics\u0026nbsp;for Windows, Version 28.0 (IBM Corp., Armonk, NY, USA). All variables were assessed for completeness, and descriptive statistics were calculated for the full cohort of patients with available data. Continuous variables were presented as means \u0026plusmn; standard deviations (SD), medians, and interquartile ranges (IQR) when appropriate. Categorical variables were summarized as frequencies and percentages. Cases with missing data for key variables were excluded from respective analyses using listwise deletion. No imputation was performed.\u0026nbsp;All statistical tests were two-sided, and a p-value of \u0026lt;0.05 was considered statistically significant unless otherwise stated.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparison of AKI Outcomes: Fontan vs. Glenn\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe association between AKI following Glenn and Fontan procedures was investigated using multiple complementary statistical approaches. Each AKI classification system was analyzed separately. Cross-tabulations were constructed to examine the distribution of patients across AKI categories after both procedures. Fisher\u0026apos;s exact test was utilized to assess the statistical significance of the association between post-Glenn and post-Fontan AKI, with odds ratios (OR) calculated to quantify the strength of association. Chi-square analyses were performed to evaluate categorical distribution patterns across the full spectrum of AKI severity classifications. For correlation analyses, both Pearson\u0026apos;s product-moment correlation coefficient (r) and Spearman\u0026apos;s rank correlation coefficient (\u0026rho;) were calculated to assess linear and monotonic relationships, respectively, between post-Glenn and post-Fontan AKI severity. Transition probabilities were computed to determine the likelihood of developing post-Fontan AKI conditional on post-Glenn AKI status. This was further stratified by analyzing transitions between specific severity categories to identify patterns of persistent or progressive renal dysfunction. Given the ordinal nature of the AKI classification systems and potential subgroup sample size limitations, results were interpreted with consideration for both statistical significance and clinical relevance.\u003c/p\u003e\n\u003ch4\u003eAssociation Between AKI Severity and Intraoperative Variables\u003c/h4\u003e\n\u003cp\u003eTo evaluate the relationship between AKI severity (KDIGO and pRIFLE) and CPB or aortic cross-clamp times (both continuous), we used \u003cstrong\u003eEta correlation coefficients\u003c/strong\u003e, as these are suitable for associations between an ordinal dependent variable and a continuous independent variable. The presence and direction of linear trends were examined, and statistical significance was assessed based on asymptotic standard errors.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 112 pediatric patients undergoing Fontan procedure were initially identified. Of these, 98 patients (87.5%) had complete datasets and were included in the final analysis. The median age at Fontan surgery was 56 months (mean 64.2 \u0026plusmn; 34.7 months), with a median weight of 15.0 kg (mean 17.3 \u0026plusmn; 7.8 kg). The median interval between Glenn procedure and Fontan was 38.5 months (mean 36.4 \u0026plusmn; 41.2 months), and the most common surgical approach was fenestrated Fontan (49.0%), followed by non-fenestrated Fontan (39.8%). Regarding the operative data, the mean CPB time was 72.4 \u0026plusmn; 33.6 minutes, and mean aortic cross-clamp time was 7.3 \u0026plusmn; 24.3 minutes. Postoperatively, only 2 patients (2.0%) required ECMO support post-Fontan, and the overall postoperative mortality rate was 5.1% (5 out of 98 patients) (Table 1). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIncidence of Postoperative Acute Kidney Injury\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe incidence of AKI post-Fontan varied depending on the classification system used and is presented in Table 2. According to KDIGO criteria, 74.5% of patients developed some degree of AKI: 38.8% were classified as stage 1, 22.4% as stage 2, and 13.3% as stage 3. Using pRIFLE, 82.7% had AKI: 48.0% at the \u0026quot;risk\u0026quot; level, 22.4% as \u0026quot;injury\u0026quot;, and 12.2% as \u0026quot;failure\u0026quot;. The distribution of AKI post-Glenn and post-Fontan is presented in Figure 2.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKDIGO Classification Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe KDIGO classification showed that 87.5% of patients who had AKI following the Glenn procedure also developed AKI after the Fontan procedure. The odds ratio of 14.36 (p = 0.001) demonstrates that patients with any degree of KDIGO-defined AKI after the Glenn procedure were over 14 times more likely to develop AKI after the Fontan procedure compared to those without post-Glenn AKI (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003epRIFLE Classification Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eUsing pRIFLE criteria, a similar pattern was observed, with 80% of patients who experienced AKI after the Glenn procedure subsequently developing AKI after the Fontan procedure. Among those in the \u0026quot;injury\u0026quot; or \u0026quot;failure\u0026quot; categories post-Glenn, 65% remained in these severe categories after the Fontan procedure (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCorrelation Between AKI Post-Glenn and Post-Fontan\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBoth Pearson\u0026apos;s and Spearman\u0026apos;s correlation analyses yielded very weak positive correlations (r = 0.039, p = 0.745; \u0026rho; = 0.030, p = 0.801, respectively) between post-Glenn and post-Fontan AKI, regardless of the classification system used. However, these metrics may underestimate the strength of association due to the ordinal nature of the data, small subgroup sizes, and potential non-linearity of the relationship.\u003c/p\u003e\n\u003cp\u003eDespite the lack of statistical significance in correlation coefficients, the high proportion of patients with post-Glenn AKI who subsequently developed post-Fontan AKI, particularly in the more severe categories, suggests a clinically relevant predictive relationship. This discrepancy highlights the importance of considering both statistical significance and clinical relevance when interpreting these results.\u003c/p\u003e\n\u003cp\u003eCross-tabulation analysis revealed that 93% of patients who experienced AKI (any severity) after the Glenn procedure subsequently developed AKI following the Fontan procedure. Notably, all patients (100%) who were classified in the \u0026quot;failure\u0026quot; category post-Glenn experienced AKI after Fontan, with 75% continuing to demonstrate severe renal dysfunction (\u0026quot;failure\u0026quot; category). Table 4 depicts the statistical correlation between Glenn and Fontan.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study demonstrates, for the first time to our knowledge, a significant association between AKI following the Glenn procedure and the subsequent development of AKI after Fontan completion. Specifically, patients who experienced AKI post-Glenn had a substantially higher likelihood of developing AKI post-Fontan, with a particularly strong association seen in those with high-grade AKI. This association remained significant across both KDIGO and pRIFLE classification systems, reinforcing the robustness of this finding.\u003c/p\u003e\n\u003cp\u003eThe statistical analysis of our data revealed an important methodological consideration when assessing the relationship between post-Glenn and post-Fontan AKI. While both Pearson\u0026apos;s and Spearman\u0026apos;s correlation analyses yielded very weak positive correlations (r = 0.039, p = 0.745; \u0026rho; = 0.030, p = 0.801, respectively) between AKI severity across procedures, we recognize several statistical limitations that may explain this apparent discrepancy with our other findings. First, correlation coefficients are inherently limited in capturing relationships between ordinal categorical variables with few levels and potentially non-linear associations. Second, the relatively small sample size, particularly when stratified across multiple AKI categories, further reduces the statistical power of these correlation tests. Third, the high baseline incidence of post-Fontan AKI even in patients without previous renal injury creates a ceiling effect that mathematically constrains correlation values. Despite these statistical limitations, the clinically significant finding that 87.5% of patients with post-Glenn AKI subsequently developed post-Fontan AKI (OR = 14.36, p = 0.001) provides compelling evidence for a strong predictive relationship that transcends the limitations of simple correlation metrics. This emphasizes the importance of considering multiple complementary statistical approaches when investigating complex clinical phenomena.\u003c/p\u003e\n\u003cp\u003eEstablishing risk factors for AKI development is crucial for the postoperative management of Fontan patients as kidney involvement carries poor outcome, Fontan failure and increased mortality [16-18].\u0026nbsp;Fontan patients who suffered AKI postoperatively have the worst short-term outcomes and an astonishingly high rate of 1-year mortality, reaching numbers as high as 72% [4, 19]. According to previous reports, up to 52% of patients undergoing the Fontan procedure develop AKI in the immediate postoperative course [4,6]. Known risk factors for AKI post Fontan include younger age at surgery, presence of AVVR, elevated pulmonary vascular resistance (PVR)[7,8], and prolonged CPB time [9,10]. However, a possible relationship between AKI post-Fontan and AKI following prior Glenn surgery has not been previously investigated [20].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOne explanation for the observed association may lie in the unique cardiac physiology and hemodynamics of single-ventricle circulation. The Fontan and Glenn procedures both culminate in a circulation where pulmonary blood flow is not supported by a pump, driven mostly by elevated systemic venous pressure [3]. This physiology inherently predisposes patients to increased central venous pressure and reduced cardiac output, particularly in the immediate postoperative period\u0026mdash;both of which may lower renal perfusion pressure and contribute to AKI [4,21]. The degree of susceptibility may also depend on specific cardiac anatomical features, such as ventricular morphology. While patients with severe AVVR are not typically candidates for Fontan completion, more subtle valvular insufficiency or a dominant right ventricular morphology may still influence hemodynamic stability and renal perfusion [20]. Previous reports have linked right ventricular dominance to poorer short- and long-term outcomes [18].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBeyond the cardiac factors, systemic or metabolic contributors likely play a significant role. Individual sensitivity to nephrotoxic insults\u0026mdash;such as contrast media, anesthetic agents, administration of blood products or commonly used antibiotics\u0026mdash;could represent a patient-specific predisposition [20]. These substances are frequently used both preoperatively and intraoperatively during the Glenn and Fontan hospitalizations, and a consistent metabolic reaction across exposures may explain the observed continuity in AKI development. If such sensitivity is indeed intrinsic to the patient, this would suggest that renal susceptibility is, at least in part, determined by stable biological characteristics, such as genetic predisposition, preexisting subclinical tubular damage, or altered drug metabolism [20,23].\u003c/p\u003e\n\u003cp\u003eA third plausible explanation\u0026mdash;and one that warrants further investigation\u0026mdash;is the concept of \u0026ldquo;renal memory.\u0026rdquo; It is conceivable that kidneys previously exposed to the inflammatory and ischemic stress of CPB, combined with altered hemodynamics and volume shifts, sustain a level of subclinical or structural injury that renders them more vulnerable to future insults [24]. If renal parenchymal injury initiated after the Glenn procedure is not fully reversible, subsequent similar physiological stress during the Fontan procedure may precipitate a more pronounced decline in renal function. This notion raises a broader question\u0026mdash;if kidneys \u0026ldquo;remember,\u0026rdquo; could other end organs, such as the liver or lungs, also exhibit similar vulnerability patterns across staged single-ventricle palliation?\u003c/p\u003e\n\u003cp\u003eIn order to better understand the possible phenomena of \u0026ldquo;renal memory\u0026rdquo;, the pathophysiology of AKI should be considered in the settings of the somewhat common physiology of a post-Glenn and post-Fontan states. Traditionally, the causes of AKI are classified into prerenal, renal, and postrenal factors. This classification provides information about the underlying pathophysiology of AKI. However, the causes of AKI in the clinical settings are difficult to differentiate clearly. In the settings of recovering from on-pump procedure, the prerenal cause of AKI is the most common etiology and may be prolonged and contribute to a renal parenchymal damage, which progresses and eventually give rise to an intrinsic kidney injury [24]. Previous investigations have shown that in addition to hemodynamic alterations, inflammation and direct nephrotoxic effects on tubular cells play crucial roles in inducing AKI in patients after cardiac surgery [25,26]. This, in addition to the loss of tubular cells and the destruction nephron units occurring at the time of the Glenn procedure, or even from the first palliative procedure such as the Norwood procedure, altogether play a role in this suggested phenomenon of \u0026ldquo;renal memory\u0026rdquo; [26,28].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTaken together, these findings raise an important clinical question: is the primary driver of AKI post-Fontan related to the heart and its circulation, to the patient\u0026rsquo;s inherent systemic or metabolic response, or to a residual renal vulnerability\u0026mdash;\u0026ldquo;renal memory\u0026rdquo;\u0026mdash;from prior surgical insult? It is likely that all three mechanisms interact, compounding the risk of renal injury in a vulnerable subgroup of patients [29].\u003c/p\u003e\n\u003cp\u003eIn light of these insights, consideration of a patient\u0026rsquo;s renal response to the Glenn procedure should be integrated into the preoperative evaluation before Fontan completion. Recognizing prior AKI as a strong predictor of future renal complications allows for more tailored both peri- and post-operative planning [19]. This may include careful assessment of contrast administration during pre-Fontan evaluation, closer fluid and hemodynamic monitoring, judicious use of nephrotoxic agents, consideration of off-pump strategies where feasible, and proactive nephrology involvement. Ultimately, improving renal outcomes after Fontan surgery may hinge on a more nuanced, longitudinal approach to renal vulnerability that begins long before the final stage of palliation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First, it is a single-center study, which may introduce selection bias and limit the generalizability of the findings. Additionally, its retrospective design is subject to inherent limitations, including potential inaccuracies in data collection and unmeasured confounding variables. As such, a causal relationship between AKI following the Glenn procedure and subsequent AKI after Fontan completion cannot be definitively established. Second, the use of urine output and serum creatinine as the sole markers for renal function is known to be imperfect, particularly in pediatric populations, and may not fully capture the extent of renal injury. Third, the majority of patients in this cohort experienced only mild degrees of AKI, which may limit the generalizability of the findings to those with more severe renal injury. Fourth, the study was limited to in-hospital measurements of creatinine levels, with no long-term follow-up data available on renal function after discharge. Finally, although several potentially modifiable risk factors for AKI were discussed, the study did not evaluate the efficacy of any specific preventive or therapeutic interventions, which will require future prospective studies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results of this study suggest a significant association between AKI following the Glenn procedure and subsequent AKI after Fontan completion. This finding raises the possibility of a form of \u0026ldquo;renal memory,\u0026rdquo; potentially driven by shared prerenal and intrinsic renal mechanisms inherent to single-ventricle physiology, as well as cumulative tubular injury beginning as early as the Glenn procedure stage or even earlier than that. Recognizing previous AKI post-Glenn as a potential predictor of adverse renal outcomes post-Fontan is crucial for preoperative risk assessment and postoperative management. Further research is warranted to elucidate the underlying pathophysiological mechanisms and explore strategies for renal protection in this vulnerable patient population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the hospital IRB.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePatient\u0026rsquo; consent for participation \u0026ndash; not relevant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of supporting data:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupporting data are available upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.K and U.P wrote wrote the manuscript. U.P and A.M concepted the idea.D.M A.S and E.K performed all the procedures. A.L is the cardiologist. all three edited the manuscript.R.K.L is the primary intensive care physician treating these patients in the postoperative course.Y.L and S.W edited the text and performed data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDavies RR, Pizarro C. Decision-Making for Surgery in the Management of Patients with Univentricular Heart. Front Pediatr. 2015 Jul 27;3:61. doi: 10.3389/fped.2015.00061. PMID: 26284226; PMCID: PMC4515559.\u003c/li\u003e\n\u003cli\u003eTalha Niaz, Elizabeth H. Stephens, MD, Stephen J. Gleich, Joseph A. Dearani, Jonathan N. Johnson,David J. Sas. Acute Kidney Injury and Renal Replacement Therapy After Fontan Operation. https://doi.org/10.1016/j.amjcard.2021.08.056\u003c/li\u003e\n\u003cli\u003ePatterson T, Hehir DA, Buelow M, Simpson PM, Mitchell ME, Zhang L, Eslami M, Murkowski K, Scott JP. Hemodynamic profile of acute kidney injury following the Fontan procedure: impact of renal perfusion pressure. World J Pediatr Congenit Heart Surg 2017;8:367\u0026ndash;375.\u003c/li\u003e\n\u003cli\u003eEsch JJ, Salvin JM, Thiagarajan RR, Del Nido PJ, Rajagopal SK. Acute kidney injury after Fontan completion: risk factors and out- comes. J Thorac Cardiovasc Surg 2015;150:190\u0026ndash;197. \u003c/li\u003e\n\u003cli\u003eZafar F, Lubert AM, Katz DA, Hill GD, Opotowsky AR, Alten JA, Goldstein SL, Alsaied T. Long-Term Kidney Function After the Fontan Operation: JACC Review Topic of the Week. J Am Coll Cardiol. 2020 Jul 21;76(3):334-341. doi: 10.1016/j.jacc.2020.05.042. PMID: 32674796.\u003c/li\u003e\n\u003cli\u003eBlinder JJ, Goldstein SL, Lee VV, Baycroft A, Fraser CD, Nelson D, et al. Congenital heart surgery in infants: effects of acute kidney injury on outcomes. J Thorac Cardiovasc Surg. 2012;143:368-74.\u003c/li\u003e\n\u003cli\u003eBai L, Jin Y, Zhang P, Li Y, Gao P, Wang W, Wang X, Feng Z, Zhao J, Liu J. Risk factors and outcomes associated with acute kidney injury following extracardiac total cavopulmonary connection: a retrospective observational study. Transl Pediatr. 2022 Jun;11(6):848-858. doi: 10.21037/tp-21-474. PMID: 35800273; PMCID: PMC9253948.\u003c/li\u003e\n\u003cli\u003eAlgaze CA, Koth AM, Faberowski LW, Hanley FL, Krawczeski CD, Axelrod DM. Acute Kidney Injury in Patients Undergoing the Extracardiac Fontan Operation With and Without the Use of Cardiopulmonary Bypass. Pediatr Crit Care Med. 2017 Jan;18(1):34-43. doi: 10.1097/PCC.0000000000000984. PMID: 27792123.\u003c/li\u003e\n\u003cli\u003eLi S, Krawczeski CD, Zappitelli M, Devarajan P, Thiessen-Philbrook H, Coca SG, et al. Incidence, risk factors, and outcomes of acute kidney injury after pediatric cardiac surgery: a prospective multicenter study. Crit Care Med. 2011; 39:1493-9.\u003c/li\u003e\n\u003cli\u003eClaudia A. Algaze, Andrew M. Koth, Lisa W. Faberowski, Frank L. Hanley, Catherine D. Krawczeski, David M. Axelrod. Acute Kidney Injury in Patients Undergoing the Extracardiac Fontan Operation With and Without the Use of Cardiopulmonary Bypass. DOI:10.1097/PCC.0000000000000984.\u003c/li\u003e\n\u003cli\u003eTaylor ML, Carmona F, Thiagarajan RR, Westgate L, Ferguson MA, Del Nido PJ, et al. Mild postoperative acute kidney injury and outcomes after surgery for congenital heart disease. J Thorac Cardiovasc Surg. 2013;146:146-52.\u003c/li\u003e\n\u003cli\u003eAydin SI, Seiden HS, Blaufox AD, Parnell VA, Choudhury T, Punnoose A, Schneider J. Acute kidney injury after surgery for congenital heart disease. Ann Thorac Surg 2012;94:1589\u0026ndash;1595.\u003c/li\u003e\n\u003cli\u003eRicci Z, Di Nardo M, Iacoella C, Netto R, Picca S, Cogo P. Pediatric RIFLE for acute kidney injury diagnosis and prognosis for children undergoing cardiac surgery: a single-center prospective observational study. Pediatr Cardiol 2013;34:1404\u0026ndash;1408.\u003c/li\u003e\n\u003cli\u003eBellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P. Acute renal failure -definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care 2004; 8: R204-12\u003c/li\u003e\n\u003cli\u003eBastin AJ, Ostermann M, Slack AJ, Diller GP, Finney SJ, Evans TW. Acute kidney injury after cardiac surgery according to Risk/ Injury/Failure/Loss/End-stage, acute kidney injury network, and kidney disease: Improving global outcomes classifications. J Crit Care. 2013;28(4): 389-396\u003c/li\u003e\n\u003cli\u003eZappitelli M, Bernier P, Saczkowski RS, et al. A small post- operative rise in serum creatinine predicts acute kidney injury in children undergoing cardiac surgery. Kidney Int. 2009;76(8): 885-892. doi:10.1038/ki.2009.270.Epub 2009 Jul 29.\u003c/li\u003e\n\u003cli\u003eCetta F, Feldt RH, O\u0026rsquo;Leary PW, Mair DD, Warnes CA, Driscoll DJ, Hagler DJ, Porter CJ, Offord KP, Schaff HV, Puga FJ, Danielson GK. Improved early morbidity and mortality after Fontan operation: the Mayo Clinic experience, 1987 to 1992. J Am Coll Cardiol 1996;28:480\u0026ndash;486.\u003c/li\u003e\n\u003cli\u003ePundi KN, Johnson JN, Dearani JA, Pundi KN, Li Z, Hinck CA, Dahl SH, Cannon BC, O\u0026apos;Leary PW, Driscoll DJ, Cetta F. 40-year follow-up After the Fontan operation: long-term outcomes of 1,052 patients. J Am Coll Cardiol 2015;66:1700\u0026ndash;1710.\u003c/li\u003e\n\u003cli\u003eCooper DS, Claes D, Goldstein SL, Bennett MR, Ma Q, Devarajan P, Krawczeski CD. Follow-Up Renal Assessment of Injury Long-Term After Acute Kidney Injury (FRAIL-AKI). Clin J Am Soc Nephrol. 2016 Jan 7;11(1):21-9. doi: 10.2215/CJN.04240415. Epub 2015 Nov 17. PMID: 26576618; PMCID: PMC4702230.\u003c/li\u003e\n\u003cli\u003eMadsen NL, Goldstein SL, Fr\u0026oslash;slev T, Christiansen CF, Olsen M. Cardiac surgery in patients with congenital heart disease is associated with acute kidney injury and the risk of chronic kidney disease. Kidney Int. 2017 Sep;92(3):751-756. doi: 10.1016/j.kint.2017.02.021. Epub 2017 Apr 12. PMID: 28412020.\u003c/li\u003e\n\u003cli\u003eLex DJ, T\u0026oacute;th R, Czobor NR, Alexander SI, Breuer T, S\u0026aacute;pi E, Szatm\u0026aacute;ri A, Sz\u0026eacute;kely E, G\u0026aacute;l J, Sz\u0026eacute;kely A. Fluid Overload Is Associated With Higher Mortality and Morbidity in Pediatric Patients Undergoing Cardiac Surgery. Pediatr Crit Care Med. 2016 Apr;17(4):307-14. doi: 10.1097/PCC.0000000000000659. PMID: 26914622.\u003c/li\u003e\n\u003cli\u003eDupont M, Mullens W, Finucan M, Taylor DO, Starling RC, Tang WH. Determinants of dynamic changes in serum creatinine in acute decompensated heart failure: the importance of blood pressure reduction during treatment. Eur J Heart Fail. 2013;15:433-40.\u003c/li\u003e\n\u003cli\u003eKwiatkowski DM, Goldstein SL, Krawczeski CD. \u0026quot;Biomarkers of acute kidney injury in pediatric cardiac patients.\u0026quot; Biomarkers in Medicine. 2017;11(11):1051-1063. DOI: 10.2217/bmm-2016-0175\u003c/li\u003e\n\u003cli\u003eHix JK, Thakar CV, Katz EM, Yared JP, Sabik J, Paganini EP. Effect of off-pump coronary artery bypass graft surgery on postoperative acute kidney injury and mortality. Crit Care Med 2006; 34: 2979-83.\u003c/li\u003e\n\u003cli\u003eWijeysundera DN, Beattie WS, Djaiani G, Rao V, Borger MA, Karkouti K, et al. Off-pump coronary artery surgery for reducing mortality and morbidity: meta-analysis of randomized and observational studies. J Am Coll Cardiol 2005; 46: 872-82.\u003c/li\u003e\n\u003cli\u003eProwle JR, Bellomo R. Sepsis-associated acute kidney injury: macrohemodynamic and microhemodynamic alterations in the renal circulation. Semin Nephrol 2015; 35: 64-74\u003c/li\u003e\n\u003cli\u003eSidharth K. Sethi, Timothy Bunchman, Ronith Chakraborty, Rupesh Raina. Pediatric acute kidney injury: new advances in the last decade. Kidney Res Clin Pract 2021;40(1).\u003c/li\u003e\n\u003cli\u003eKato, M., Natarajan, R. Epigenetics and epigenomics in diabetic kidney disease and metabolic memory. Nat Rev Nephrol 15, 327\u0026ndash;345 (2019). https://doi.org/10.1038/s41581-019-0135-6.\u003c/li\u003e\n\u003cli\u003eMusiał, K. Current Concepts of Pediatric Acute Kidney Injury\u0026mdash;Are We Ready to Translate Them into Everyday Practice. J. Clin. Med. 2021, 10, 3113. https://doi.org/10.3390/jcm10143113\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Patient characteristics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"443\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient characteristics at Fontan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003cp\u003e(n=98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eAge, months, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e64.27 (34.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eMales, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e59, (60.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eWeight (kg)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e17.33 (7.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eNon-cardiac malformations, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e24 (24.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eLeft ventricular dominance, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e55 (56.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eRight ventricular dominance, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e43 (43.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eCPB time, minutes, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e72.40 (33.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eCross-clamp time, minutes, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e7.28 (24.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eGoretex size, mm, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e19.38 (1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003ePostoperative ECMO, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e2 (2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003eMortality, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e5 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 1. The baseline and surgical characteristics and postoperative outcome of all the patients who underwent Fontan procedure.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: CPB=cardiopulmonary bypass; ECMO\u003c/em\u003e=\u003cem\u003eextracorporeal membrane oxygenation; PRBC=packed red blood cell.\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eIncidence of postoperative acute kidney injury\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003ePost Glenn (Stage 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003ePost Fontan (Stage 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eKDIGO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eStage 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e13 (17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e38 (38.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eStage 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e3 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e22 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eStage 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e13 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003epRIFLE\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eRisk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e29 (39.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e47 (48.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eInjury\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e4 (5.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e22 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eFailure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e12 (12.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eLoss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eEnd-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2. This table presents the distribution of AKI severity by stage following the Glenn (Stage 2) and Fontan (Stage 3) procedures, classified by KDIGO and pRIFLE criteria. A notable increase in moderate-to-severe AKI is observed post-Fontan, with KDIGO Stage 2\u0026ndash;3 rising from 5.2% to 35.7% and pRIFLE Injury/Failure increasing from 5.5% to 34.6%. These shifts suggest a clear worsening of renal function following Fontan completion.\u003cspan dir=\"RTL\"\u003e\u003cbr\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eStatistical Analysis of the Association Between Post-Glenn and Post-Fontan AKI\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"658\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistical Test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClassification System\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKDIGO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eFisher\u0026apos;s Exact Test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e[1,2,3] post-Glenn to [1,2,3] post-Fontan vs [0] post-Glenn to [1,2,3] post-Fontan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eOR = 14.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eHighly significant association\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eFisher\u0026apos;s Exact Test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e[2,3] post-Glenn to [2,3] post-Fontan vs [0,1] post-Glenn to [2,3] post-Fontan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eOR = 9.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eHighly significant association\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eChi-Square Test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2; = 3.644, df = 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eNot significant, likely due to small subgroup sizes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003ePearson\u0026apos;s Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003er = 0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eVery weak correlation, not significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epRIFLE\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eFisher\u0026apos;s Exact Test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e[R,I,F] post-Glenn to [R,I,F] post-Fontan vs [None] post-Glenn to [R,I,F] post-Fontan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eOR = 8.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eHighly significant association\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eFisher\u0026apos;s Exact Test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e[I,F] post-Glenn to [I,F] post-Fontan vs [None,R] post-Glenn to [I,F] post-Fontan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eOR = 8.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eHighly significant association\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eChi-Square Test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2; = 8.167, df = 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eNot significant, but shows clinical trend\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eSpearman\u0026apos;s Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026rho; = 0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eVery weak correlation, not significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003ePearson\u0026apos;s Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003er = 0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eVery weak correlation, not significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3. This table highlights a key methodological insight: although Pearson\u0026apos;s and Spearman\u0026apos;s correlation tests showed very weak and non-significant associations between AKI severity post-Glenn and post-Fontan, these results are limited by statistical constraints. Correlation analyses are less effective for ordinal data with few categories, small sample sizes, and non-linear trends. Additionally, a ceiling effect\u0026mdash;due to a high rate of post-Fontan AKI even in patients without prior AKI\u0026mdash;likely suppressed correlation values. Despite this, Fisher\u0026rsquo;s Exact Tests revealed a strong and highly significant association, underscoring the predictive value of early AKI.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eTransition Probabilities Between AKI States from Glenn to Fontan Procedures\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"638\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003eInitial State (Post-Glenn)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003eTransition to Post-Fontan AKI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003eProbability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003eKDIGO [0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003eKDIGO [1,2,3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003eKDIGO [1,2,3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003eKDIGO [1,2,3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003epRIFLE [R,I,F]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003epRIFLE [R,I,F]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003epRIFLE [I,F]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003epRIFLE [I,F]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 213px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4. This table summarizes the observed probabilities of AKI progression from post-Glenn to post-Fontan using both the KDIGO and pRIFLE classification systems. Patients with no initial AKI (KDIGO [0]) had an 80.7% chance of developing some degree of AKI post-Fontan, while those with pre-existing AKI (KDIGO [1,2,3]) had an even higher progression rate of 87.5%. Similarly, using the pRIFLE system, patients with any AKI post-Glenn (R/I/F) showed an 80% chance of maintaining or worsening their renal status post-Fontan. A more refined pRIFLE subset (I/F) indicated a 65% progression rate. These findings support a high likelihood of AKI persistence or deterioration, particularly in patients with pre-existing renal injury before Fontan completion.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acute Kidney Injury, Congenital Heart Disease, Single Ventricle, Glenn, Fontan","lastPublishedDoi":"10.21203/rs.3.rs-6632404/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6632404/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAcute kidney injury (AKI) is a common and serious complication following Fontan completion in children with single ventricle physiology. While risk factors for post-Fontan AKI are well studied, it remains unknown whether prior AKI after the Glenn procedure can predict subsequent renal injury, potentially informing risk stratification and management.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study included 98 pediatric patients who underwent Fontan surgery between 2009 and 2016. AKI after both Glenn and Fontan procedures was assessed using KDIGO and pRIFLE classification systems. Statistical analyses included odds ratios, cross-tabulations, and correlation tests to evaluate the relationship between post-Glenn and post-Fontan AKI.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong patients who developed AKI after Glenn, 87.5% (KDIGO) and 80% (pRIFLE) experienced AKI again after Fontan. Patients with Glenn-related AKI were over 14 times more likely to develop post-Fontan AKI (OR\u0026thinsp;=\u0026thinsp;14.36, p\u0026thinsp;=\u0026thinsp;0.001). Notably, 100% of patients with severe (\u0026ldquo;failure\u0026rdquo; category) Glenn AKI developed Fontan AKI, and 75% remained in the severe category. Despite weak correlation coefficients, categorical analysis highlighted a clinically significant predictive relationship. Only 2% required ECMO post-Fontan, and overall mortality was 5.1%.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAKI following the Glenn procedure is a strong predictor of subsequent AKI after Fontan completion. This finding suggests a possible continuum of renal vulnerability across staged palliation, supporting the concept of \"renal memory.\" Integrating prior renal response into pre-Fontan risk assessment could enable early intervention and tailored perioperative strategies.\u003c/p\u003e","manuscriptTitle":"Renal memory in the Glenn-Fontan acute kidney injury continuum: A window for early renal protection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-16 12:58:06","doi":"10.21203/rs.3.rs-6632404/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ded6f2c1-be99-4aea-bb41-67e6a7d501d7","owner":[],"postedDate":"May 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-21T18:38:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-16 12:58:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6632404","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6632404","identity":"rs-6632404","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}