What is the Cumulative Impact of Race & Social Determinants of Health on Minorities’ Single Ventricle Journey Beyond the First Year

What is the Cumulative Impact of Race & Social Determinants of Health on Minorities’ Single Ventricle Journey Beyond the First Year | 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 What is the Cumulative Impact of Race & Social Determinants of Health on Minorities’ Single Ventricle Journey Beyond the First Year Amir Mehdizadeh-Shrifi, Grant Chappell, Muhammad Faateh, Nadine Kasparian, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6591389/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 Race and social determinants of health are known to impact stage-I-palliation (S1P) outcomes. Resources are predominantly focused during their first year of life which may reduce the impact of socioeconomic status (SES) and race. We sought to investigate their impact on long-term outcomes in patients who survived at least one year. Methods The Pediatric-Health-Information-System database was used to identify patients born with Hypoplastic Left Heart Syndrome (HLHS) who underwent S1P and survived to age one. Outcomes and resource utilization were compared by stratifying patients based on SES and race. Results A total of 5,968 children who underwent S1P and survived one year were included. Amongst these, 3,932(66%) were Non-Hispanic White (NHW), 924(15%) were Non-Hispanic Black (NHB) and 569(9%) were Hispanic-Latino (HL). Adjusted one-year conditional mortality demonstrated significantly increased mortality in low-income (LI) Black children (Year 3 LI-Black:7% vs. HI-White:3%, p < 0.001). The difference in mortality ratio was almost double compared to the total unadjusted cohort in year one. In a multivariate analysis for one-year conditional survival at year three, Black children below the poverty line (HR:6.65 [2.06–8.56]p < 0.001) was the strongest predictor of mortality and the HR was lower in unadjusted patients at year one (HR:3.74 [1.89–5.52]p < 0.001). Conclusions Mortality is significantly increased in low-income Black children, and the negative effect of SES is greater after one year. Disparities in HLHS care and social determinants of health become amplified for Black children from low-income families after the first year suggesting that there are opportunities to review resource allocation of vulnerable children. Burden Socioeconomic status disparities resource utilization Figures Figure 1 Introduction While major advances have occurred over the last decade in the diagnosis and management of children undergoing single-ventricle palliation with hypoplastic left heart syndrome (HLHS), mortality within the first year remains a major cause of concern for surgeons. However, additional interactions among socioeconomic status (SES), race, and access to care continue to modify congenital heart disease (CHD) outcomes. 1 A recent analysis by Karamlou et al. outlined how hospitals serving more vulnerable patient populations developed care pathways aimed explicitly at bolstering minority families. 1 Nevertheless, adverse outcomes among disadvantaged patient populations, inclusive of minority and low-income households, are still significantly magnified in complex CHDs, suggesting that further efforts in targeted resource allocation and population health initiatives are required. 1 , 2 Most resources and initiatives focus on the first year after stage-I-palliation (S1P), emphasizing the interstage period and despite this, the effect of race and SES is still significant. However, past the first year, when the program’s resource allocation and focus on S1P patients generally wanes, could the impact of race and SES potentially be greater on outcomes? We hypothesize that the discrepancies in one-year resource utilization and outcomes that exist in palliated minority and low SES children are significantly amplified after the first year. Material and Methods Patient and Data Acquisition The Pediatric Health Information System (PHIS) is an administrative database that contains inpatient, emergency department, ambulatory surgery, and observation unit data from 49 not-for-profit, tertiary-care pediatric hospitals in the United States and Canada. These hospitals are affiliated with the Child Health Corporation of America (Shawnee Mission, Kansas), a business alliance of children's hospitals. Data quality and reliability are assured through a joint effort between the Child Health Corporation of America and participating hospitals. For external benchmarking, participating hospitals provide discharge/encounter data, including demographics, diagnoses, and procedures. The majority of these hospitals also submit resource use data (e.g., pharmaceuticals, imaging, laboratory, supply, and physician-related information, etc.) to PHIS. Data are de-identified at the time of submission and are subjected to a number of reliability and validity checks before being included in the database. Names of participating hospitals are included in both ID formats and are specifically deidentified. Study groups, covariates, and outcomes The study groups included one-year conditional survivors stratified by race and ethnicity. All patients survived and had at least one year of follow-up after S1P. Patients without PHIS birth admission were excluded. The three groups comprised Non-Hispanic White, Non-Hispanic Black, and Hispanic-Latino children. Asians, Pacific Islanders, and Native American children could not be accurately assessed in the dataset due to missing data and low sample size. Pre-operative demographic characteristics were evaluated. The primary outcomes were postoperative clinical and resource utilization. Secondary outcomes included cumulative mortality stratified by composition of race and socio-economic status. Low income was defined as median household income below the 25th percentile and high income as > 75th percentile. United States census information was used to determine the national poverty level, and the consumer price index provided by the Census Bureau was utilized to adjust costs and income by inflation. Center volume was defined as the quartiles derived from the total number of S1P surgeries performed at a hospital divided by the years in the database. Ethical Considerations Our institutional review board (IRB) approved the study and deemed it a non-human subject study. A waiver of consent was granted (IRB #2022 − 0515). Statistical analysis Pre-operative baseline characteristics and outcomes were compared among three groups stratified by race and ethnicity. Chi-square or Fisher’s exact test was used to compare categorical variables, and student t-test or Wilcoxon rank-sum tests were used for continuous variables. A multivariable Cox Hazard regression model was used to assess predictive factors of mortality. Predictors of mortality were evaluated for year one of life in the total unadjusted cohort. Additionally, mortality predictors were analyzed at year three in one-year conditional survivors. Model validation occurred using a concordance index for both unadjusted total and adjusted one-year conditional cohort. Cumulative mortality was analyzed using Kaplan-Meier models and log-rank for pairwise group comparison. Mortality was assessed for unadjusted survivors and one-year conditional survivors. Statistical analyses were performed using SPSS (IBM Corp. Released 2020. IMB SPSS Statistics, Version 27.0. Armonk, NY: IMB Corp) and SAS version 9.4 (Cary, North Carolina, USA). Results Demographic and clinical characteristics of one-year conditional survivor A total of 5,968 children who underwent stage I palliation and survived at least one year were included. Amongst these, 3,932 (66%) were Non-Hispanic White (NHW), 924 (15%) were Non-Hispanic Black (NHB), and 569 (9%) were Hispanic-Latino (HL) (Table 1). There was no difference in age at surgery during S1P. Almost half of all NHB patients were female (NHB: 46% vs. HL: 40% vs. NHW: 37%, p<0.001). Three-quarters of all NHB and HL children were on government-sponsored insurance (NHB: 77% vs. HL: 75% vs. NHW: 40%, p<0.001), whereas most NHW one-year survivors were on private payor modalities. Furthermore, NHB and HL children had significantly reduced median household income ($1000’s USD) (NHB: 45 vs. HL: 48 vs. NHW: 54, p<0.001), and almost one-third of NHB families were below the 25 th percentile median household income (NHB: 32% vs. HL: 26% vs. NHW: 18%, p<0.001) and NHB children were two-fold more likely to be below the United States federal poverty line (NHB: 7% vs. HL: 4% vs. NHW: 3%, p<0.001). Moreover, NHB and HL children were more likely to be treated at low-volume centers (NHB: 17% vs. HL: 18% vs. NHW: 13%, p<0.001) than their White counterparts. Almost one-fourth of NHB were born prematurely (NHB: 23% vs. HL: 20% vs. NHW: 19%, p<0.001) and with low birth weight (NHB: 17% vs. HL: 10% vs. NHW: 10%, p<0.001) (Table 1). Post S1P outcomes and resource utilization of one-year conditional survivors Post-Norwood clinical outcomes revealed two-fold higher rates of tracheostomy in NHB children (NHB: 6% vs. HL: 2% vs. NHW: 1%, p<0.001), higher rates of delayed sternal closure (NHB: 11% vs. HL: 10% vs. NHW: 7%, p<0.001) and prolonged mechanical ventilation (NHB: 12% vs. HL: 11% vs. NHW: 8%, p<0.001) (Table 2). Furthermore, the authors investigated resource utilization in one-year survivors, including hospital visits, hospitalization time, procedures, diagnostics, medication, and healthcare expenditure. Analysis of hospitalization resources demonstrated significantly increased length of stay in the S1P index admission in NHB children (NHB: 61 days [33-101] vs. HL: 53 [31-89] vs. NHW: 41 [27-71] p<0.001). Furthermore, NHB and HL children had significantly increased 30-day inpatient hospital readmission (NHB: 12% vs. HL: 11% vs. NHW: 8%, p<0.001) as compared to NHW, with respectively increased readmission hospitalization length (days) (NHB: 17 [11-31] vs. HL: 12 [7-17] vs. NHW: 9 [4-21] p<0.001) as well as higher number of emergency department visits 6 months after S1P (NHB: 9 [6-21] vs. HL: 7 [4-14] vs. NHW: 6 [3-10], p<0.001). Contrasting, the number of post-S1P clinic visits was significantly lower in NHB one-year survivors (NHB: 6 [2-9] vs. HL: 9 [4014] vs. NHW: 11 [4-19] p<0.001). Additionally, NHB were more likely to be in the lower 25 th percentile of days alive and outside the hospital after S1P than White children (NHB: 18% vs. HL: 16% vs. NHW: 10%, p<0.001). The procedural resource utilization of one-year conditional survivors did not reveal any differences in the utilization of cardiac catheterizations and non-cardiac procedures. Further assessment of diagnostic studies showed significantly reduced use of cardiac echocardiography in NHB children (NHB: 6 [3-11] vs. HL: 7 [4-13] vs. NHW: 10 [4-15], p<0.001), and non-cardiac imaging (NHB: 52 [27-86] vs. HL: 57 [42-79] vs. NHW: 68 [39-115], p<0.001). There was no difference in the total medication numbers of the inpatients. However, adjusted costs of hospitalization were significantly higher in NHB and HL children (NHB: 912,411 [551,051-1,516,491] vs. HL: 722,588 [445,611-1,169,582] vs. NHW: 535,917 [307613-790,192], p<0.001). Unadjusted and one-year conditional Kaplan-Meier survival analysis Unadjusted cumulative mortality stratified by combined race and income of all HLHS children who underwent S1P showed the lowest mortality in high-income (HI) White children. Highest cumulative mortality was observed in low-income (LI) Back children (Year 1 LI-Black: 20% vs HI-White: 12%, p<0.001). The mortality ratio at year one between low-income Black and high-income White children was 1.6 at year one and 1.8 at year five (Figure 1A). Adjusted one-year conditional survival continued to demonstrate significantly increased and 2.5 higher mortality in low-income Black children (Year 5 LI-Black: 10% vs. HI-White: 4%, p<0.001), whereas mortality in other race and socio-economic groups did not yield differences when selecting for one-year survivors (Figure 1B). Furthermore, the mortality ratio of one-year conditional survivors at year three was 2.3 and 2.5 at year five in low-income Black children, thus, revealing a significant step wise increase compared to the total unadjusted cohort of high-income White children at one year. Multivariate Cox proportional hazard regression of mortality in one-year conditional survivors In- total, 21 univariate predictors of mortality at year one for unadjusted patients and 18 univariate predictors of mortality at year three for adjusted one-year survivors were assessed (Table 3-4). In unadjusted patients, nine clinical and social co-variates increased mortality in year one. The highest predictor of mortality was tracheostomy (HR: 5.63 [3.45 – 8.07], p 0.002), followed by treatment at low volume centers (HR: 4.90 [3.20 – 6.44], p<0.001), being Black and below the federal poverty line (HR: 3.74 [1.89-5.52], p<0.001) and being Black and from a low-income family (HR:1.99 [1.33-3.34], p<0.001) (Table 3). In adjusted one-year survivors, seven clinical and social co-variates increased mortality in year three (Table 4). The strongest predictor of mortality was being Black and below the federal poverty line (HR: 6.65 [2.06-8.56], p<0.001), followed by tracheostomy (HR: 4.82 [2.93 – 7.91], p 0.002), being Black and from a low-income household (HR: 3.30 [2.33-5.34] p 0.001). White children, regardless of income status, remained unaffected in the adjusted one-year conditional prediction model. In contrast, the Hazard Ratios of Black children from low-income households (HR Adjusted Year 3: 3.3 vs. Unadjusted Year 1: 1.99) and below the federal poverty line (HR Adjusted Year 3: 6.65 vs. Unadjusted Year 1: 3.74) at year three increased almost two-fold as compared to unadjusted palliated Black children at year one. Region and insurance status were not predictors of mortality in adjusted one-year conditional survivors (Table 4). Discussion The present report demonstrated that social determinants of health, such as government-sponsored insurance, lower household income, and disproportionate treatment at low-volume centers, remained risk factors in one-year conditional HLHS survivors. Non-Hispanic Black and Hispanic-Latino children received less outpatient care and cardiac and non-cardiac imaging. In contrast, inpatient readmission, length of stay, and emergency department visits were significantly increased in NHB one-year survivors. In this large multicenter cohort, we also found that the combination of race and social determinants of health had a significantly negative effect on mortality and was substantially amplified in low-income Black children after the first year of life, as demonstrated by a stepwise increase in cumulative mortality ratios and rising Hazard Ratios in vulnerable children. Despite the overall improvement in the life expectancy of CHD patients, disparities in morbidity and mortality, as well as resource utilization, exist. Numerous predictors affecting mortality and disparate resource use have been analyzed, with a broad consensus that critical examination of multilevel contributions that facilitate health inequities is required. 3 – 5 Regarding the importance of the multi-level approach, Lopez et al. analyzed various factors that specifically influence HLHS. 5 They confirmed the impact of factors such as social determinants of health, hospital distance, language proficiency, racial bias, and the intersection between institutional regionalization of care and geography on outcomes. Furthermore, a closer look revealed that Black race and low surgical volume remain predictors of mortality throughout the eras. 1 , 4 , 6 While the vast body of literature has identified the stark reality of racial inequities in HLHS, the present study aims to shift focus from traditional HLHS assessment and extend the perspective to the progress of HLHS survivors beyond the first year. An important finding of the present study is that the differences mentioned above do not cease to exist even in “successful” one-year conditional survivors but seem to increase in Black and Hispanic-Latino communities as well as low-income families. This study emphasizes the concerning distribution of lower outpatient clinic visits, cardiac and non-cardiac imaging, that potentially contributed to increased readmission rates, and substantially increased costs in Black and Hispanic-Latino children. Similar findings have been confirmed in other patient populations, inclusive of specialized transplant and general pediatric care in which Black and Hispanic-Latino children had significantly fewer clinic visits, reduced access to care, and general follow-up in the outpatient setting. 7 The authors believe that these effects linger in children of minority communities that would have been otherwise deemed as successfully palliated. The authors have recently demonstrated the immense burden and resource utilization that are invested in the first year of life for HLHS children. 8 Another important finding of this study is that SES and race significantly impact mortality beyond the first year. Cumulative mortality in low-income Black children was more than two-fold higher in one-year conditional survivors at three years and at five years of age compared to Non-Hispanic White children from high-income backgrounds. It was noteworthy that the cumulative effect of SES and race most significantly affected Non-Hispanic Black children. However, an improvement in SES (i.e., high income) did not significantly increase Non-Hispanic Black nor Hispanic children’s survival, nor did a decrease in SES (i.e., low income) significantly decrease Non-Hispanic White children’s survival. Lopez et al. report that the interplay of race, and SES was critical in examining the effects of the intersection. It revealed that especially complex CHDs are not immune to disparities. 5 While mortality in HLHS has declined overall, racial and ethnic disparities in mortality have remained the same in the current era. 5 , 9 Yet, qualitative and community-based participatory research heavily emphasized the first year of life. Single ventricle programs focus many resources (e.g., special clinics, home monitoring, frequent calls, etc.) during the first year of life, especially during the interstage period (e.g., the practice of keeping S1P patients in hospital until S2P), and despite this, SES and race still have a significant effect. This intense focus decreases at most programs significantly after the first year, and therefore, one would expect, as this analysis demonstrated, that the negative effects of SES and race would be amplified. Perhaps this is even more evident in low-volume programs with fewer resources, which may explain the Hazard ratio of 3.49. There are limitations to this study. The exact indications and rationale for center-specific resource allocation could not be assessed. PHIS contains a sample of pediatric hospitals in the US, so it may not be generalizable to all congenital centers. The burden reported herein is minimally accumulated due to the potential for missing certain outpatient visits, such as telehealth appointments. We were unable to assess specific vulnerable communities such as Native Americans and Pacific Islanders or patients categorized as others due to missing information. Moreover, this study was not designed to determine a myriad of surgeon and provider-specific aspects, such as physician ratios, implicit and explicit biases, and geographic and regional disparities. Therefore, the true extent of long-term disparate access to care and problems in resource allocation may be even more pronounced. In conclusion, this analysis reveals that the effect of social determinants of health and race, after the intense focus on first year post-S1P care begins to wane, seems to amplify and is most pronounced in the most vulnerable populations (e.g., Black children from low-income families). As mortality in minority children is increased and resource use is substantially lower, this report may open avenues to rethink resource allocation in HLHS care and equitable distribution that supports these vulnerable communities when the effects of social determinants of health become more prominent. Further policy review assessing HLHS health equity, including examination at the individual, systemic, and population levels, seems warranted. Abbreviations SES: Socioeconomic Status S1P: Stage-I-Palliation HLHS: Hypoplastic Left Heart Syndrome PHIS: Pediatric Health Information System ICD: International Classification of Disease NHW: Non-Hispanic White NHB: Non-Hispanic Black HL: Hispanic-Latino LI: Low Income HI: High Income CHD: Congenital Heart Disease HR: Hazard Ratio Declarations Competing Interests David L. S. Morales reports a relationship with Abbott Vascular, Aziyo, Xeltis BV, Berlin Heart, SynCardia Systems (consulting or advisory). that includes: consulting or advisory. Awais Ashfaq reports a relationship with Pyrames that includes: non-financial support. If Author Contribution A. M. S. wrote the main manuscript text, performed the analysis, and prepared tables and figuresG. C. assisted in the analysis and reviewed the manuscript and contributed to revisionsM. F. prepared tables and figures and reviewed the manuscript and contributed to revisionsN. K. reviewed the manuscript and contributed to revisionsA. A. reviewed the manuscript and contributed to revisionsD. L. reviewed the manuscript and contributed to revisionsH. H. reviewed the manuscript and contributed to revisionsM. R. reviewed the manuscript and contributed to revisionsD. L. S. M. wrote the manuscript text, reviewed methodology, reviewed the manuscript and contributed to revisions Acknowledgements: None Additional Funding : None References Karamlou T, Hawke JL, Zafar F et al (2022) Widening our focus: characterizing socioeconomic and racial disparities in congenital heart disease. Ann Thorac Surg 113(1):157–165 Krishnan A, Jacobs MB, Morris SA et al (2021) Impact of socioeconomic status, race and ethnicity, and geography on prenatal detection of hypoplastic left heart syndrome and transposition of the great arteries. Circulation 143(21):2049–2060 Ross FJ, Latham G, Tjoeng L, Everhart K, Jimenez N (2023) Racial and ethnic disparities in US children undergoing surgery for congenital heart disease: A narrative literature review. SAGE Publications Sage CA, Los Angeles, CA, pp 224–234 Schidlow DN, Gauvreau K, Bucholz EM et al (2023) Prenatal care coordination, racial and socioeconomic inequities, and pre-and post-operative outcomes in hypoplastic left heart syndrome. J Perinatol 43(3):378–384 Lopez KN, Baker-Smith C, Flores G et al (2022) Addressing social determinants of health and mitigating health disparities across the lifespan in congenital heart disease: a scientific statement from the American Heart Association. J Am Heart Association 11(8):e025358 Dean PN, McHugh KE, Conaway MR, Hillman DG, Gutgesell HP (2013) Effects of race, ethnicity, and gender on surgical mortality in hypoplastic left heart syndrome. Pediatr Cardiol 34:1829–1836 Sborov KD, Haruno LS, Raszka S, Poon SC (2023) Racial and Ethnic Disparities in Pediatric Musculoskeletal Care. Curr Rev Musculoskelet Med 16(10):488–492 Amir Mehdizadeh-Shrifi MF, Kevin Kulshrestha H, Heydarian R, Hirsch M, Hossain S, Hogue A, Ashfaq D, Morales (2023) Sr. Unveiling the Complete Medical Burden of Hypoplastic Left Heart Syndrome: 18 Years of Insight from Childhood to Adolescence. 10/31/2024, https://www.aats.org/resources/unveiling-the-complete-medical-7727 Lopez KN, Morris SA, Sexson Tejtel SK, Espaillat A, Salemi JL (2020) US mortality attributable to congenital heart disease across the lifespan from 1999 through 2017 exposes persistent racial/ethnic disparities. Circulation 142(12):1132–1147 Tables Table 1 to 4 are available in the Supplementary Files section. Additional Declarations Competing interest reported. David L. S. Morales reports a relationship with Abbott Vascular, Aziyo, Xeltis BV, Berlin Heart, SynCardia Systems (consulting or advisory). that includes: consulting or advisory. Awais Ashfaq reports a relationship with Pyrames that includes: non-financial support. If Supplementary Files Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-6591389","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":453959059,"identity":"b95a1448-9458-41e8-a195-28d5f09a8b99","order_by":0,"name":"Amir Mehdizadeh-Shrifi","email":"data:image/png;base64,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","orcid":"","institution":"The Heart Institute, Cincinnati Children’s Hospital Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Amir","middleName":"","lastName":"Mehdizadeh-Shrifi","suffix":""},{"id":453959060,"identity":"3e6f5fed-2024-4351-8fef-cd1ba7d2560d","order_by":1,"name":"Grant Chappell","email":"","orcid":"","institution":"The Heart Institute, Cincinnati Children’s Hospital Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Grant","middleName":"","lastName":"Chappell","suffix":""},{"id":453959061,"identity":"41025122-282a-49e8-b7ff-094d152c19c4","order_by":2,"name":"Muhammad Faateh","email":"","orcid":"","institution":"The Heart Institute, Cincinnati Children’s Hospital Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Faateh","suffix":""},{"id":453959062,"identity":"fca71aa2-61a4-49ae-a451-d58d83e10893","order_by":3,"name":"Nadine Kasparian","email":"","orcid":"","institution":"The Heart Institute, Cincinnati Children’s Hospital Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Nadine","middleName":"","lastName":"Kasparian","suffix":""},{"id":453959063,"identity":"df5a4495-e5db-47a5-8afb-adc5583b608d","order_by":4,"name":"Awais Ashfaq","email":"","orcid":"","institution":"The Heart Institute, Cincinnati Children’s Hospital Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Awais","middleName":"","lastName":"Ashfaq","suffix":""},{"id":453959064,"identity":"d5cbaa8d-b35d-4c24-8009-2a372b49506f","order_by":5,"name":"David Lehenbauer","email":"","orcid":"","institution":"The Heart Institute, Cincinnati Children’s Hospital Medical Center","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Lehenbauer","suffix":""},{"id":453959065,"identity":"54eca4c6-ee0e-4b97-ac61-0e1767a42580","order_by":6,"name":"Haleh Heydarian","email":"","orcid":"","institution":"The Heart Institute, Cincinnati Children’s Hospital Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Haleh","middleName":"","lastName":"Heydarian","suffix":""},{"id":453959066,"identity":"378c094c-3fbb-4f90-b292-dbc868c48ce5","order_by":7,"name":"Marco Ricci","email":"","orcid":"","institution":"The Heart Institute, Cincinnati Children’s Hospital Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Marco","middleName":"","lastName":"Ricci","suffix":""},{"id":453959067,"identity":"56da3f85-f909-4578-a564-2464f7d87745","order_by":8,"name":"David L. S. Morales","email":"","orcid":"","institution":"The Heart Institute, Cincinnati Children’s Hospital Medical Center","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"L. S.","lastName":"Morales","suffix":""}],"badges":[],"createdAt":"2025-05-05 05:38:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6591389/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6591389/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82581039,"identity":"85b08041-a174-4491-9615-209413279bf5","added_by":"auto","created_at":"2025-05-13 06:37:50","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1455515,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e1A: \u003c/strong\u003eCumulative mortality stratified by composition of race and socioeconomic status\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1B: \u003c/strong\u003eCumulative one-year conditional mortality stratified by composition of race and socioeconomic status\u003c/p\u003e","description":"","filename":"Figure1A.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6591389/v1/a2de97dd3c143f1cdba35428.jpg"},{"id":98423037,"identity":"c0038b35-c242-4f13-a278-5f689b00ea22","added_by":"auto","created_at":"2025-12-17 16:31:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1905700,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6591389/v1/5b561b03-e440-4448-a00f-f0f3cf531d71.pdf"},{"id":82581040,"identity":"af0b4e10-74f7-47dc-be08-8b29d9e355e2","added_by":"auto","created_at":"2025-05-13 06:37:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29099,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6591389/v1/14c558b283b5abca85a05594.docx"}],"financialInterests":"Competing interest reported. David L. S. Morales reports a relationship with Abbott Vascular, Aziyo, Xeltis BV, Berlin Heart, SynCardia Systems (consulting or advisory). that includes: consulting or advisory. Awais Ashfaq reports a relationship with Pyrames that includes: non-financial support. If","formattedTitle":"What is the Cumulative Impact of Race \u0026 Social Determinants of Health on Minorities’ Single Ventricle Journey Beyond the First Year","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWhile major advances have occurred over the last decade in the diagnosis and management of children undergoing single-ventricle palliation with hypoplastic left heart syndrome (HLHS), mortality within the first year remains a major cause of concern for surgeons. However, additional interactions among socioeconomic status (SES), race, and access to care continue to modify congenital heart disease (CHD) outcomes. \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e A recent analysis by Karamlou et al. outlined how hospitals serving more vulnerable patient populations developed care pathways aimed explicitly at bolstering minority families. \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Nevertheless, adverse outcomes among disadvantaged patient populations, inclusive of minority and low-income households, are still significantly magnified in complex CHDs, suggesting that further efforts in targeted resource allocation and population health initiatives are required. \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMost resources and initiatives focus on the first year after stage-I-palliation (S1P), emphasizing the interstage period and despite this, the effect of race and SES is still significant. However, past the first year, when the program\u0026rsquo;s resource allocation and focus on S1P patients generally wanes, could the impact of race and SES potentially be greater on outcomes? We hypothesize that the discrepancies in one-year resource utilization and outcomes that exist in palliated minority and low SES children are significantly amplified after the first year.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient and Data Acquisition\u003c/h2\u003e \u003cp\u003eThe Pediatric Health Information System (PHIS) is an administrative database that contains inpatient, emergency department, ambulatory surgery, and observation unit data from 49 not-for-profit, tertiary-care pediatric hospitals in the United States and Canada. These hospitals are affiliated with the Child Health Corporation of America (Shawnee Mission, Kansas), a business alliance of children's hospitals. Data quality and reliability are assured through a joint effort between the Child Health Corporation of America and participating hospitals. For external benchmarking, participating hospitals provide discharge/encounter data, including demographics, diagnoses, and procedures. The majority of these hospitals also submit resource use data (e.g., pharmaceuticals, imaging, laboratory, supply, and physician-related information, etc.) to PHIS. Data are de-identified at the time of submission and are subjected to a number of reliability and validity checks before being included in the database. Names of participating hospitals are included in both ID formats and are specifically deidentified.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy groups, covariates, and outcomes\u003c/h3\u003e\n\u003cp\u003eThe study groups included one-year conditional survivors stratified by race and ethnicity. All patients survived and had at least one year of follow-up after S1P. Patients without PHIS birth admission were excluded. The three groups comprised Non-Hispanic White, Non-Hispanic Black, and Hispanic-Latino children. Asians, Pacific Islanders, and Native American children could not be accurately assessed in the dataset due to missing data and low sample size. Pre-operative demographic characteristics were evaluated. The primary outcomes were postoperative clinical and resource utilization. Secondary outcomes included cumulative mortality stratified by composition of race and socio-economic status. Low income was defined as median household income below the 25th percentile and high income as \u0026gt;\u0026thinsp;75th percentile. United States census information was used to determine the national poverty level, and the consumer price index provided by the Census Bureau was utilized to adjust costs and income by inflation. Center volume was defined as the quartiles derived from the total number of S1P surgeries performed at a hospital divided by the years in the database.\u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eOur institutional review board (IRB) approved the study and deemed it a non-human subject study. A waiver of consent was granted (IRB #2022\u0026thinsp;\u0026minus;\u0026thinsp;0515).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003ePre-operative baseline characteristics and outcomes were compared among three groups stratified by race and ethnicity. Chi-square or Fisher\u0026rsquo;s exact test was used to compare categorical variables, and student t-test or Wilcoxon rank-sum tests were used for continuous variables. A multivariable Cox Hazard regression model was used to assess predictive factors of mortality. Predictors of mortality were evaluated for year one of life in the total unadjusted cohort. Additionally, mortality predictors were analyzed at year three in one-year conditional survivors. Model validation occurred using a concordance index for both unadjusted total and adjusted one-year conditional cohort.\u003c/p\u003e \u003cp\u003eCumulative mortality was analyzed using Kaplan-Meier models and log-rank for pairwise group comparison. Mortality was assessed for unadjusted survivors and one-year conditional survivors. Statistical analyses were performed using SPSS (IBM Corp. Released 2020. IMB SPSS Statistics, Version 27.0. Armonk, NY: IMB Corp) and SAS version 9.4 (Cary, North Carolina, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003e\u003cu\u003eDemographic and clinical characteristics of one-year conditional survivor\u0026nbsp;\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 5,968 children who underwent stage I palliation and survived at least one year were included. Amongst these, 3,932 (66%) were Non-Hispanic White (NHW), 924 (15%) were Non-Hispanic Black (NHB), and 569 (9%) were Hispanic-Latino (HL) (Table 1). There was no difference in age at surgery during S1P. Almost half of all NHB patients were female (NHB: 46% vs. HL: 40% vs. NHW: 37%, p\u0026lt;0.001). Three-quarters of all NHB and HL children were on government-sponsored insurance (NHB: 77% vs. HL: 75% vs. NHW: 40%, p\u0026lt;0.001), whereas most NHW one-year survivors were on private payor modalities. Furthermore, NHB and HL children had significantly reduced median household income ($1000\u0026rsquo;s USD) (NHB: 45 vs. HL: 48 vs. NHW: 54, p\u0026lt;0.001), and almost one-third of NHB families were below the 25\u003csup\u003eth\u0026nbsp;\u003c/sup\u003epercentile median household income (NHB: 32% vs. HL: 26% vs. NHW: 18%, p\u0026lt;0.001) and NHB children were two-fold more likely to be below the United States federal poverty line (NHB: 7% vs. HL: 4% vs. NHW: 3%, p\u0026lt;0.001). Moreover, NHB and HL children were more likely to be treated at low-volume centers (NHB: 17% vs. HL: 18% vs. NHW: 13%, p\u0026lt;0.001) than their White counterparts. Almost one-fourth of NHB were born prematurely (NHB: 23% vs. HL: 20% vs. NHW: 19%, p\u0026lt;0.001) and with low birth weight (NHB: 17% vs. HL: 10% vs. NHW: 10%, p\u0026lt;0.001) (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cu\u003ePost S1P outcomes and resource utilization of one-year conditional survivors\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePost-Norwood clinical outcomes revealed two-fold higher rates of tracheostomy in NHB children (NHB: 6% vs. HL: 2% vs. NHW: 1%, p\u0026lt;0.001), higher rates of delayed sternal closure (NHB: 11% vs. HL: 10% vs. NHW: 7%, p\u0026lt;0.001) and prolonged mechanical ventilation (NHB: 12% vs. HL: 11% vs. NHW: 8%, p\u0026lt;0.001) (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, the authors investigated resource utilization in one-year survivors, including hospital visits, hospitalization time, procedures, diagnostics, medication, and healthcare expenditure. Analysis of hospitalization resources demonstrated significantly increased length of stay in the S1P index admission in NHB children (NHB: 61 days [33-101] vs. HL: 53 [31-89] vs. NHW: 41 [27-71] p\u0026lt;0.001). Furthermore, NHB and HL children had significantly increased 30-day inpatient hospital readmission (NHB: 12% vs. HL: 11% vs. NHW: 8%, p\u0026lt;0.001) as compared to NHW, with respectively increased readmission hospitalization length (days) (NHB: 17 [11-31] vs. HL: 12 [7-17] vs. NHW: 9 [4-21] p\u0026lt;0.001) as well as higher number of emergency department visits 6 months after S1P (NHB: 9 [6-21] vs. HL: 7 [4-14] vs. NHW: 6 [3-10], p\u0026lt;0.001). Contrasting, the number of post-S1P clinic visits was significantly lower in NHB one-year survivors (NHB: 6 [2-9] vs. HL: 9 [4014] vs. NHW: 11 [4-19] p\u0026lt;0.001). Additionally, NHB were more likely to be in the lower 25\u003csup\u003eth\u003c/sup\u003e percentile of days alive and outside the hospital after S1P than White children (NHB: 18% vs. HL: 16% vs. NHW: 10%, p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eThe procedural resource utilization of one-year conditional survivors did not reveal any differences in the utilization of cardiac catheterizations and non-cardiac procedures. Further assessment of diagnostic studies showed significantly reduced use of cardiac echocardiography in NHB children (NHB: 6 [3-11] vs. HL: 7 [4-13] vs. NHW: 10 [4-15], p\u0026lt;0.001), and non-cardiac imaging (NHB: 52 [27-86] vs. HL: 57 [42-79] vs. NHW: 68 [39-115], p\u0026lt;0.001). There was no difference in the total medication numbers of the inpatients. However, adjusted costs of hospitalization were significantly higher in NHB and HL children (NHB: 912,411 [551,051-1,516,491] vs. HL: 722,588 [445,611-1,169,582] vs. NHW: 535,917 [307613-790,192], p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cu\u003eUnadjusted and one-year conditional Kaplan-Meier survival analysis\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eUnadjusted cumulative mortality stratified by combined race and income of all HLHS children who underwent S1P showed the lowest mortality in high-income (HI) White children. Highest cumulative mortality was observed in low-income (LI) Back children (Year 1 LI-Black: 20% vs HI-White: 12%, p\u0026lt;0.001). The mortality ratio at year one between low-income Black and high-income White children was 1.6 at year one and 1.8 at year five (Figure 1A).\u003c/p\u003e\n\u003cp\u003eAdjusted one-year conditional survival continued to demonstrate significantly increased and 2.5 higher mortality in low-income Black children (Year 5 LI-Black: 10% vs. HI-White: 4%, p\u0026lt;0.001), whereas mortality in other race and socio-economic groups did not yield differences when selecting for one-year survivors (Figure 1B). Furthermore, the mortality ratio of one-year conditional survivors at year three was 2.3 and 2.5 at year five in low-income Black children, thus, revealing a significant step wise increase compared to the total unadjusted cohort of high-income White children at one year.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cu\u003eMultivariate Cox proportional hazard regression of mortality in one-year conditional survivors\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn- total, 21 univariate predictors of mortality at year one for unadjusted patients and 18 univariate predictors of mortality at year three for adjusted one-year survivors were assessed (Table 3-4). In unadjusted patients, nine clinical and social co-variates increased mortality in year one. The highest predictor of mortality was tracheostomy (HR: 5.63 [3.45 \u0026ndash; 8.07], p 0.002), followed by treatment at low volume centers (HR: 4.90 [3.20 \u0026ndash; 6.44], p\u0026lt;0.001), being Black and below the federal poverty line (HR: 3.74 [1.89-5.52], p\u0026lt;0.001) and being Black and from a low-income family (HR:1.99 [1.33-3.34], p\u0026lt;0.001) (Table 3).\u003c/p\u003e\n\u003cp\u003eIn adjusted one-year survivors, seven clinical and social co-variates increased mortality in year three (Table 4). The strongest predictor of mortality was being Black and below the federal poverty line (HR: 6.65 [2.06-8.56], p\u0026lt;0.001), followed by tracheostomy (HR: 4.82 [2.93 \u0026ndash; 7.91], p 0.002), being Black and from a low-income household (HR: 3.30 [2.33-5.34] p 0.001). White children, regardless of income status, remained unaffected in the adjusted one-year conditional prediction model. In contrast, the Hazard Ratios of Black children from low-income households (HR Adjusted Year 3: 3.3 vs. Unadjusted Year 1: 1.99) and below the federal poverty line (HR Adjusted Year 3: 6.65 vs. Unadjusted Year 1: 3.74) at year three increased almost two-fold as compared to unadjusted palliated Black children at year one. Region and insurance status were not predictors of mortality in adjusted one-year conditional survivors (Table 4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present report demonstrated that social determinants of health, such as government-sponsored insurance, lower household income, and disproportionate treatment at low-volume centers, remained risk factors in one-year conditional HLHS survivors. Non-Hispanic Black and Hispanic-Latino children received less outpatient care and cardiac and non-cardiac imaging. In contrast, inpatient readmission, length of stay, and emergency department visits were significantly increased in NHB one-year survivors. In this large multicenter cohort, we also found that the combination of race and social determinants of health had a significantly negative effect on mortality and was substantially amplified in low-income Black children after the first year of life, as demonstrated by a stepwise increase in cumulative mortality ratios and rising Hazard Ratios in vulnerable children.\u003c/p\u003e \u003cp\u003eDespite the overall improvement in the life expectancy of CHD patients, disparities in morbidity and mortality, as well as resource utilization, exist. Numerous predictors affecting mortality and disparate resource use have been analyzed, with a broad consensus that critical examination of multilevel contributions that facilitate health inequities is required. \u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Regarding the importance of the multi-level approach, Lopez et al. analyzed various factors that specifically influence HLHS. \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e They confirmed the impact of factors such as social determinants of health, hospital distance, language proficiency, racial bias, and the intersection between institutional regionalization of care and geography on outcomes. Furthermore, a closer look revealed that Black race and low surgical volume remain predictors of mortality throughout the eras. \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e While the vast body of literature has identified the stark reality of racial inequities in HLHS, the present study aims to shift focus from traditional HLHS assessment and extend the perspective to the progress of HLHS survivors beyond the first year.\u003c/p\u003e \u003cp\u003eAn important finding of the present study is that the differences mentioned above do not cease to exist even in \u0026ldquo;successful\u0026rdquo; one-year conditional survivors but seem to increase in Black and Hispanic-Latino communities as well as low-income families. This study emphasizes the concerning distribution of lower outpatient clinic visits, cardiac and non-cardiac imaging, that potentially contributed to increased readmission rates, and substantially increased costs in Black and Hispanic-Latino children. Similar findings have been confirmed in other patient populations, inclusive of specialized transplant and general pediatric care in which Black and Hispanic-Latino children had significantly fewer clinic visits, reduced access to care, and general follow-up in the outpatient setting. \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e The authors believe that these effects linger in children of minority communities that would have been otherwise deemed as successfully palliated. The authors have recently demonstrated the immense burden and resource utilization that are invested in the first year of life for HLHS children. \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAnother important finding of this study is that SES and race significantly impact mortality beyond the first year. Cumulative mortality in low-income Black children was more than two-fold higher in one-year conditional survivors at three years and at five years of age compared to Non-Hispanic White children from high-income backgrounds. It was noteworthy that the cumulative effect of SES and race most significantly affected Non-Hispanic Black children. However, an improvement in SES (i.e., high income) did not significantly increase Non-Hispanic Black nor Hispanic children\u0026rsquo;s survival, nor did a decrease in SES (i.e., low income) significantly decrease Non-Hispanic White children\u0026rsquo;s survival. Lopez et al. report that the interplay of race, and SES was critical in examining the effects of the intersection. It revealed that especially complex CHDs are not immune to disparities. \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e While mortality in HLHS has declined overall, racial and ethnic disparities in mortality have remained the same in the current era. \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Yet, qualitative and community-based participatory research heavily emphasized the first year of life. Single ventricle programs focus many resources (e.g., special clinics, home monitoring, frequent calls, etc.) during the first year of life, especially during the interstage period (e.g., the practice of keeping S1P patients in hospital until S2P), and despite this, SES and race still have a significant effect. This intense focus decreases at most programs significantly after the first year, and therefore, one would expect, as this analysis demonstrated, that the negative effects of SES and race would be amplified. Perhaps this is even more evident in low-volume programs with fewer resources, which may explain the Hazard ratio of 3.49.\u003c/p\u003e \u003cp\u003eThere are limitations to this study. The exact indications and rationale for center-specific resource allocation could not be assessed. PHIS contains a sample of pediatric hospitals in the US, so it may not be generalizable to all congenital centers. The burden reported herein is minimally accumulated due to the potential for missing certain outpatient visits, such as telehealth appointments. We were unable to assess specific vulnerable communities such as Native Americans and Pacific Islanders or patients categorized as others due to missing information. Moreover, this study was not designed to determine a myriad of surgeon and provider-specific aspects, such as physician ratios, implicit and explicit biases, and geographic and regional disparities. Therefore, the true extent of long-term disparate access to care and problems in resource allocation may be even more pronounced.\u003c/p\u003e \u003cp\u003eIn conclusion, this analysis reveals that the effect of social determinants of health and race, after the intense focus on first year post-S1P care begins to wane, seems to amplify and is most pronounced in the most vulnerable populations (e.g., Black children from low-income families). As mortality in minority children is increased and resource use is substantially lower, this report may open avenues to rethink resource allocation in HLHS care and equitable distribution that supports these vulnerable communities when the effects of social determinants of health become more prominent. Further policy review assessing HLHS health equity, including examination at the individual, systemic, and population levels, seems warranted.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSES: Socioeconomic Status\u003c/p\u003e\n\u003cp\u003eS1P: Stage-I-Palliation\u003c/p\u003e\n\u003cp\u003eHLHS: Hypoplastic Left Heart Syndrome\u003c/p\u003e\n\u003cp\u003ePHIS: Pediatric Health Information System\u003c/p\u003e\n\u003cp\u003eICD: International Classification of Disease\u003c/p\u003e\n\u003cp\u003eNHW: Non-Hispanic White\u003c/p\u003e\n\u003cp\u003eNHB: Non-Hispanic Black\u003c/p\u003e\n\u003cp\u003eHL: Hispanic-Latino\u003c/p\u003e\n\u003cp\u003eLI: Low Income\u003c/p\u003e\n\u003cp\u003eHI: High Income\u003c/p\u003e\n\u003cp\u003eCHD: Congenital Heart Disease\u003c/p\u003e\n\u003cp\u003eHR: Hazard Ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDavid L. S. Morales reports a relationship with Abbott Vascular, Aziyo, Xeltis BV, Berlin Heart, SynCardia Systems (consulting or advisory). that includes: consulting or advisory. Awais Ashfaq reports a relationship with Pyrames that includes: non-financial support. If\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eA. M. S. wrote the main manuscript text, performed the analysis, and prepared tables and figuresG. C. assisted in the analysis and reviewed the manuscript and contributed to revisionsM. F. prepared tables and figures and reviewed the manuscript and contributed to revisionsN. K. reviewed the manuscript and contributed to revisionsA. A. reviewed the manuscript and contributed to revisionsD. L. reviewed the manuscript and contributed to revisionsH. H. reviewed the manuscript and contributed to revisionsM. R. reviewed the manuscript and contributed to revisionsD. L. S. M. wrote the manuscript text, reviewed methodology, reviewed the manuscript and contributed to revisions\u003c/p\u003e\n\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional Funding\u003c/strong\u003e: None\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKaramlou T, Hawke JL, Zafar F et al (2022) Widening our focus: characterizing socioeconomic and racial disparities in congenital heart disease. Ann Thorac Surg 113(1):157\u0026ndash;165\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrishnan A, Jacobs MB, Morris SA et al (2021) Impact of socioeconomic status, race and ethnicity, and geography on prenatal detection of hypoplastic left heart syndrome and transposition of the great arteries. Circulation 143(21):2049\u0026ndash;2060\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoss FJ, Latham G, Tjoeng L, Everhart K, Jimenez N (2023) Racial and ethnic disparities in US children undergoing surgery for congenital heart disease: A narrative literature review. SAGE Publications Sage CA, Los Angeles, CA, pp 224\u0026ndash;234\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchidlow DN, Gauvreau K, Bucholz EM et al (2023) Prenatal care coordination, racial and socioeconomic inequities, and pre-and post-operative outcomes in hypoplastic left heart syndrome. J Perinatol 43(3):378\u0026ndash;384\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez KN, Baker-Smith C, Flores G et al (2022) Addressing social determinants of health and mitigating health disparities across the lifespan in congenital heart disease: a scientific statement from the American Heart Association. J Am Heart Association 11(8):e025358\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDean PN, McHugh KE, Conaway MR, Hillman DG, Gutgesell HP (2013) Effects of race, ethnicity, and gender on surgical mortality in hypoplastic left heart syndrome. Pediatr Cardiol 34:1829\u0026ndash;1836\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSborov KD, Haruno LS, Raszka S, Poon SC (2023) Racial and Ethnic Disparities in Pediatric Musculoskeletal Care. Curr Rev Musculoskelet Med 16(10):488\u0026ndash;492\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmir Mehdizadeh-Shrifi MF, Kevin Kulshrestha H, Heydarian R, Hirsch M, Hossain S, Hogue A, Ashfaq D, Morales (2023) Sr. Unveiling the Complete Medical Burden of Hypoplastic Left Heart Syndrome: 18 Years of Insight from Childhood to Adolescence. 10/31/2024, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.aats.org/resources/unveiling-the-complete-medical-7727\u003c/span\u003e\u003cspan address=\"https://www.aats.org/resources/unveiling-the-complete-medical-7727\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez KN, Morris SA, Sexson Tejtel SK, Espaillat A, Salemi JL (2020) US mortality attributable to congenital heart disease across the lifespan from 1999 through 2017 exposes persistent racial/ethnic disparities. Circulation 142(12):1132\u0026ndash;1147\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 4 are available in the Supplementary Files section.\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":"Burden, Socioeconomic status, disparities, resource utilization","lastPublishedDoi":"10.21203/rs.3.rs-6591389/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6591389/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eRace and social determinants of health are known to impact stage-I-palliation (S1P) outcomes. Resources are predominantly focused during their first year of life which may reduce the impact of socioeconomic status (SES) and race. We sought to investigate their impact on long-term outcomes in patients who survived at least one year.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe Pediatric-Health-Information-System database was used to identify patients born with Hypoplastic Left Heart Syndrome (HLHS) who underwent S1P and survived to age one. Outcomes and resource utilization were compared by stratifying patients based on SES and race.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 5,968 children who underwent S1P and survived one year were included. Amongst these, 3,932(66%) were Non-Hispanic White (NHW), 924(15%) were Non-Hispanic Black (NHB) and 569(9%) were Hispanic-Latino (HL). Adjusted one-year conditional mortality demonstrated significantly increased mortality in low-income (LI) Black children (Year 3 LI-Black:7% vs. HI-White:3%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The difference in mortality ratio was almost double compared to the total unadjusted cohort in year one. In a multivariate analysis for one-year conditional survival at year three, Black children below the poverty line (HR:6.65 [2.06\u0026ndash;8.56]p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was the strongest predictor of mortality and the HR was lower in unadjusted patients at year one (HR:3.74 [1.89\u0026ndash;5.52]p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eMortality is significantly increased in low-income Black children, and the negative effect of SES is greater after one year. Disparities in HLHS care and social determinants of health become amplified for Black children from low-income families after the first year suggesting that there are opportunities to review resource allocation of vulnerable children.\u003c/p\u003e","manuscriptTitle":"What is the Cumulative Impact of Race \u0026amp; Social Determinants of Health on Minorities’ Single Ventricle Journey Beyond the First Year","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 06:37:45","doi":"10.21203/rs.3.rs-6591389/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":"868b4a19-ac1f-45b4-8f9f-e831cfd3861f","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-11T11:24:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-13 06:37:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6591389","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6591389","identity":"rs-6591389","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}