Outcomes after Heart Transplantation among Non-Native English-Speaking Recipients

Abstract

Introduction:

Effective communication and understanding are imperative for heart transplant (HT) recipients who require lifelong adherence to treatment plans and medications. Whether non-native English speaking (NNES) recipients have inferior outcomes compared to native English-speaking recipients (NES) has not been studied post-HT.

Methods:

We reviewed adult HT recipients at Columbia University Irving Medical Center from January 2005 through December 2022 with primary language determined by chart review. Baseline characteristics and patient level zip codes which were used to derive socioeconomic status (SES) index using data from the Agency for Healthcare Research and Quality (AHRQ) were included. Mortality at 1-year and 5-year was compared between NNES and NES. Survival curves were estimated by the Kaplan-Meir method and log-rank testing was used to compare survival between groups. Secondary outcomes including hospitalization, hospitalization for infection, and rejection at 1-year, as well as rejection and CAV at 5-years were analyzed using cumulative incidence functions with Gray’s testing to detect outcome differences between groups. Multivariable Cox proportional hazard models were constructed to determine if there was an association between NNES and primary and secondary outcomes.

Results:

Of 1,066 HT recipients, 103 (10%) were NNES. NNES recipients were more likely to identify as non-White, have Medicaid as the primary payer, and have lower educational attainment. On average, NNES recipients resided in zip codes with higher levels of unemployment, lower educational attainment, and lower household incomes. Overall, NNES had lower median AHRQ SES indices (51 vs 55, p<0.001). After adjustment for clinical factors including socioeconomic status, race/ethnicity, and education level, mortality at 1- and 5-years for NNES and NES recipients were not significantly different although there was a trend towards improved survival in the NNES group (1-year adjusted hazard ratio (HR) 0.24, 95% CI 0.06-1.01, p=0.05; 5-year adjusted HR 0.48, 95% CI 0.22-1.03, p=0.06). Similarly, there were no differences in need for re-hospitalization, infection requiring hospitalization, and rejection at 1 year.

Conclusions:

There were no significant differences in outcomes at 1 year and 5 years post-HT among NNES and NES. Availability of interpreter services and educational resources in multiple languages are paramount to maintaining effective communication and equitable outcomes.

Lay Summary

Although the population of individuals living with heart failure in the United States is incredibly diverse, little is known about whether non-Native English speakers (NNES) fare differently after heart transplantation. In this study of over 1000 heart transplant recipients, we found that although NNES patients were more likely to be non-White, had lower education status and had public insurance, outcomes were similar at 1- and 5-years after transplant.

Introduction:

Heart transplantation (HT) is the gold standard therapy for end-stage heart failure (HF). Given the scarcity of donor hearts relative to the advanced HF population in need, patient selection is paramount given the need for meticulous post-transplant care and close engagement with the medical system to optimize post-HT outcomes. While long term post-transplant survival in heart recipients has progressively improved during the past two decades among White individuals, this has not been the case among Black or Hispanic recipients.^1–3 Large national transplant registry studies have shown that Black recipients have a 34% to 46% higher adjusted cumulative mortality after HT, compared to White recipients.⁴ Black patients also experience more major morbid events post-HT, including acute rejection, cardiac allograft vasculopathy (CAV), and graft failure, compared to other racial groups. Similarly, compared to Whites, Hispanics have decreased 30-day and 1-year survival post HT.³ These disparities are multifactorial in origin, and include differences in immunologic risk, implicit biases, and social determinants of health including income, education level, and social and community context.⁴ Embedded in these are cultural factors such as primary language.

At least 350 languages are spoken in the United States, and approximately 20% of the US adult population is non-English speaking.⁵ Multiple studies have shown that non-English speaking patients often face challenges when receiving medical care including limited understanding and adherence, decreased preventative services, and dissatisfaction with care.^6–9 Effective communication and understanding are pivotal following HT which requires livelong adherence to treatment plans and medications. Previous studies have assessed the effect of being non-English-speaking on transplant outcomes among kidney and hematopoietic stem cell transplant recipients^10,11 and found that not speaking English impacts a patient’s understanding and use of health information and correlates with health disparities. Among kidney transplant candidates, those with limited health literacy had decreased likelihood of listing and a 2.42-fold increased risk of mortality on the waiting list.¹¹ In a population of hematopoietic stem cell transplant recipients, survival was similar between NNES and NES¹⁰; however, data are lacking among HT recipients.

Given the established healthcare disparities that exist in HT and the urgent need to ameliorate them, this study aimed to understand the association between primary language spoken on post-HT outcomes in order to help develop targeted interventions and improve equitable access for this life-saving therapy.

Methods:

Study Population

Adult recipients (aged ≥ 18 years) who underwent HT between January 1, 2005, and December 31, 2022, at Columbia University Irving Medical Center (CUIMC) were included in this retrospective analysis. Patients’ primary language was determined based on review of electronic medical records and documentation of interpreter services. The patient’s preferred language was recorded. Bilingual patients who preferred English and declined interpreter services during patient encounters were considered English-speaking. Patients for whom primary language was not able to be determined based on chart review were excluded from this study. Patients who underwent re-transplantation were only included once. To capture the potential effect of language on post-discharge management and post-HT morbidity, patients who died during index admission were excluded from this study. This study was approved by the CUIMC Institutional Review board.

Services Available for NNES Individuals

Our institution has professional interpreter services available 24 hours a day; these may be in-person, by phone or by video. Additionally, multiple HF team members are bilingual. Printed educational material for our heart transplant recipients regarding lifestyle changes and immunosuppression are available in Spanish, English, and Mandarin.

Variables of Interest

For all individuals, baseline comorbidities and characteristics at the time of HT including use of mechanical circulatory support, UNOS status and donor characteristics were collected.

As primary language intersects with other social determinants of health, which may also impact patient outcomes, an effort was made to account for neighborhood-level socioeconomic status (SES). Patient-level zip code data were collected from the medical record. For each five-digit zip code, an SES index was then estimated using a method created and validated by the Agency for Healthcare Research and Quality (AHRQ) and data extracted from the 2019 American Community Survey. The AHRQ SES index is a weighted combination of seven census-derived variables which capture employment, households below the federal poverty line, educational attainment, median household income, median property values, and household crowding which has been used previously.^12–14 AHRQ index values range from 0 to 100 with higher values representing higher SES levels.

Outcomes

The primary outcome was survival at 1-year and 5-years post-HT. Secondary outcomes included acute cellular rejection (ACR), antibody-mediated rejection (AMR), all-cause hospitalization, and infection requiring hospital admission at 1-year, and rejection and CAV at 5-year post HT. Rejection was defined as either biopsy-proven rejection (ISHLT Grade 2 or above for ACR, ISHLT pAMR 1 or above¹⁵) or clinical rejection requiring treatment. CAV was defined based on coronary angiography using the Stanford criteria for CAV.¹⁶

Follow-up was complete through December 31, 2023. For all analyses, the comparison groups included native English-speaking (NES) recipients and non-native English-speaking recipients (NNES).

Statistical Analysis

Continuous variables were reported as means with standard deviations if normally distributed or medians with interquartile ranges if not normally distributed. Categorical variables were presented as numbers with percentages. For continuous variables, differences between groups were tested for statistical significance using Student’s T-Test if data were normally-distributed or Wilcoxon rank-sum tests if not normally distributed. For categorical variables, chi-squared tests or Fisher’s exact tests where expected values were < 10 were used.

Survival curves were estimated by the Kaplan-Meier method and log-rank testing was used to compare survival between groups. Secondary outcomes were analyzed using cumulative incidence functions with Gray’s testing to handle the competing risk of death. Cause-specific hazard models were used for the outcome of interest.

Multivariable Cox proportional hazard models were constructed to determine the association between NNES with primary and secondary outcomes. Covariates for the multivariable model were selected a priori based on clinical relevance and included age, sex, race/ethnicity, insurance status (defined as private primary payer versus other), level of educational attainment (defined as college degree/higher versus other), year of HT, AHRQ SES index, and UNOS status at transplant.

All tests were 2-tailed with a critical P value of 0.05. All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).

Results:

Baseline Characteristics

From 2005 to 2022, 1,162 HT were performed at our institution. After exclusions, 1,066 were included in this analysis (Supplemental Figure 1). Of these, 103 (10%) were NNES. Sixteen languages were spoken among NNES; the most common non-English language spoken was Spanish (n=73, 71%) (Supplemental Table 1). Trends in NNES HT recipients by year are shown in Figure 1.

Figure 1. Proportion of Non-Native English-Speaking Heart Transplant Recipients Over Time.

The proportion of non-native English-speaking (NNES) heart transplant recipients as a function of transplant year is shown for the study period of 2005 through 2022.

Baseline characteristics by primary language are shown in Table 1. NNES were older (median age 56 vs. 52 years, p = 0.002), less likely to identify as white (16% vs 57%, p <0.001), and less likely to be US citizens (63% vs 94%, p < 0.001). Compared to NES, NNES were also more likely to have Medicaid (39% vs 17%, p<0.001) or Medicare (32 vs 22%, p<0.001) as the primary insurance payer and less likely to have a college (23% vs 43%, p<0.001) or post-college graduate degree (2% vs 13%, p<0.001). Functional status, UNOS status at transplantation, and presence of mechanical circulatory support were similar between groups (p>0.05 for all).

Table 1.

Baseline characteristics stratified by primary language

	Non-Native English-Speaking (n = 103)	Native English Speaking (n = 963)	P value
Age, years, mean (SD)	56.2 (11.6)	52.1 (13.0)	0.002
Age, years, n (%)
18-39	9 (8.7)	173 (18.0)	0.028
40-64	67 (65.1)	607 (63.0)
≥65	27 (26.2)	183 (19.0)
Male, n (%)	80 (77.7)	717 (74.5)	0.48
Race/Ethnicity, n (%)
Non-Hispanic White	16 (15.5)	550 (57.1)	<0.001
Non-Hispanic Black	1 (1.0)	249 (25.9)
Hispanic	71 (68.9)	105 (10.9)
Other	15 (14.6)	59 (6.1)
Primary payer, n (%)
Private	24 (23.3)	575 (59.7)	<0.001
Medicaid	40 (38.8)	160 (16.6)
Medicare	33 (32.0)	210 (21.8)
Other	6 (5.8)	18 (1.9)
Level of education
None or grade school	21 (20.4)	28 (2.9)	<0.001
High school	36 (35.0)	266 (27.6)
College*	24 (23.3)	412 (42.9)
Post-college graduate degree	2 (1.9)	128 (13.3)
Other	20 (19.4)	129 (13.4)
Citizenship, n (%)
US Citizen	65 (63.1)	905 (94.0)	<0.001
Resident	29 (28.2)	52 (5.4)
Other	9 (8.7)	6 (0.6)
Year of transplant, n (%)
2005-2009	39 (37.9)	309 (32.1)	0.24
2010-2014	19 (18.5)	242 (25.1)
2015-2019	20 (19.4)	223 (23.2)
2020-2022	25 (24.3)	189 (19.6)
UNOS status 1A at transplant pre-2018 allocation revision or status 1, 2, or 3 post-2018 allocation revision, n (%)	64 (62.1)	681 (70.7)	0.071
Ischemic cardiomyopathy, n (%)	29 (28.2)	258 (26.8)	0.75
Diabetes, n (%)	36 (35.0)	241 (25.0)	0.029
Cerebrovascular disease, n (%)	11 (10.7)	84 (8.7)	0.51
Functional status at listing, n (%)**
Excellent	4 (4.0)	28 (3.0)	0.76
Moderate	68 (68.7)	664 (71.7)
Poor	27 (27.3)	234 (25.3)
Implanted cardiac defibrillator	70 (68.6)	687 (71.4)	0.69
IABP at transplant, n (%)	22 (21.4)	150 (15.6)	0.16
Durable VAD at transplant, n (%)	18 (17.5)	153 (15.9)	0.68
ECMO at transplant, n (%)	2 (1.9)	35 (3.6)	0.57
Multiorgan transplantation
Lung, n (%)	0 (0)	5 (0.52)	1.0
Liver, n (%)	1 (0.97)	13 (1.4)	1.0
Kidney, n (%)	3 (2.9)	35 (3.6)	1.0
Ischemic time, hours, mean (SD)	3.2 (0.82)	3.2 (1.0)	0.74
Donor age, years, mean (SD)	30.8 (11.5)	33.1 (11.9)	0.067
Donor male sex, n (%)	40 (40.8)	516 (55.9)	0.004
Donor race/ethnicity, n (%)
Non-Hispanic White	55 (53.4)	550 (57.1)	0.74
Non-Hispanic Black	20 (19.4)	169 (17.6)
Hispanic	19 (18.5)	183 (19.0)
Other	9 (8.7)	61 (6.3)
Donor hypertension, n (%)	11 (10.7)	132 (13.7)	0.45
Hepatitis C positive donor, n (%)	6 (5.8)	39 (4.1)	0.43
Donation after circulatory death, n (%)	5 (5.1)	32 (3.5)	0.39

ECMO = extracorporeal membrane oxygenation; IABP = intra-aortic balloon pump; IQR = interquartile range; UNOS = United Network for Organ Sharing; VAD = ventricular assist device

^*Includes those who attended college/technical school and those who achieved an associates/bachelor’s degree

^**41 individuals missing data.

Zip code level socioeconomic status indicators were analyzed and stratified by the primary language spoken. Five hundred and fifty-seven unique zip codes were represented in our cohort. On average, NNES recipients resided in zip codes with comparatively higher levels of unemployment (6.9 vs 5.4, p<0.001), lower educational attainment (21% with less than high school education in NNES vs 10% in NES), and lower household incomes ($57,266 vs $85,088, p<0.001). Overall, NNES had lower median Agency for Healthcare Research and Quality SES indices (51 vs 55, p<0.001) (Table 2).

Table 2.

Zip-code level socioeconomic status indicators, stratified by primary language

	Non-Native English-Speaking (n = 103)	Native English Speaking (n = 963)	P value
Percentage of civilian labor force that is unemployed, median [IQR]	6.9 [5.4-9.8]	5.4 [4.1-6.7]	<0.001
Median household income (dollars, inflation-adjusted to 2020), median [IQR]	57,266 [49,439-80,746]	85,088 [62,224-110,490]	<0.001
Percentage of population with an income to poverty ratio under 1.00, median [IQR]	18.0 [10.9-23.4]	8.6 [5.3-15.3]	<0.001
Percentage of population with a bachelor’s degree, median [IQR]	20.8 [14.9-22.3]	21.9 [16.5-28.9]	0.006
Percentage of population with less than high school education, median [IQR]	20.7 [14.0-25.7]	10.0 [5.6-16.4]	<0.001
Median home value of owner-occupied housing units, median [IQR]	500,800 [386,100-639,800]	464,100 [345,100-615,500]	0.027
Percentage of housing units with more than one occupant per room, median [IQR]	7.7 [5.2-11.6]	3.4 [1.2-6.7]	<0.001
Agency for Healthcare Research and Quality SES index, median [IQR]	51.2 [49.6-54.5]	54.9 [52.0-57.8]	<0.001

IQR = interquartile range

Post-HT Mortality

The mean follow-up time for the study cohort was 6.2 years (standard deviation 4.9 years). Reported mortality rates exclude those individuals who died during the index HT hospitalization. Overall, mortality post-HT was similar amongst NNES and NES individuals at 1 year (2.2% vs 4.4%, log rank p = 0.32 and 5 years post-HT (10.4 vs 17.0%, log rank p = 0.13)(Table 3). In the adjusted multivariable model to predict 1- and 5-year mortality, there were no statistically significant differences in risk of death according to primary language (NNES vs NES)(1-year adjusted hazard ratio (HR) 0.24, 95% CI 0.06-1.01, p = 0.05; 5-year adjusted HR 0.48, 95% CI 0.22–1.03, p = 0.06)(Table 4).

Table 3.

Association Between Primary Language and Unadjusted Morbidity and Mortality After Heart Transplantation

	Non-Native English-Speaking (n = 104)	Native English Speaking (n = 968)	P value
1-y post transplantation, n (%) [% 95% CI]*
Mortality	2 (2.2) [0.57-8.7]	40 (4.4) [3.2-5.9]	0.32
Any hospitalization	57 (57.0) [46.6-66.1]	518 (54.6) [51.4-57.7]	0.56
Hospitalization for infection	41 (41.5) [31.5-51.2]	313 (32.5) [29.5-35.5]	0.13
Acute cellular rejection	32 (32.5) [23.4-41.9]	337 (35.2) [32.2-38.3]	0.59
Antibody mediated rejection	4 (4.1) [1.3-9.5]	73 (7.6) [6.0-9.4]	0.21
Rejection (combined)	33 (32.0) [23.2-41.2]	356 (36.4) [33.3-39.4]	0.41
5-y post transplantation, n (%) [% 95% CI]
Mortality	8 (10.4) [5.3-19.9]	128 (17.0) [14.4-20.0]	0.13
Cardiac allograft vasculopathy	20 (25.0) [16.1-35.0]	269 (32.6) [29.3-35.8]	0.10
Rejection (combined)	46 (44.7) [34.8-54.0]	446 (45.8) [42.6-48.9]	0.78

^*For mortality, Kaplan-Meier method with log-rank testing was used. For other outcomes, cumulative incidence function with fine gray testing was used

Table 4.

Association Between Primary Language and Adjusted Morbidity and Mortality after Heart Transplantation

	Unadjusted Cox Regression		Adjusted Cox Regression
	HR (95% CI)	P-value	HR (95% CI)	P-value
1-y post transplantation, HR [95% CI]
Mortality	0.49 (0.12-2.02)	0.32	0.24 (0.06-1.01)	0.051
Any hospitalization	1.10 (0.82-1.42)	0.61	0.97 (0.69-1.36)	0.86
Hospitalization for infection	1.22 (0.89-1.68)	0.21	1.07 (0.72-1.59)	0.74
Acute cellular rejection	0.84 (0.60-1.21)	0.34	0.71 (0.47-1.07)	0.10
Antibody mediated rejection	0.45 (0.18-1.11)	0.08	0.33 (0.12-0.85)	0.02
Rejection (combined)	0.95 (0.85-1.06)	0.35	0.90 (0.79-1.03)	0.14
5-y post transplantation, HR [95% CI]
Mortality	0.58 (0.29-1.19)	0.14	0.48 (0.22-1.03)	0.060
Cardiac allograft vasculopathy	0.69 (0.47-0.99)	0.050	0.61 (0.40-0.94)	0.025
Rejection (combined)	0.98 (0.87-1.12)	0.86	0.92 (0.78-1.07)	0.26

^*Covariates for adjusted multivariable modes: age, race, year of transplantation, UNOS Status 1A prior to the allocation system revision or 1, 2, or 3 following the allocation system revision at the time of HT, educational attainment (college or more versus not), primary payer (private insurance versus not), and SES score

^**Chi-square testing was used to produce the p-values

Post-HT Morbidity

There were no significant differences in rates of overall hospitalizations (57.0%, 95% CI 46.6-66.1% in NNES vs. 54.6%, 95% CI 51.4-57.7% among NES, p = 0.56), hospitalization for infection (41.5%, 95% CI 31.5-51.2% in NNES vs 32.5%, 95% CI 29.5-35.5% in NES, p = 0.13), acute cellular rejection (32.5% in NNES 95% CI 23.4-41.9% compared to 35.2%, 95% CI 32.2-38.3% in NES, p-value = 0.59), or antibody mediated rejection (4.1%, CI 1.3-9.5% in NNES compared to 7.6% CI 6.0-9.4% in NES, p = 0.21) in unadjusted analyses (Table 3). Notably, NNES was associated with a lower risk of AMR compared to NES (adjusted HR 0.33, 95% CI 0.12-0.85, p = 0.02) among NNES compared to NES (Table 4). However, other outcomes were not significantly different in adjusted Cox analyses.

At 5 years post-HT, rates of combined rejection were similar between the two groups (44.7%, 95% CI 34.8-54.0% in NNES vs. 45.8%, 95% CI 42.6-48.9% among NES, p = 0.78). Rates of CAV were slightly lower amongst NNES (25.0%, 95% CI 16.1-35.0%) versus NES (32.6%, 95% CI 29.3-35.8%, p =0.10). After adjustment for covariates, NNES remained at slightly lower risk for CAV compared to NES (HR 0.61, 95% CI 0.40–0.94, p = 0.025) (Tables 3 and 4). Outcomes stratified by Spanish and non-Speaking NNES individuals are shown in Supplemental Table 2.

Discussion:

In this retrospective study, we examined the association of primary language with one- and five- year post-HT outcomes in a large diverse cohort of HT recipients. Our main findings were the following: (1) nearly 10% of our cohort were NNES with Spanish being the most represented language; (2) Compared to NES, NNES were more likely to have Medicaid as primary payer, less likely to have attained a college degree, had a lower median income, and had a lower median Agency for Healthcare Research and Quality SES index; and (3) even after adjusting for clinical, demographic, and zip-code level factors, we found no statistical difference in mortality or other key outcomes post-HT although clinical outcomes may be slightly more favorable in NNES recipients. (Figure 3). Our findings demonstrate that in an environment where language appropriate resources are available, NNES did not experience worse post-HT morbidity or mortality compared to NES.

Figure 3. Impact of Primary Language on Outcomes Post-Heart Transplant.

A summary figure of key study outcomes and findings is shown. HT = heart transplant; NES = Native English-speaking; NNES = non-Native English-speaking; SES = socioeconomic status

Our population of HT recipients encompassed a diverse population with respect to race, ethnicity, as well as geography with 557 unique zip codes represented. Additionally, our transplant center is located in the Washington Heights/Inwood neighborhood which may have contributed to the relatively large percentage of Spanish-speaking patients. In 2022, 66.5% of the Washington Heights population identified as Hispanic.¹⁷ Median household income for the neighborhood was 20% less than citywide median household income.¹⁷ To better serve this community, multiple members of the multidisciplinary transplant team (including social workers and transplant coordinators) are Spanish-speaking. Additionally, we have readily available patient educational materials in Spanish. These factors may partly explain why no difference was seen in outcomes in the current study among non-English speaking recipients as compared to English speaking recipients. Nevertheless, many other languages were represented in our analysis, and it is imperative to continue to improve the use and availability of interpreter services and transplant educational materials in a patient’s native language.

Additionally, our findings may partly be explained by bias in referral and selection for heart transplantation. Previous literature has established that under-represented racial and ethnic groups as well as women are less likely to be referred for advanced therapies.^18,19 Even among those who are referred, implicit bias may impact decision-making.²⁰ For example, only 16% of our HT population is Hispanic despite 67% of the surrounding area identifying as Hispanic. Therefore, the NNES recipients who were transplanted may have been held to a higher standard leading to favorable outcomes compared to NES recipients.

Social determinants of health, such as insurance, access to medication, and health literacy, impact outcomes post-HT.^21,22 Importantly, health literacy is considered a modifiable risk factor that can be improved through tailored patient education that improves understanding. Although health literacy was not measured directly in our study, health literacy is a well-established mediator of socioeconomic status. Intertwined with health literacy is patient language as well as the accessibility and readability of patient resources. Studies of kidney transplant center websites have shown that only 17% provided resources in a language other than English and website information consistently scored at a college reading level, which is significantly above the recommended sixth or seventh grade reading level by the CDC and NIH.²³ A similar analysis of heart transplant centers showed that most patient-directed information on heart transplant center websites is at the reading level of a college junior and that only half of centers currently offer non-English resources.²⁴ Given the large proportion of patients who are NNES, these findings underscore a modifiable organizational contributor to poor health literacy which in turn may impact outcomes from HT among marginalized populations. Improving readability and ensuring that HT education materials are available in patients’ native language is thus a potential avenue to further decrease HT disparities.

Another potential avenue to improve patient engagement among HT patients and subsequent outcomes is the use of diverse healthcare teams and professional interpreters. In the US, approximately 26 million people are considered to have limited English proficiency (LEP). Previous literature has suggested that race and sex concordance between patients and providers may be associated with improved patient satisfaction and improved patient outcomes. One study from orthopedics found that patient-physician language concordance was associated with improved patient-reported communication with their physician.²⁵ Although this was not investigated in the current study, this may be a potential strategy for mitigating disparities in post-transplant care. Furthermore, while the use of professional medical interpretation has been associated with improved overall health outcomes, decreased medical cost, and improved satisfaction²⁶, this has not been studied among HT patients specifically. A qualitative study which surveyed interpreters working with HF patients demonstrated that individuals with LEP had limited understanding of HF etiology, prognosis, and treatment options. Importantly, interpreters highlighted the discharge process as a specific missed opportunity to improve LEP patients’ comprehension of HF management.²⁶ The consistent use of professional interpreters among HT patients particularly at the time of discharge from their index admission may further decrease HT disparities.

Limitations

Our study also has important limitations. It is a single center study from a hospital with a 67% Hispanic neighboring population, which may limit generalizability to other geographically distinct centers across the United States. Furthermore, given the ease of access to interpreters 24 hours a day, sevend days a week at our center, as well as NNES staff members, our results on the effect of language on transplant outcomes may be underestimated. Unfortunately, national data sources with transplant specific registries collect a limited number of social determinants of health variables which often do not include primary language.²⁷ Further research in this area is needed, with a focus on geographic regions where access to interpreters may not be widely available and patient-centered outcomes including patient experience and quality of life.

Conclusions

In our single-center retrospective cohort study, we found that a primary language other than English was not associated with worse post-HT morbidity or mortality in an environment where language appropriate resources are available. Future qualitative studies as well as ongoing attempts to diversify the heart transplant care team and ensure the use of professional interpreters are important steps to improve the post-transplant experience for this population.

Figure 2. Kaplan–Meier unadjusted 5-year survival estimates after transplantation, stratified by primary language.

Survival curves are shown for non-native English-speaking heart transplant recipients (NNES) (shown in red) and native English-speaking heart transplant recipients (NES) (shown in blue) with no significant differences in mortality.

Brief Bullet Points.

• Data are limited regarding whether non-Native English speakers have different outcomes after heart transplantation than Native English speakers. there is an association between primary language spoken and outcomes after heart transplantation.

• In our single center study, non-native English speakers were less likely to be White, more likely to have public insurance and had lower educational attainment.

• After adjusting for clinical and sociodemographic variables, there were no differences in post-transplant survival, rejection, infection, or hospitalization.

Non-Standard Abbreviations

ACR

acute cellular rejection

AHRQ

Agency for Healthcare Research and Quality

AMR

antibody-mediated rejection

CAV

cardiac allograft vasculopathy

HF

heart failure

HT

heart transplantation

ISHLT

The International Society for Heart and Lung Transplantation

MCS

mechanical circulatory support

NES

native English speaker

NNES

Non-native English speaker

SES

socioeconomic status

UNOS

United Network for Organ Sharing

Biography