Associations between the stanford integrated psychosocial assessment for transplant and one-year lung transplant medical and psychosocial outcomes

Abstract

The Stanford Integrated Psychosocial Assessment for Transplant (SIPAT) is a standardized measure of the psychosocial risk profile of solid organ transplant candidates. While studies have found associations between this measure and transplant outcomes, to date this has not been examined in lung transplant recipients. We examined relations between pre-transplant SIPAT scores and 1-year lung transplant medical and psychosocial outcomes in a sample of 45 lung transplant recipients. The SIPAT was significantly associated with 6-minute walk test (χ²(1) = 6.47, p = .010), number of readmissions (χ²(1) = 6.47, p = .011), and mental health services utilization (χ²(1) = 18.15, p < .001). It was not a significantly associated with the presence of organ rejection or mortality (ps > 0.10). Results suggest that the SIPAT can help identify patients who are at an elevated risk for transplant complications and thus would benefit from services to mitigate risk factors and improve outcomes.

Introduction

Lung transplant is a well-established treatment for end-stage lung diseases such as chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF). While a lung transplant can significantly improve the recipient’s quality of life, it has a median survival rate of 55.6% at 5 years (Valapour et al., 2018). This is the lowest survival rate of any solid organ transplant. Additional research is needed to improve the survival rate for lung transplant recipients.

One way to increase the survival rate is to improve the detection of high-risk psychosocial and behavioral factors, such as active illicit substance use, that may contribute to complications. These risk factors may impact patients’ abilities to appropriately manage the rigorous post-transplant care requirements, such as an extensive daily medication regimen and frequent follow-up appointments (Castleberry et al., 2017; Dobbels et al., 2006). Better detection of these factors allows the transplant team to provide additional support and treatment to improve outcomes.

One way to identify risk factors is through a psychosocial evaluation. This is currently a standard component of the extensive and multidisciplinary transplant evaluation (Weill et al., 2015). The format of this evaluation varies, and increased standardization may allow for improved detection of risk factors. One standardized measure of psychosocial transplant candidacy is the Stanford Integrated Psychosocial Assessment for Transplant (SIPAT) (Maldonado et al., 2012). This measure examines several psychosocial domains including readiness for transplant, social support, psychological stability and psychopathology, and substance use. Initial studies have found that the SIPAT is predictive of both psychosocial and medical transplant outcomes.

Most studies on the SIPAT have focused on higher volume transplant populations such as heart, liver, and kidney (Chen et al., 2019; Deutsch-Link et al., 2021; Vandenbogaart et al., 2017). Only one study included lung transplant patients, but they collapsed outcomes across several solid organ groups (Maldonado et al., 2015). The authors found that the SIPAT was significantly related to several outcomes including psychiatric decompensation, rejection episodes, and hospitalizations. This study did not examine outcomes separately in each organ group; thus, it is unclear which outcomes are significantly related to the SIPAT in lung transplant patients. The current study aimed to help fill this gap in the literature by examining relations between pre-transplant SIPAT scores and 1-year lung transplant psychosocial and medical outcomes. Outcomes included mental health services utilization, physical rehabilitation progress, readmissions, presence of rejection episodes, and mortality.

Materials and methods

Sample

This study analyzed retrospective data collected as a part of standard clinical care and was approved by the Institutional Review Board. Participants underwent a lung transplant between November 2017 and March 2020 at a hospital that is affiliated with an academic medical center. This is a large academic medical center serving a predominantly rural population. Participants who had a SIPAT administered prior to a transplant and at least one year of outcome data following a transplant were included in the study. During their initial lung transplant evaluation visit all individuals provided written informed consent to have the clinical information related to their lung transplant (e.g., visit notes, self-report measures, etc.) included in research projects.

Measures

Stanford integrated psychosocial assessment for transplant

During the study period as part of the transplant workup process all lung transplant candidates underwent a psychological evaluation prior to listing that was conducted by a licensed clinical psychologist or a license-eligible clinical psychology fellow. The SIPAT was completed as part of this evaluation, and the scores were stored in a Research Electronic Data Capture (REDCap) project that was designed to track psychological transplant variables (Maldonado et al., 2012).

The SIPAT consists of 18 items rated on an ordinal scale distributed across 4 different subscales: readiness level, social support system, psychological stability and psychopathology, and lifestyle and effect of substance use. The SIPAT domains are typically used to guide a clinical interview, and the scores are derived based on clinical judgment. Patients also typically fill out self-report measures during their psychological evaluations, and this information is also used to inform the SIPAT scores. Additionally, all patients also underwent an evaluation with a licensed social worker which focuses more on evaluating social barriers to transplant (e.g., limited social support, unstable housing, etc.) but does also evaluate transplant readiness and psychopathology. The information from this evaluation was used to help inform the SIPAT score, especially for items on the social support system scale.

The SIPAT produces a total score with higher scores indicating worse psychosocial functioning. The SIPAT total score can be divided into ranges including excellent candidate (0–6), good candidate (7–20), minimally acceptable candidate (31–39), poor candidate (40–69), and high-risk candidate (71+). The SIPAT has high inter-rater reliability, and scores have been shown to predict listing status in lung transplant patients (Maldonado et al., 2012; Chernyak et al., 2021).

At the study transplant center, the SIPAT score is used to inform the presentation that psychology gives during the multidisciplinary committee meetings in which it is determined if patients are appropriate transplant candidates. The transplant team does not have any firm SIPAT cut-off score at which patients are deemed to not be candidates. However, patients in the poor and high-risk categories are rarely transplanted, and those in the high-risk category are often ruled out during a pre-screening phase prior to the full transplant workup. The psychologist and psychology fellow are members of the transplant committee. The social worker is also a member of the transplant committee and presents on transplant candidates. This presentation focuses more heavily on social variables but does contain information on psychological stability. If social work and psychology provide converging evidence that a patient has significant psychosocial risk factors this may be especially compelling to the team. Decisions about whether to transplant are ultimately collaborative. This is determined by the transplant team and takes into account both psychosocial and medical factors. As such, when medically indicated, the team may transplant a patient who is deemed to be at higher risk from a psychosocial perspective.

During the initial psychological evaluation, the SIPAT score is used to inform treatment recommendations. Patients who have significant risk factors or contraindications on the SIPAT are given recommendations to optimize their candidacy such as to initiate psychotherapy or discontinue alcohol use. These patients may have follow-up visits with psychology prior to transplant to evaluate progress on these recommendations.

Six-minute walk test

After transplant patients are discharged from the hospital, they are required to complete a course of daily intensive outpatient physical rehabilitation at an outpatient facility dedicated to thoracic transplant physical therapy. Patients attend this program for 2.5 hours each day for approximately 3–4 weeks. Patients complete a 6-minute walk test (6MWT) at the beginning and end of their time in the program to index their progress toward their pre-defined goals. This is a measure of functional status and is indexed by the distance patients are capable of walking over the course of 6 minutes including breaks as needed. We used the 6MWT completed at the end of the rehabilitation program to calculate the percent predicted performance. This was calculated by dividing each patient’s actual distance walked by the predicted distance for their age and sex based on the Enright equation (Jay & Enright, 2000). This yields a standardized measure with higher scores indicating better performance. 6MWT data was extracted from the database that the rehabilitation program uses to track patient outcomes.

Readmissions

Readmissions were defined as any unplanned hospitalization lasting longer than 24 hours following discharge after transplant. This data was extracted via review of each patient’s medical record in addition to the Organ Transplant Tracking Record software (OTTR; HKS Medical Information Systems, Omaha, NE). This is a web-based software that is used by many transplant centers and was designed to track transplant-specific data.

Acute cellular rejection episode

Acute Cellular Rejection (ACR) episodes requiring medical intervention and documented in the OTTR database were included in analyses.

Transplant behavioral health visits

While patients are in the hospital if they are experiencing significant distress that is impacting their ability to progress medically the inpatient treatment team can place a consult for transplant psychology and/or the psychiatry consultation-liaison team. After discharge, patients continue to have access to outpatient transplant psychology services but do not have access to any outpatient transplant psychiatry services. The transplant psychology team consisted of a psychologist, a psychology fellow, and up to two psychology interns. Services were typically available 4 days per week. The psychology team was available to both the heart and the lung transplant teams.

The role of transplant psychology was to assess and triage patients who were experiencing psychological problems after transplant that interfered with treatment adherence or had the potential to do so. Patients who already had psychiatric care established in the community prior to a transplant continued with that care (e.g., patients with serious and persistent mental illness). If the transplant team had concerns about these patients, psychology could meet with these patients and contact their community providers to ensure that they were aware of the team’s concerns. Transplant psychology provided brief interventions (approximately 4–6 sessions) for more acute issues that were directly impacting adherence (e.g., trouble weaning off of oxygen due to anxiety). Patients were referred to care in the community for more long-term issues (e.g., chronic depression that was exacerbated after transplant), specialized treatment needs (e.g., chemical dependency treatment), if the distance from the transplant center was prohibitive for routine visits, or outpatient medication management with a psychiatrist.

For our transplant behavioral health visits variable, we summed the number of inpatient psychiatry consultation-liaison/transplant psychology visits, and outpatient transplant psychology visits during the first year after the transplant. We chose to focus on these types of visits because they are the ones most likely to indicate transplant-related mental health needs. In particular, these types of visits would address problematic behaviors that are impacting transplant care (e.g., anxiety impacting the ability to participate in treatment while hospitalized, medical nonadherence, etc.). Other types of mental health visits (e.g., outpatient psychology visits) were not included because they are more likely to reflect more longstanding issues not directly linked to transplants (e.g., chronic depression). The number of visits was extracted by querying each patient’s medical record for visit type (e.g., psychiatry or psychology inpatient or outpatient visit). This information was then reviewed before calculating the total number of visits.

Mortality

Mortality was determined as death within the first year after a transplant. This information was extracted from the OTTR database.

Lung allocation score

Lung allocation score (LAS) indicates a candidate’s urgency for transplant and can range from 0 to 100, with 100 being the most severe. This data was obtained by reviewing patients’ listing data in OTTR.

Statistical analyses

All analyses were conducted using IBM SPSS version 27 software. In order to examine the relationship between the SIPAT and the 6MWT a linear regression was used. A logistic regression was used to determine if SIPAT scores predicted the presence of an ACR episode. To examine the relation between the SIPAT and both transplant behavioral health visits and readmissions poisson regressions were used. A cox proportional hazards model was used to determine if the SIPAT significantly predicted mortality. Sex, age, and LAS were included as covariates for all analyses except for the 6MWT which only included LAS since that measure is already adjusted for age and sex. For 6MWT we also ran a follow-up analysis that included the transplant hospitalization length as a covariate to help account for deconditioning and medical comorbidity.

For significant primary outcomes, follow-up analyses were conducted to examine if any of the SIPAT subscales (readiness level, social support system, psychological stability/ psychopathology, and lifestyle/effect of substance use) were significantly correlated with these outcomes. For these follow-up analyses, we used the same methods as the primary analyses.

Results

Demographics

Participants included 45 patients who underwent a lung transplant, had a pre-transplant SIPAT, and had at least 1 year of follow-up data. Demographic characteristics are presented in Table 1. Mean (SD) length of initial hospitalization was 48 (40.60) days and ranged from 12 to 186 days. Mean (SD) LAS score was 39.85 (11.26) and scores ranged from 32.37 to 88.51, indicating a wide range of severity. Mean (SD) SIPAT score was 15.36 (9.27) which falls in the good candidate range, and scores ranged from 2 (excellent candidate) to 38 (minimally acceptable) (Fig. 1). A total of 9 participants were in the excellent candidate category, 21 were in the good category, and 15 were in the minimally acceptable category. None of the patients were in the poor or high-risk candidate categories.

Table 1.

Demographics and study variables

	Mean (SD), Range
Age (years)	60.40 (9.42), 29–72
6 MWT	87.35 (15.61), 50.12–127.65
Number of readmissions	1.15 (1.68), 0–7
Number of transplant BH visits	2.11 (3.42), 0–13
	n (%)
ACR episode	28 (62.20)
Mortality	6 (13.30)
Male	29 (64.40)
Lung Disease
Idiopathic Pulmonary Fibrosis	23 (51.10)
Chronic Obstructive Pulmonary Disease	13 (28.90)
Other	8 (17.80)
Cystic Fibrosis	1 (2.20)
Race
Caucasian	43 (95.60)
Black/African American	2 (4.40)

6MWT (6 min walk test); BH (behavioral health); ACR (acute rejection episode)

Fig. 1.

Histogram of SIPAT total scores

A total of 13 participants had additional visits with transplant psychology prior to transplant in order to help optimize their candidacy. There was a significant difference between the SIPAT scores of patients who had additional pre-transplant visits (M = 23.31, SD = 7.83) and those who did not (M = 12.13, SD = 7.82), t(43) = -4.35, p < .05. There was a significant difference between the number of post-transplant behavioral health visits of patients who had additional pre-transplant visits (M = 4.08, SD = 4.48) and those who did not (M = 1.29 SD = 2.52), t(42) = -2.63, p < .05.

Descriptive statistics for the outcome variables are presented in Table 1. A total of 22 patients (48.89%) required psychology/psychiatry visits and 23 patients were readmitted at least 1 time (51.11%). A total of 28 patients (62.20%) had at least one ACR episode. A total of four patients died during their initial hospitalization and an additional two died within the first year of receiving a transplant. Mean (SD) number of days of survival for these patients post-transplant was 88.50 (90.46) and ranged from 1 to 237 days. These patients fell into the excellent (n = 1), good (n = 4), and minimally acceptable (n = 1) categories. The four patients who died during their initial hospitalization were excluded from the 6MWT analysis and from the readmission analysis. The one patient who died 1 day after his/her transplant was excluded from the transplant behavioral health visits analysis. Two additional patients did not complete the rehabilitation program and thus were excluded from the 6MWT analysis.

Primary analyses

For the primary analyses, we examined relations between the total SIPAT score and the transplant outcome variables (6MWT, transplant behavioral health visits, readmissions, presence of an ACR episode, and mortality). Results from the significant models are presented in Table 2. The regression for 6MWT was significant (F(2, 35) = 3.87, p = .030, R² = 0.18). The SIPAT was a significant predictor (t = -2.73, p = .010; Fig. 2) in this model. The SIPAT remained a significant predictor when controlling for the length of transplant hospitalization (t = -2.39, p = .023). The poisson regression for transplant behavioral health visits was also significant ((χ²(4) = 26.99, p < .001). The SIPAT was a significant predictor (χ²(1) = 18.15, p < .001). For every point increase in the SIPAT there was a 5.4% increase in the number of visits. The poisson regression for readmissions was significant (χ²(4) = 10.56, p = .032). The SIPAT was a significant predictor in this model (χ²(1) = 6.47, p = .011). For every point increase in the SIPAT there was a 5% increase in the number of readmissions.

Table 2.

Significant models using SIPAT total score as a predictor

6MWT
	B	95% CI	t	P value
SIPAT	-0.74	-1.23, -0.19	-2.73	0.010
LAS	-0.35	-0.91, 0.21	-1.27	0.21
Number of Readmissions
	B	95% CI	Wald χ2	P value
SIPAT	0.05	0.01, 0.09	6.47	0.011
LAS	0.04	0.01, 0.08	5.26	0.022
Age	0.03	-0.01, 0.07	2.45	0.12
Sex	0.83	0.17, 1.49	6.03	0.014
Number of Transplant BH Visits
	B	95% CI	Wald χ2	P value
SIPAT	0.05	0.03, 0.08	18.15	< 0.001
LAS	0.02	-0.01, 0.04	1.08	0.30
Age	-0.01	-0.03, 0.02	0.25	0.62
Sex	-0.19	-0.71, 0.33	0.53	0.47

Bolded values p < .05

6MWT (6 min walk test); LAS (lung allocation score); BH (behavioral health)

Fig. 2.

Scatterplot of SIPAT total score and 6MWT

The logistic regression using the SIPAT to predict the presence of an ACR episode was not significant (χ²(4) = 4.70, p = .32). The cox proportional hazards model did not demonstrate a significant relationship between the SIPAT and mortality (χ²(3) = 4.02, p = .26). We also ran the same analysis excluding the patients who died during their initial hospitalization, and it was also not significant (p > .10).

Follow-up analyses

For all significant models (6MWT, readmissions, and transplant behavioral health visits) we conducted follow-up analyses examining the relation between the 4 SIPAT subscales (readiness level, social support system, psychological stability/ psychopathology, and lifestyle/effect of substance use) and the outcome variable. For 6MWT none of the subscales were significant predictors (ps > 0.10). For readmissions, only the model including the readiness subscale was significant ((χ²(4) = 18.72, p < .001), and readiness was a significant predictor (p < .010). For every point increase in the readiness subscale there is a 12.5% increase in the number of readmissions. See Table 3 for significant models. For transplant behavioral health visits, the model including the psychopathology subscale ((χ²(4) = 24.78, p < .001) and the model including the substance use subscale ((χ²(4) = 32.99, p < .001) were significant. The subscales were significant predictors (ps < 0.010) of the number of visits. For every point increase in the substance use subscale there was a 14.6% increase in the number of visits. For every point increase in the psychopathology subscale there was an 11.6% increase in the number of visits.

Table 3.

Significant models using SIPAT subscales as a predictor

	B		95% CI	Wald χ2		P value
Number of Readmissions
SIPAT Readiness		0.12	0.06, 0.18	15.09	< 0.001
LAS		0.03	0.00, 0.06	3.89	0.05
Age		0.03	-0.01, 0.07	2.49	0.11
Sex		0.17	-0.48, 0.82	0.27	0.61
Number of Transplant BH Visits
SIPAT Psychopathology		0.11	0.06, 0.16	17.32	< 0.001
LAS		0.01	-0.02, 0.04	0.19	0.67
Age		-0.01	-0.03, 0.01	0.69	0.41
Sex		-0.24	-0.75, 0.26	0.89	0.35
Number of Transplant BH Visits
SIPAT Substance Use		0.14	0.08, 0.19	25.58	< 0.001
LAS		0.01	-0.02, 0.04	0.56	0.46
Age		-0.02	-0.05, 0.00	4.62	0.032
Sex		-0.02	-0.56, 0.52	0.01	0.94

Bolded values p < .05

6MWT (6 min walk test); LAS (lung allocation score); BH (behavioral health)

Discussion

While the SIPAT has been shown to correlate with medical and psychosocial transplant outcomes in several solid organ populations, limited work to date has focused on lung transplant recipients. In this study, we found that pre-transplant SIPAT total scores were significantly related to the number of readmissions, 6MWT, and the number of transplant behavioral health visits.

Readmissions after a lung transplant are associated with worse outcomes, including mortality, and are costly for the medical system (Mollberg et al., 2017; Simanovski & Ralph, 2020). In our follow-up analysis, the readiness subscale was a significant predictor of readmissions, with every point increase in the readiness subscale resulting in a 12.5% increase in the number of readmissions. The readiness subscale includes items assessing the patient’s understanding of their current medical situation, their understanding of transplant, their motivation for transplant, treatment adherence, and their ability to make lifestyle changes (e.g., dietary and exercise changes). Thus, individuals who are less motivated and adherent prior to transplant may be nonadherent with transplant care requirements, resulting in complications requiring hospitalization.

Physical rehabilitation after discharge is critical to help patients counteract the deconditioning effects of chronic illness and an extended hospital stay (Langer, 2015; Wickerson et al., 2016). Making adequate progress in rehabilitation can help maximize post-transplant quality of life. Results of the current study suggest that individuals who present with more psychosocial and behavioral risk factors before transplant do not make as much progress in post-transplant rehabilitation, which may impact their long-term quality of life. Psychosocial factors such as lack of motivation, anxiety, and inadequate social support may all limit progress. This analysis remained significant when controlling for LAS and length of initial hospitalization, suggesting that the relation was not driven solely by the severity of illness prior to transplant and by medical comorbidity/deconditioning after transplant. Follow-up analyses examining the SIPAT subscales were not significant. This suggests that the relation between the SIPAT and the 6MWT is not driven by any specific psychosocial domain, but rather by a combination of readiness, social support, psychological stability, and substance use.

While a lung transplant can significantly improve a recipient’s quality of life, it also can be a significant source of stress. Individuals must undergo a long recovery process and make significant lifestyle changes, such as adjusting to an extensive medication regimen and making dietary changes (Adegunsoye et al., 2017). Additionally, even after the initial recovery process, many individuals continue to experience ongoing symptoms and limitations due to medication side effects and transplant complications (de Vito Dabbs et al., 2003; Rodrigue et al., 2005; Thabut & Mal, 2017). While some individuals can appropriately cope with transplant-related stress, up to 30% of recipients experience anxiety and depression within the first few years (Dew et al., 2012). Depression is associated with an elevated risk for transplant complications including mortality (Rosenberger et al., 2017; Smith et al., 2016).

We found that for every point increase in the SIPAT there was a 5.4% increase in the number of behavioral health visits. Thus, these individuals with more psychosocial risk factors may be less resilient in the face of transplant-related stress and require more psychosocial intervention. Transplant behavioral health visits indicate acute issues that directly impact a patient’s ability to progress medically. For example, individuals may experience significant anxiety which limits their participation in physical therapy, which is a barrier to being discharged. Therefore, individuals with more psychosocial risk factors prior to transplant appear to be more likely to develop problematic behaviors after transplant that interfere with their medical care. These individuals require more support and resources after transplant. Careful pre-transplant psychosocial evaluation provides an opportunity to identify these individuals, and thus proactively monitor them and provide additional support throughout the transplant process. This may allow for psychosocial adjustment problems to be caught earlier, and thus reduce the potential for significant psychiatric decompensation.

Follow-up analyses demonstrated that the psychological stability and psychopathology subscale, as well as the lifestyle and effect of substance use subscale, were significant predictors of the number of visits. We found that, for every point increase in the psychopathology subscale, there was an 11.6% increase in the number of behavioral health visits. Lung transplant candidates have been shown to have an elevated risk of psychopathology, with one study finding a 41.5% current prevalence for a psychiatric disorder during the evaluation process, and 61% lifetime prevalence (Parekh et al., 2003; Søyseth et al., 2016). Individuals with a more significant psychopathology history are more likely to need psychosocial support after a transplant.

We also found that for every point increase in the substance use subscale there was a 14.6% increase in the number of behavioral health visits. The limited literature on substance use in lung transplant recipients has mostly focused on a return to smoking cigarettes, with estimates ranging from 0 to 15% (Evon et al., 2005; Zmeskal et al., 2016). Substance use also often has other psychiatric comorbidities and may reflect inadequate coping in response to stressors, including adjustment to transplant, and thus a need for mental health follow-up. Additional work is needed to better understand the relation between pre-transplant substance use history and post-transplant substance use and psychopathology.

The SIPAT was not a significant predictor of the presence of an ACR episode. This is in contrast with a prior study that included lung transplant recipients and found a significant relation with the number of ACR episodes (Maldonado et al., 2015). Within this sample over half of the patients had a rejection episode, which is consistent with prior studies (Thabut & Mal, 2017). Lung transplant recipients experience the highest rates of rejection among solid organ recipients (Martinu et al., 2009; Thabut & Mal, 2017). Given that over half of the recipients experience an ACR rejection within the first year, this may be driven more by medical factors than by behavioral factors. Additionally, prior studies have indicated high adherence rates during the first year after a lung transplant (Bosma et al., 2011). Future studies may also want to examine chronic rejection.

The SIPAT was also not a significant predictor of mortality. This is consistent with the findings of a prior study that included lung transplant recipients (Maldonado et al., 2015). This may have been an artifact of our relatively small sample size, with only 6 patients dying over the 1-year study period. Four of these patients died during the initial admission, which suggests that their death may be driven more by medical factors than psychosocial factors. A survival analysis only including patients who died after the initial hospitalization was also not significant. Both analyses were likely not sufficiently powered to detect an effect. Future studies should examine this relation during a longer follow-up period.

There are several additional reasons why we may not have found a significant relation between the SIPAT and either presence of ACR episodes or mortality. For one, we did not have any patients with SIPAT scores in the poor or high-risk candidate range. Thus, it may be that the individuals whose psychosocial risk profiles would put them at an elevated risk for poor medical outcomes were not included in this study. Additionally, it may be that access to behavioral health visits helped mitigate some of the psychosocial risk factors that may have put patients at an elevated risk for poor medical outcomes.

Limitations and future directions

One limitation of this study is the relatively small sample size at a single transplant center. Given the small sample size, it was not possible to conduct subsample analyses to determine the extent to which findings may vary based on clinical and demographic variables. Additionally, the relative homogeneity of the current sample may limit the generalizability of the current findings. This remains a relatively large sample size for lung transplant recipients. Future studies should aim to replicate these findings in a large multi-site study. Additionally, there may have been sample selection bias in this study, since the SIPAT was used to inform listing decisions. This may have contributed to patients with SIPAT scores in the poor and high-risk categories not being present in this sample thereby limiting our ability to detect significant relations. Future studies could consider having someone administer the SIPAT who is not part of the candidate selection process. Studies should also consider including patients with a wider range of SIPAT scores. Additionally, patients with higher SIPAT scores were more likely to have additional follow-up visits with transplant psychology prior to transplant to optimize their candidacy which may have resulted in a change in their SIPAT scores. The SIPAT was not readministered for these patients prior to transplant. As such it is unclear the extent to which this might have impacted the current results. Future studies should examine if intervention prior to transplant results in a reduction in SIPAT score and if this improves post-transplant outcomes.

Another limitation is that post-transplant patients were not routinely screened for psychological complications, and as such, we may have underestimated the post-transplant mental health needs. While the number of behavioral health visits captures post-transplant psychiatric decompensation, it does not provide fine-grained information on the type of psychiatric complications. It is recommended that future studies extract additional information about the specific symptoms endorsed during the visits and the nature of the interventions. Additionally, while the transplant psychology team was typically able to meet the short-term needs of post-transplant recipients, it is a relatively small team, and as such access may have impacted the number of behavioral health visits. In addition, individuals with higher SIPAT scores before transplant were more likely to have additional visits with transplant psychology both before and after transplant. It is unclear if this is due to these patients being higher risk and thus needing more support, to the transplant team following these patients more closely due to their higher scores, or a combination of the two. Future studies should examine why patients are selected for follow-up visits by behavioral health.

In this study period, we had a small number of deaths, which may have limited the ability of the SIPAT to predict mortality due to a lack of sufficient power. Future studies should utilize a longer follow-up period to have a larger number of cases to predict. As this was a retrospective study using data provided over the course of standard care, it is possible that pre-transplant predictions of patients’ psychological vulnerability may have influenced requests for post-transplant follow-up among transplant team members. We also did not examine the impact of medical confounders such as high-risk graft donors, and future studies should take this into account.

Conclusions

The findings of the current study add to our understanding of the utility of careful psychosocial evaluation of transplant candidates. The COVID-19 pandemic has brought into even sharper focus the need to continue to optimize psychosocial support for lung transplant candidates and recipients. This pandemic has resulted in a surge of individuals who sustained a significant lung injury and may be candidates for a lung transplant (Walter, 2021). These transplants may be higher risk due to the uncertainty regarding the prognosis for post-COVID fibrosis lung transplant recipients and the abbreviated evaluation period for some patients with severe acute respiratory distress (King et al., 2022). As such, it is even more critical that future studies strive to continue to explore how to identify individuals who may need additional treatment and support throughout the transplant process.

Authors’ contributions

All authors contributed to the study conception and design. All authors read and approved the final manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

data is not available.

Code availability

code is not available.

Declarations

Conflict of interest

The authors do not have any competing interests to disclose.

Research involving human participants and/or animals: This research was conducted in accordance with the Helsinki Declaration as revised in 2008.

Informed consent

All individuals provided written informed consent to have their clinical data included in research projects.

Consent to participate

all individuals provided informed written consent.

Ethics approval

This study was approved by the IRB and was conducted in accordance with the Helsinki Declaration as revised in 2008.