Curricular Self‐management for patients on ventricular assist device support decreases depression: A multicenter randomized controlled trial
INTRODUCTION Significant advancements in ventricular assist device (VAD) therapies have been documented emphasizing improved survival rates , and enhanced quality of life (QoL) for patients with advanced heart failure. , , , , However, life expectancy and QoL can be hampered by device‐related adverse events, namely thromboembolic neurological events, driveline exit site infections, and major bleeding events. Psychological symptoms like anxiety and depression have been shown to be elevated in patients on VAD support. , Evidence‐based self‐management education is essential in order to prepare patients and caregivers for their 24/7 tasks and responsibilities. , , , The concept of self‐management was introduced by Lorig and Holman in 2003: it is characterized as an individual's ability to manage the symptoms, treatment, physical and psychological consequences and lifestyle changes inherent in living with a chronic condition. For individuals with a chronic condition, this includes the ability to monitor his/her own condition and manage behavioral, cognitive, and emotional responses inherent to that condition. For patients on VAD support, a self‐management model was developed that includes the following three components: managing the therapeutic regimen; managing emotions and psychosocial adjustment; and managing new life roles. In patients on VAD support, effectively managing the therapeutic regimen is key to improved functioning in daily life and includes, but is not limited to device handling, self‐monitoring, adhering to polypharmacy, symptom and side‐effect detection and management, infection prevention, and wound management. Component two targets cognitive, emotional, and behavioral responses to maintain a satisfactory quality of life while being on VAD support, component three addresses life roles and their adjustment. Howell and associates published a call to action which emphasized that successful self‐management requires (i) a willing and able patient encouraged to assume responsibility; (ii) a family member or caregiver providing a social network instrumental in supporting patient efforts; and (iii) a collaborative relationship between patient and provider. In order to meet these requirements, it is necessary to develop and implement evidence‐based self‐management programs. Against this background, the three‐phase study “Improved Self‐management for Patients on Ventricular Assist Device (VAD) Support (SELMA)” was developed. The aim of phase 1 of the study was to assess the self‐management needs of patients on VAD support. , , , In phase 2, the intervention was prepared by a thorough scoping review, which informed the development and revision of a modular, evidence‐based curriculum to improve the self‐management for patients on VAD support. The objective of this study in phase 3 was to implement and evaluate the curriculum in a randomized controlled trial (RCT). This study (phase 3) aimed to promote patient self‐management and thereby (1) reduce VAD‐specific adverse events (thromboembolic neurological events, driveline exit site infections, bleeding events), associated rehospitalizations, and mortality (combined primary endpoint); and (2) improve patient‐reported outcomes including anxiety and depression, quality of life, and social support (secondary outcomes) in the first year after VAD implantation.   METHODS This study was part of the three‐phase national multi‐center SELMA study for self‐management for patients on VAD support (NCT04526964); a detailed description can be found in the published study protocol. The protocol was approved by the institutional review board of the host institution (IRB‐No. 41/20); the participating centers' review boards confirmed this approval before initiation of the data collection process. In line with ethical considerations, monitoring was an integral component of this study. An independent, neutral professional from the clinical trials unit of the host institution, who was not a member of the study group, incorporated monitoring. All study procedures were performed in concordance with the Helsinki declaration and the European data protection regulation. Results were reported in accordance with the CONSORT guidelines. 2.1 Study design This study used a non‐blinded, block‐randomized controlled design, allocation ratio 1:1, to determine superiority of outcomes for those randomized to the multistage intervention (Figure ). Data were collected pre‐ and post‐intervention along with two follow‐up assessments at 3 months after intervention completion, and 12 months after VAD implantation (Figure ). 2.2 Setting and participants This study was conducted at four established university heart centers in Germany. Patient recruitment considered center‐related volumes and recruited study participants simultaneously. Authorized, trained personnel in the participating centers performed recruitment. Stable in‐patients following VAD implantation were considered for this study. Predefined inclusion and exclusion criteria included age 18 or older, cognitive and linguistic ability to participate in the study, written informed consent, and stable postoperative condition defined as transfer of patient from the intensive care unit to step‐down unit, as well as planned follow‐up at the implanting heart center. The study was impacted by the Covid‐19 pandemic. Beginning and end of the patient recruitment period were delayed in an effort to reduce recruitment bias due to the pandemic since implant activities were significantly reduced or even paused for elective procedures at all participating sites. No other changes were made to the methods after trial commencement. 2.3 Power and drop out The study was designed with a power of 80% and alpha level of 0.05 to detect a change in the combined primary endpoint (VAD‐specific adverse event rates [thromboembolic neurological events, driveline exit site infections, and bleeding events], associated re‐hospitalizations and mortality) from 53% to 30% within in the first year after VAD implantation. A non‐response rate of 10% and a dropout rate of 20% within a year was built into the model. Due to the Covid‐19 pandemic and subsequent reduced implant activities, 70 patients per group could be recruited within the study period. Power calculation took into account gender and center‐based implant activities. With a power of 72.3% and a two‐sided significance level of <0.05, 70 participants in the intervention and control groups were required to detect statistically significant differences. Based on reports from comparable previous studies, , a refusal rate of 10% and a dropout rate of 20% were anticipated. 2.4 Randomization Patients were consecutively recruited. Randomization was based on gender (80% male) and implantation volume of the centers (35% centers with high, 20% with medium, and 10% with low implantation volume) using a stratified block randomization procedure. This procedure is intended to balance the stability of participants in the intervention and control groups across strata. Randomization for each stratum was performed using R (block‐randomization). To avoid a selection bias, concealed allocation was performed, in which the order was hidden until the interventions were allocated: Block‐randomized, sequentially numbered lists were prepared by a study statistician and submitted to the study coordination team. Two team members retained the list, and study site recruiters received the sequential randomization code number to assign a potential study participant to either the intervention or the control group. 2.5 Intervention The intervention lasted 3 months per consecutive patient. Intervention content was based on a thorough scoping review assessing self‐management areas for support for VAD patients. From that, an evidence‐based, multi‐modular curriculum was developed (Table ). Caregivers were explicitly invited and encouraged to participate. 2.6 Self‐management curriculum and modules Professionals involved in the intervention were uniformly trained to teach the curriculum content in a train‐the‐trainer workshop held prior to the initiation of the intervention period. Patients in the intervention group were provided with individualized VAD‐specific self‐management training sessions utilizing a modular curriculum and provided by multiple trained professionals as members of the VAD post‐implant follow‐up teams. Beginning during their post‐implant hospitalization, training was initiated in the step‐down unit following VAD implant surgery, and continued in the outpatient setting to refresh and maintain self‐management skills on topics agreed upon between the VAD training staff, the patient, and caregiver. During the outpatient period, content was delivered via communication channels that the individual preferred (e.g., face‐to‐face, phone, email, video conference) and which were appropriate to the topic, for example, wound management might be best delivered via a videoconference line (e.g., FaceTime). Intervention content and didactics were individualized and selected from a potpourri of interventional strategies designed to meet the needs of the individual patient, and, where possible, of their caregivers. The intervention was targeted to patients following VAD implantation. However, wherever and whenever possible, caregivers were invited to participate in all sessions. During the Covid‐19 pandemic, caregivers experienced hospital restrictions on visiting their family member and/ or participating in the SELMA sessions. Proof of sufficient vaccination was required at all participating sites and for all visiting caregivers. In some cases, written permissions were needed to allow caregivers to enter the clinic and participate in those sessions. The SELMA curriculum was developed based on a synthesis of the current evidence. The curriculum consisted of 11 modules aimed at providing knowledge, skills, and competencies to VAD patients and preferably their caregivers (Table ). A trained multi‐professional VAD team delivered the modules with each module using different didactic feedback and evaluation elements. The time frame for each topic and each patient varied according to the cognitive and emotional capabilities per patient and session between 5 and 45 min. A recommended maximum time frame per patient and session was depicted in the last column in Table . However, healthcare professionals were flexible in shortening or expanding the recommended time frame according to the patients or family member's needs. Repetitions were estimated within the same time frame as the initial sessions. Repetitions were performed on a patient‐by‐patient basis and always stated the introductory question “what stood out for you personally from our last session about xy….” A brief assessment on knowledge and skills delivered was performed and eventually repeated, corrected or confirmed. All curriculum content was also offered to patients in the intervention group via a specially developed Selma App as a supplement to the self‐management intervention. Multiple opportunities to store and monitor data on this App were provided. For more details, please see the SELMA study protocol. 2.7 Usual care (control group) Care as usual for both groups contained the standardized VAD‐specific education as the current standard of care delivered by trained professionals at each participating site. Patients in the control group were offered to use the app as well as paper‐based content of the curriculum after completion of the study. 2.8 Outcomes, instruments and measures Instruments and measurement methods were used in accordance with the updated U.S. Department of Health and Human Services Food and Drug Administration report. Following written informed consent, data were collected through standardized patient‐reported outcome (PRO) measures at the measurement time points shown in Table . In addition, clinical data were abstracted from the patient records and entered into electronic case report forms by trained staff at the participating sides. Demographic measures were collected by patient self‐reports. Instruments and outcome measures for this study are shown in Table . The baseline assessment at T0 was performed after a patient had been transferred from the ICU to the step‐down unit post implant, which allowed a pre‐intervention status assessment for a selected number of instruments. Please note that not all questionnaires were relevant at this time point, for example, the Selma‐VAD questionnaire was not relevant yet, items asked about handling the device in the home setting. Thus, for the instruments (Selma‐VAD, QoLVAD, and FSoZu‐K14 ) we were not able to collect baseline assessments. Those questionnaires were considered from T1 onwards (Table ). More specifically, only three preselected items of the QoLVAD questionnaire were collected as T0, patients were not able to answer all items of this instrument. All instruments were standardized and available in a psychometrically tested German version. A paper‐and‐pencil format was chosen considering the patient population studied. 2.9 Statistical methods Statistical analyses were performed using the programs R 4.3.2 and SAS. A thorough data quality review was performed, which included validation of data ranges, identification of missing values, assessment of data structure, and detection of errors. Descriptive and univariate analyses were calculated to characterize the sample and relevant demographic and clinical variables. Group comparisons of baseline characteristics were conducted using Fisher's Exact Test for categorical variables and the t‐test for independent samples for continuous variables. All analyses were conducted following the intention‐to‐treat (ITT) principle. All participants were analyzed as originally randomized. All tests performed were two‐sided, and the significance level was set at ≤0.05 a priori. The concept self‐management (Selma‐VAD ) was analyzed using mixed regression models, with independent variables being time points (T1‐T3), gender, and the group indicator (IG or CG) with random intercepts for each patient and center. However, as self‐management was assessable after training at T1 and the baseline score (T0) could not be included as a measurement time point; it was not adjusted for in the model. The concept social support (FSoZu‐K14 ) necessitated to apply the same approach: no baseline score was measurable (patients were not able to answer this questionnaire while being in the hospital at T0). The calculation indicates a direction in the development of patients' self‐management skills. For the primary outcome, a combined endpoint was assessed, which encompassed VAD‐specific adverse events (thromboembolic neurological events, bleeding events, and driveline exit site infections), associated re‐hospitalizations and mortality in the first year after VAD implantation. The analysis of this combined endpoint utilized a logistic regression with a random intercept for gender and center. Furthermore, a sensitivity analysis was conducted using a Cox regression for interval‐censored data, considering the independent variables of group, gender, and center. The analysis was performed with 100 bootstrap samples to estimate standard errors. A second primary analysis focused on calculating rehospitalization rates during the 3‐month intervention and the 9‐month follow‐up per participant. This was accomplished through competing risk analysis, where death was considered a competing risk for rehospitalization. A multi‐stage model was employed to study the stages of implantation (1), rehospitalization (2), and death (3), along with their potential transitions. For the secondary outcomes, assessed endpoints were self‐management, anxiety, depression, social support, and quality of life. For quality of life, the closing item of the QoLVAD instrument was used (Item 46. On a scale of 1–10 (10 being the best, 1 being the worst), my overall quality of life corresponds to ) as this item was collected at all four time points. Descriptive examination and mixed linear regression models were performed. These models included a nested random intercept for patients and center. Independent variables considered were the time points, the respective baseline score, gender, and the group indicator, with a random intercept for each patient and center. Dependent variable was the change from the respective baseline score if available. For QoL (QoLVAD i‐46 ) and social support (FSoZu‐K14 ) a cumulative link mixed model with logit link and equidistant threshold was performed instead of linear regression, to take into account the non‐linear nature of these variables.   Study design This study used a non‐blinded, block‐randomized controlled design, allocation ratio 1:1, to determine superiority of outcomes for those randomized to the multistage intervention (Figure ). Data were collected pre‐ and post‐intervention along with two follow‐up assessments at 3 months after intervention completion, and 12 months after VAD implantation (Figure ).   Setting and participants This study was conducted at four established university heart centers in Germany. Patient recruitment considered center‐related volumes and recruited study participants simultaneously. Authorized, trained personnel in the participating centers performed recruitment. Stable in‐patients following VAD implantation were considered for this study. Predefined inclusion and exclusion criteria included age 18 or older, cognitive and linguistic ability to participate in the study, written informed consent, and stable postoperative condition defined as transfer of patient from the intensive care unit to step‐down unit, as well as planned follow‐up at the implanting heart center. The study was impacted by the Covid‐19 pandemic. Beginning and end of the patient recruitment period were delayed in an effort to reduce recruitment bias due to the pandemic since implant activities were significantly reduced or even paused for elective procedures at all participating sites. No other changes were made to the methods after trial commencement.   Power and drop out The study was designed with a power of 80% and alpha level of 0.05 to detect a change in the combined primary endpoint (VAD‐specific adverse event rates [thromboembolic neurological events, driveline exit site infections, and bleeding events], associated re‐hospitalizations and mortality) from 53% to 30% within in the first year after VAD implantation. A non‐response rate of 10% and a dropout rate of 20% within a year was built into the model. Due to the Covid‐19 pandemic and subsequent reduced implant activities, 70 patients per group could be recruited within the study period. Power calculation took into account gender and center‐based implant activities. With a power of 72.3% and a two‐sided significance level of <0.05, 70 participants in the intervention and control groups were required to detect statistically significant differences. Based on reports from comparable previous studies, , a refusal rate of 10% and a dropout rate of 20% were anticipated.   Randomization Patients were consecutively recruited. Randomization was based on gender (80% male) and implantation volume of the centers (35% centers with high, 20% with medium, and 10% with low implantation volume) using a stratified block randomization procedure. This procedure is intended to balance the stability of participants in the intervention and control groups across strata. Randomization for each stratum was performed using R (block‐randomization). To avoid a selection bias, concealed allocation was performed, in which the order was hidden until the interventions were allocated: Block‐randomized, sequentially numbered lists were prepared by a study statistician and submitted to the study coordination team. Two team members retained the list, and study site recruiters received the sequential randomization code number to assign a potential study participant to either the intervention or the control group.   Intervention The intervention lasted 3 months per consecutive patient. Intervention content was based on a thorough scoping review assessing self‐management areas for support for VAD patients. From that, an evidence‐based, multi‐modular curriculum was developed (Table ). Caregivers were explicitly invited and encouraged to participate.   Self‐management curriculum and modules Professionals involved in the intervention were uniformly trained to teach the curriculum content in a train‐the‐trainer workshop held prior to the initiation of the intervention period. Patients in the intervention group were provided with individualized VAD‐specific self‐management training sessions utilizing a modular curriculum and provided by multiple trained professionals as members of the VAD post‐implant follow‐up teams. Beginning during their post‐implant hospitalization, training was initiated in the step‐down unit following VAD implant surgery, and continued in the outpatient setting to refresh and maintain self‐management skills on topics agreed upon between the VAD training staff, the patient, and caregiver. During the outpatient period, content was delivered via communication channels that the individual preferred (e.g., face‐to‐face, phone, email, video conference) and which were appropriate to the topic, for example, wound management might be best delivered via a videoconference line (e.g., FaceTime). Intervention content and didactics were individualized and selected from a potpourri of interventional strategies designed to meet the needs of the individual patient, and, where possible, of their caregivers. The intervention was targeted to patients following VAD implantation. However, wherever and whenever possible, caregivers were invited to participate in all sessions. During the Covid‐19 pandemic, caregivers experienced hospital restrictions on visiting their family member and/ or participating in the SELMA sessions. Proof of sufficient vaccination was required at all participating sites and for all visiting caregivers. In some cases, written permissions were needed to allow caregivers to enter the clinic and participate in those sessions. The SELMA curriculum was developed based on a synthesis of the current evidence. The curriculum consisted of 11 modules aimed at providing knowledge, skills, and competencies to VAD patients and preferably their caregivers (Table ). A trained multi‐professional VAD team delivered the modules with each module using different didactic feedback and evaluation elements. The time frame for each topic and each patient varied according to the cognitive and emotional capabilities per patient and session between 5 and 45 min. A recommended maximum time frame per patient and session was depicted in the last column in Table . However, healthcare professionals were flexible in shortening or expanding the recommended time frame according to the patients or family member's needs. Repetitions were estimated within the same time frame as the initial sessions. Repetitions were performed on a patient‐by‐patient basis and always stated the introductory question “what stood out for you personally from our last session about xy….” A brief assessment on knowledge and skills delivered was performed and eventually repeated, corrected or confirmed. All curriculum content was also offered to patients in the intervention group via a specially developed Selma App as a supplement to the self‐management intervention. Multiple opportunities to store and monitor data on this App were provided. For more details, please see the SELMA study protocol.   Usual care (control group) Care as usual for both groups contained the standardized VAD‐specific education as the current standard of care delivered by trained professionals at each participating site. Patients in the control group were offered to use the app as well as paper‐based content of the curriculum after completion of the study.   Outcomes, instruments and measures Instruments and measurement methods were used in accordance with the updated U.S. Department of Health and Human Services Food and Drug Administration report. Following written informed consent, data were collected through standardized patient‐reported outcome (PRO) measures at the measurement time points shown in Table . In addition, clinical data were abstracted from the patient records and entered into electronic case report forms by trained staff at the participating sides. Demographic measures were collected by patient self‐reports. Instruments and outcome measures for this study are shown in Table . The baseline assessment at T0 was performed after a patient had been transferred from the ICU to the step‐down unit post implant, which allowed a pre‐intervention status assessment for a selected number of instruments. Please note that not all questionnaires were relevant at this time point, for example, the Selma‐VAD questionnaire was not relevant yet, items asked about handling the device in the home setting. Thus, for the instruments (Selma‐VAD, QoLVAD, and FSoZu‐K14 ) we were not able to collect baseline assessments. Those questionnaires were considered from T1 onwards (Table ). More specifically, only three preselected items of the QoLVAD questionnaire were collected as T0, patients were not able to answer all items of this instrument. All instruments were standardized and available in a psychometrically tested German version. A paper‐and‐pencil format was chosen considering the patient population studied.   Statistical methods Statistical analyses were performed using the programs R 4.3.2 and SAS. A thorough data quality review was performed, which included validation of data ranges, identification of missing values, assessment of data structure, and detection of errors. Descriptive and univariate analyses were calculated to characterize the sample and relevant demographic and clinical variables. Group comparisons of baseline characteristics were conducted using Fisher's Exact Test for categorical variables and the t‐test for independent samples for continuous variables. All analyses were conducted following the intention‐to‐treat (ITT) principle. All participants were analyzed as originally randomized. All tests performed were two‐sided, and the significance level was set at ≤0.05 a priori. The concept self‐management (Selma‐VAD ) was analyzed using mixed regression models, with independent variables being time points (T1‐T3), gender, and the group indicator (IG or CG) with random intercepts for each patient and center. However, as self‐management was assessable after training at T1 and the baseline score (T0) could not be included as a measurement time point; it was not adjusted for in the model. The concept social support (FSoZu‐K14 ) necessitated to apply the same approach: no baseline score was measurable (patients were not able to answer this questionnaire while being in the hospital at T0). The calculation indicates a direction in the development of patients' self‐management skills. For the primary outcome, a combined endpoint was assessed, which encompassed VAD‐specific adverse events (thromboembolic neurological events, bleeding events, and driveline exit site infections), associated re‐hospitalizations and mortality in the first year after VAD implantation. The analysis of this combined endpoint utilized a logistic regression with a random intercept for gender and center. Furthermore, a sensitivity analysis was conducted using a Cox regression for interval‐censored data, considering the independent variables of group, gender, and center. The analysis was performed with 100 bootstrap samples to estimate standard errors. A second primary analysis focused on calculating rehospitalization rates during the 3‐month intervention and the 9‐month follow‐up per participant. This was accomplished through competing risk analysis, where death was considered a competing risk for rehospitalization. A multi‐stage model was employed to study the stages of implantation (1), rehospitalization (2), and death (3), along with their potential transitions. For the secondary outcomes, assessed endpoints were self‐management, anxiety, depression, social support, and quality of life. For quality of life, the closing item of the QoLVAD instrument was used (Item 46. On a scale of 1–10 (10 being the best, 1 being the worst), my overall quality of life corresponds to ) as this item was collected at all four time points. Descriptive examination and mixed linear regression models were performed. These models included a nested random intercept for patients and center. Independent variables considered were the time points, the respective baseline score, gender, and the group indicator, with a random intercept for each patient and center. Dependent variable was the change from the respective baseline score if available. For QoL (QoLVAD i‐46 ) and social support (FSoZu‐K14 ) a cumulative link mixed model with logit link and equidistant threshold was performed instead of linear regression, to take into account the non‐linear nature of these variables.   RESULTS 3.1 Participants A total of 199 patients were assessed for eligibility, 59 individuals were excluded, and hence, the study included 140 patients who were randomly assigned, 70 patients in the intervention group, and 70 patients in the control group. With a withdrawal (IG 2.8%; CG 8.5%) and an event (IG 20.0%; CG 22.8%) overall rate of 27.1%, the sample size at final follow‐up (T3) consisted of 102 participants, with 54 in the intervention group and 48 in the control group. A detailed overview of the recruiting process and follow‐up process was outlined in the modified CONSORT study flow diagram in Figure . Adverse events at measurement points are outlined. Sample characteristics at baseline (T0) are presented in Table . 3.2 Self‐management Self‐management skills to handle the VAD and the implant‐related therapeutic regimen were assessed and revealed a slight increase for both groups over time. Although the intervention group exhibited numerically higher values for the self‐management concept (Selma‐VAD Score: 0–100, higher values indicate better perceived self‐management) at time points T1–T3 (Table ), the regression analysis did not reveal statistically significant differences (Estimate 1.79; 95% CI −2.03 to 5.60; p = 0.357). 3.3 Primary outcome (combined endpoint): Event free follow‐up, re‐hospitalizations, and death For the primary endpoint, at visit T2 (3 months after VAD implant), 24 patients had dropped out of the study or had missing data. With 62 and 54 patients per group left at T2, we reached a power of 71.7% to detect the change in combined primary endpoint from 53% to 30%. In the frequency of adverse events (thromboembolic neurological events, driveline exit site infections, bleeding, re‐hospitalizations, and death) among the investigated groups, no statistically significant differences were observed at three different time points: T1, T2, and T3. The analysis, utilizing logistic regression for the combined endpoint, considering a random intercept for the center, resulted in an odds ratio of 0.99 (95% CI 0.47–2.10; p = 0.984) at time point T3. Furthermore, a sensitivity analysis revealed no significant differences between the groups in terms of the adverse event or death rate (HR 1.11; 95% CI 0.59–2.08; p = 0.743). The intervention did not have a significant impact on the rehospitalization rate when considering only patients alive (cause‐specific HR 0.81, 95% CI 0.47–1.38, p = 0.41; adjusted for gender and random intercept for center). Additionally, there was no detectable effect of the intervention on the mortality rate of patients hospitalized considering rehospitalization as competing event (cause‐specific HR 0.81, 95% CI 0.23–2.82; p = 0.740). When considering the influence on rehospitalization and death simultaneously using the Fine‐Gray model, no significant effect of the intervention on the rehospitalization rate could be detected (sub‐distribution HR 0.80; 95% CI 0.48–1.36; p = 0.41, Figure ). Finally, a sub‐analysis for age dichotomized along the median (≤60 vs. >60 years), considering a random intercept for center, revealed an odds ratio of 0.98 (95% CI 0.91–1.06; p = 0.684) for the combined primary endpoint. 3.4 Secondary outcomes: Depression, anxiety, social support perceptions, and quality of life The intervention led to significant results concerning the outcome of depression symptoms, as measured by the HADS. At the beginning of the intervention, both groups reported similar levels of depression symptoms. However, over time, the intervention group showed a significant average decrease in 1.8 points (95% CI −2.17 to −0.18, p = 0.021) compared to the control group (Figure ). A significant effect was outlined for gender (male) (OR 1.23; 95% CI −0.02 to 2.49; p = 0.05), when corrected for center effects. Furthermore, there was a trend toward lower anxiety levels (HADS) in the intervention group compared to the control group at the end of the intervention (OR −0.69; 95% CI −1.61 to 0.23; p = 0.141) (Figure ). In addition, anxiety levels showed clinically significant reductions for the intervention group between T0 and T3 (IG 51.9%; CG 40.7%), whereas clinically significant increases appeared for the same time frame for 11.1% control group patients, but for only one IG patient. Regarding depression levels, similar clinically significant reductions were present between T0 and T3 (IG 57.7%; CG 46.2%), and a clinically significant increase in depression levels appeared again for 11.5% control group patients, but for only one IG patient. Patients in the intervention versus control group reported comparable scores with respect to their QoL (QoLVAD, item 46, Figure ), and their social support compared to those in the control group (Figure ).   Participants A total of 199 patients were assessed for eligibility, 59 individuals were excluded, and hence, the study included 140 patients who were randomly assigned, 70 patients in the intervention group, and 70 patients in the control group. With a withdrawal (IG 2.8%; CG 8.5%) and an event (IG 20.0%; CG 22.8%) overall rate of 27.1%, the sample size at final follow‐up (T3) consisted of 102 participants, with 54 in the intervention group and 48 in the control group. A detailed overview of the recruiting process and follow‐up process was outlined in the modified CONSORT study flow diagram in Figure . Adverse events at measurement points are outlined. Sample characteristics at baseline (T0) are presented in Table .   Self‐management Self‐management skills to handle the VAD and the implant‐related therapeutic regimen were assessed and revealed a slight increase for both groups over time. Although the intervention group exhibited numerically higher values for the self‐management concept (Selma‐VAD Score: 0–100, higher values indicate better perceived self‐management) at time points T1–T3 (Table ), the regression analysis did not reveal statistically significant differences (Estimate 1.79; 95% CI −2.03 to 5.60; p = 0.357).   Primary outcome (combined endpoint): Event free follow‐up, re‐hospitalizations, and death For the primary endpoint, at visit T2 (3 months after VAD implant), 24 patients had dropped out of the study or had missing data. With 62 and 54 patients per group left at T2, we reached a power of 71.7% to detect the change in combined primary endpoint from 53% to 30%. In the frequency of adverse events (thromboembolic neurological events, driveline exit site infections, bleeding, re‐hospitalizations, and death) among the investigated groups, no statistically significant differences were observed at three different time points: T1, T2, and T3. The analysis, utilizing logistic regression for the combined endpoint, considering a random intercept for the center, resulted in an odds ratio of 0.99 (95% CI 0.47–2.10; p = 0.984) at time point T3. Furthermore, a sensitivity analysis revealed no significant differences between the groups in terms of the adverse event or death rate (HR 1.11; 95% CI 0.59–2.08; p = 0.743). The intervention did not have a significant impact on the rehospitalization rate when considering only patients alive (cause‐specific HR 0.81, 95% CI 0.47–1.38, p = 0.41; adjusted for gender and random intercept for center). Additionally, there was no detectable effect of the intervention on the mortality rate of patients hospitalized considering rehospitalization as competing event (cause‐specific HR 0.81, 95% CI 0.23–2.82; p = 0.740). When considering the influence on rehospitalization and death simultaneously using the Fine‐Gray model, no significant effect of the intervention on the rehospitalization rate could be detected (sub‐distribution HR 0.80; 95% CI 0.48–1.36; p = 0.41, Figure ). Finally, a sub‐analysis for age dichotomized along the median (≤60 vs. >60 years), considering a random intercept for center, revealed an odds ratio of 0.98 (95% CI 0.91–1.06; p = 0.684) for the combined primary endpoint.   Secondary outcomes: Depression, anxiety, social support perceptions, and quality of life The intervention led to significant results concerning the outcome of depression symptoms, as measured by the HADS. At the beginning of the intervention, both groups reported similar levels of depression symptoms. However, over time, the intervention group showed a significant average decrease in 1.8 points (95% CI −2.17 to −0.18, p = 0.021) compared to the control group (Figure ). A significant effect was outlined for gender (male) (OR 1.23; 95% CI −0.02 to 2.49; p = 0.05), when corrected for center effects. Furthermore, there was a trend toward lower anxiety levels (HADS) in the intervention group compared to the control group at the end of the intervention (OR −0.69; 95% CI −1.61 to 0.23; p = 0.141) (Figure ). In addition, anxiety levels showed clinically significant reductions for the intervention group between T0 and T3 (IG 51.9%; CG 40.7%), whereas clinically significant increases appeared for the same time frame for 11.1% control group patients, but for only one IG patient. Regarding depression levels, similar clinically significant reductions were present between T0 and T3 (IG 57.7%; CG 46.2%), and a clinically significant increase in depression levels appeared again for 11.5% control group patients, but for only one IG patient. Patients in the intervention versus control group reported comparable scores with respect to their QoL (QoLVAD, item 46, Figure ), and their social support compared to those in the control group (Figure ).   DISCUSSION Our study was the first to deliver a comprehensive, evidence‐based, multi‐module self‐management intervention for patients on continuous flow VAD support. The study was performed during and was impacted by the Covid‐19 pandemic resulting in a decreased power of 72%. Despite all potentially depressing effects by the ongoing pandemic, intervention group patients showed a significant decrease in depression scores over time. In this non‐blinded RCT, self‐management showed a trend toward improvement in both groups indicating an intervention effect and that a more intensified, evidence‐based, multi‐module self‐management program has positive effects from the patients' point of view. For the combined primary endpoint, no statistically significant difference between groups was observed. For the secondary endpoints, intervention group patients showed significantly lower depression scores and a tendency toward lower anxiety and better QoL in favor for intervention group patients. Social support perceptions were not sensitive toward the intervention. The intervention group showed a significant reduction in depression levels in the intervention in comparison to the control group by the end of this study. This ambiguous effect needs to be framed within the circumstances of the first and second waves of the COVID‐19 pandemic. The Robert Koch Institute performed a representative survey of adults in Germany during the pandemic, and described elevated depression symptom levels and reduced self‐rated mental health. In our study, a significant decrease in depression symptoms was reached despite all potentially depressing effects of the ongoing pandemic. Perhaps this finding can be credited albeit with caution to the curricular modules that focused on resource activation and coping, emotional acceptance of the device, and symptom management, all delivered by professionals with some psychological background. Depression symptoms have been reported to be frequent in patients on durable VAD support , , , , , having potential to diminish the success after VAD implantation in terms of quality of life. , , However, this study was not able to reach statistically significant improvements for anxiety and social support despite a comprehensive self‐management intervention delivered by multiple professions. This might be explained at least in part by the fact that healthcare professionals with psychological background were members of all standard care VAD teams at all four participating sites. Basic VAD handling skills and psychological support were offered to all patients and not withheld to controls. Within this context, we interpret our findings showing trends toward better self‐management, lower anxiety, and higher QoL in the intervention group to be encouraging. Our intervention targeted patients in the hospital in a very early and eventually vulnerable stage post implant and against the background of the Covid‐19 pandemic. We aimed to target self‐management and controlled for social support as a potentially mediating concept. However, the patient‐reported outcome measurement instruments were only applicable after the intervention, for example, the question about someone's ability “to handle the VAD equipment” can be answered only after a skills training has been performed. Thus, measurement concepts and instruments before the intervention had to be limited for two reasons: first, due to a patient's limited ability to answer a battery of questionnaires a few days after the implant procedure in general; and second, because some of the questionnaires and items were not relevant at that time. Therefore, we had to limit the baseline assessment to the HADS and one item (item 46) from the QoLVAD questionnaire. In designing this intervention study aiming to improve self‐management support for patients on VAD support, we followed Howell and associates call to action for self‐management. According to the authors, successful self‐management requires a “whole system approach.” In our SELMA study, being a three‐phase study, we assessed the patient and caregiver needs in phase 1 , , , , ; developed an evidence‐based curriculum in phase 2, and tested the curriculum in the participating heart centers using trained healthcare providers with differing professional background in phase 3. Howells' third column “public policies & financing” was partially and temporarily established by the grant support for this study. However, the success of this study might also be measured by its impact with respect to sustainability. In the participating centers, trained healthcare staff remained as VAD team members, thus, sustaining the skills and knowledge acquired during the study period to be continued after the study period was completed. 4.1 Strengths and limitations Our study holds several strengths and limitations. One of the strengths of this study is that the curriculum was developed based on a thorough scoping review assessing relevant target areas for this self‐management intervention. Two, this study was developed and carried out by a multiprofessional team of experts. We set up a structure for a continuous experience exchange during the course of this study in order to ensure that all intervention content was understood and delivered in a comparable way. Our analyses detected no center‐related biases. Three, the VAD handling is essential and was trained and sustained in refresher sessions as part of this intervention. This seems of particular importance since the Vienna team around Schloeglhofer and associates reported patients' struggling with the change of power supplies, and unintentional driveline disconnections. Our curriculum content might add a jigsaw piece to better equip patients and their caregivers to handle the VAD components in the future, we encourage VAD programs to incorporate the curriculum content into usual care. SELMA App content was transferred to written patient information materials during the lockdown. Thus, patients were able to choose their preferred medium for sustaining their self‐management skills. Regarding weaknesses, first and foremost, the entire study was impacted by the first and second waves of the Covid‐19 pandemic. All elective VAD implant surgery was postponed for all elective surgical procedures, and so was patient recruitment in order to avoid a patient selection bias. Second, the patient recruitment period had to be expanded because patients worried about additional contact with the multiprofessional study team members for the self‐management sessions. Third, our approach consciously invited caregivers to participate in the self‐management sessions. However, caregivers were not allowed into the hospital or declined participation. Four, Covid‐19 prevention precautions and isolation procedures tremendously impacted the logistics during the intervention, for example, in one center, patients were transferred to another campus with long travel times for the study team to deliver the intervention content. Five, despite all efforts by the study team and a permission to expand the patient recruitment process by the funding agency, we were not able to reach our expected sample size and had to adjust the power for this study. Six, our analyses were performed based on the intention‐to‐treat principle according to the study protocol. Kabisch and associates describe this approach as conservative since treatment effects tend to be underestimated regardless of whether the primary endpoint represents an improvement or deterioration. In our study, we have seen trends toward an improved self‐management in the intervention group but failed to prove that self‐management reduced adverse event rates in the combined primary outcome. However, we were able to show a significant reduction in the secondary endpoint depression, a tendency toward reduced anxiety and an increase in quality of life, all favoring the intervention group.   Strengths and limitations Our study holds several strengths and limitations. One of the strengths of this study is that the curriculum was developed based on a thorough scoping review assessing relevant target areas for this self‐management intervention. Two, this study was developed and carried out by a multiprofessional team of experts. We set up a structure for a continuous experience exchange during the course of this study in order to ensure that all intervention content was understood and delivered in a comparable way. Our analyses detected no center‐related biases. Three, the VAD handling is essential and was trained and sustained in refresher sessions as part of this intervention. This seems of particular importance since the Vienna team around Schloeglhofer and associates reported patients' struggling with the change of power supplies, and unintentional driveline disconnections. Our curriculum content might add a jigsaw piece to better equip patients and their caregivers to handle the VAD components in the future, we encourage VAD programs to incorporate the curriculum content into usual care. SELMA App content was transferred to written patient information materials during the lockdown. Thus, patients were able to choose their preferred medium for sustaining their self‐management skills. Regarding weaknesses, first and foremost, the entire study was impacted by the first and second waves of the Covid‐19 pandemic. All elective VAD implant surgery was postponed for all elective surgical procedures, and so was patient recruitment in order to avoid a patient selection bias. Second, the patient recruitment period had to be expanded because patients worried about additional contact with the multiprofessional study team members for the self‐management sessions. Third, our approach consciously invited caregivers to participate in the self‐management sessions. However, caregivers were not allowed into the hospital or declined participation. Four, Covid‐19 prevention precautions and isolation procedures tremendously impacted the logistics during the intervention, for example, in one center, patients were transferred to another campus with long travel times for the study team to deliver the intervention content. Five, despite all efforts by the study team and a permission to expand the patient recruitment process by the funding agency, we were not able to reach our expected sample size and had to adjust the power for this study. Six, our analyses were performed based on the intention‐to‐treat principle according to the study protocol. Kabisch and associates describe this approach as conservative since treatment effects tend to be underestimated regardless of whether the primary endpoint represents an improvement or deterioration. In our study, we have seen trends toward an improved self‐management in the intervention group but failed to prove that self‐management reduced adverse event rates in the combined primary outcome. However, we were able to show a significant reduction in the secondary endpoint depression, a tendency toward reduced anxiety and an increase in quality of life, all favoring the intervention group.   CONCLUSION Our study was the first to develop, implement, and evaluate a comprehensive, evidence‐based, multi‐module self‐management intervention for patients on continuous flow VAD support. Generalizability of the curriculum was established by a thorough analysis and scoping review of the current international literature. The study was classified as a complex intervention, and was performed during and impacted by the Covid‐19 pandemic. Given the fact that depression levels in the German adult population had increased due to the pandemic, the finding of this study that this intervention yielded a significant reduction in depression levels compared to the control group by the end of this study is of utmost importance and a proof of concept. Future research should systematically target self‐management support to patient–caregiver dyads and assess the impact of this intervention on the caregivers to sustain their physical and mental health and thus, their ability to act as effective caregivers for patients on VAD support.   Conception and design (CK, HS, and KTL), acquisition (CK and KTL), analysis, and interpretation (CK, HS, PS, and KTL). Drafting (CK and HS), revising (CK, HS, FR, VL, WA, CSK, SSK, PS, and KTL). Critical revision and final approval (CK, HS, FR, VL, WA, CSK, SSK, PS, and KTL).   This work is supported by The German Federal Joint Committee (G‐BA). Grant number 01VSF18012.   The authors declare that they have no conflicts of interest with the contents of this article.   