Performance status at the time of lung retransplant predicts long-term function.

BACKGROUND: Lung retransplantation is offered to select patients with chronic allograft dysfunction. Given the increased risk of morbidity and mortality conferred by retransplantation, post-transplant function should be considered in the decision of who and when to list. The aim of this study is to identify predictors of post-operative disability in patients undergoing lung retransplantation. METHODS: Data were collected from the UNOS national dataset and included all patients who underwent lung retransplant from May 2005-March 2023. Pre- and post-operative function was reported by the Karnofsky Performance Status (KPS) and patients were stratified based on their needs. Cumulative link mixed effects models identified associations between pre-transplant variables and post-transplant function. RESULTS: A total of 1275 lung retransplant patients were included. After adjusting for between-group differences, pre-operative functional status was predictive of post-transplant function; patients requiring Total Assistance ( n = 740) were 74% more likely than No/Some Assistance patients (n = 535) to require more assistance in follow-up (OR 1.74, 95% CI 1.13-2.68, p = .012). Estimated one year survival of Total Assistance patients is lower than No/Some Assistance Recipients (72% vs. 82%, CI 69%-75%; 79%-86%) but similar to overall re-transplant survival (76%, CI 74%-79%). CONCLUSION: Both survival and regain of function in patients requiring Total Assistance prior to retransplant may be higher than previously reported. Pre-operative functional status is predictive of post-operative function and should weigh in the selection, timing and post-operative care of patients considered for lung retransplantation.

A qualitative study of social connectedness and its relationship to community health programs in rural Chiapas, Mexico.

BACKGROUND: Social connectedness is an important predictor of health outcomes and plays a large role in the physical and mental health of an individual and a community. The presence of a functioning health clinic with a community health worker program may indirectly improve health outcomes by increasing the social connectedness of the community in addition to providing direct patient care. This study examines the social connectedness of the inhabitants of three Mexican towns within the catchment area of a healthcare Non-Government Organization (NGO) through a qualitative analysis. METHODS: Willing participants were videotaped answering open-ended questions about their community and use of healthcare resources. Interviews were then coded for relevant themes and analyzed for content relating to social connectedness, social isolation, and health. RESULTS: Respondents reported that having a functioning community clinic had improved their lives significantly through direct provision of care and by reducing the financial burden of travel to seek medical care elsewhere. Respondents from each town differed slightly in their primary means of social support. One town relied more heavily on organized groups (i.e., religious groups) for their support system. Social isolation was reported most frequently by housewives who felt isolated in the home and by respondents that had to deal with personal illness. Respondents that self-identified as Community Health Workers (CHWs) in their respective communities acknowledged that their roles bestowed physical and psychological health benefits upon themselves and their families. CONCLUSIONS: Overall, a long-term health intervention may directly impact the relative social isolation and social connectedness of a community's inhabitants. The social connectedness of the community is an important quality that must be considered when evaluating and planning health interventions.

Waitlist Mortality and Extracorporeal Membrane Oxygenation Bridge to Lung Transplant.

BACKGROUND: Use of extracorporeal membrane oxygenation (ECMO) as bridge to lung transplant has increased. However, little is known about patients placed on ECMO who die while on the waiting list. Using a national lung transplant data set, we investigated variables associated with waitlist mortality of patients bridged to lung transplant. METHODS: All patients supported on ECMO at time of listing were identified using the United Network for Organ Sharing database. Univariable analyses were performed using bias-reduced logistic regression. Cause-specific hazard models were used to determine the effect of variables of interest on hazard of outcomes. RESULTS: From April 2016 to December 2021, 634 patients met inclusion criteria. Of these, 445 (70%) were successfully bridged to transplant, 148 (23%) died on the waitlist, and 41 (6.5%) were removed for other reasons. Univariable analysis found associations between waitlist mortality and blood group, age, body mass index, serum creatinine, lung allocation score, days on waitlist, United Network for Organ Sharing region, and being listed at a lower-volume center. Cause-specific hazard models demonstrated that patients at high-volume centers were 24% more likely to survive to transplant and 44% less likely to die on the waitlist. Among patients who were successfully bridged to transplant, there was no difference in survival between low- and high-volume centers. CONCLUSIONS: ECMO is an appropriate strategy to bridge selected high-risk patients to lung transplant. Of those placed on ECMO with intent to transplant, about one quarter may not survive to transplantation. High-risk patients requiring advanced support strategies may be more likely to survive to transplant when bridged at a high-volume center.

Evolution of extracorporeal membrane oxygenation trigger criteria in COVID-19 acute respiratory distress syndrome.

OBJECTIVE: To understand the implications of a tiered extracorporeal membrane oxygenation (ECMO) criteria framework and the outcomes of patients with COVID-19 acute respiratory distress syndrome who we were consulted on for ECMO but ultimately declined. METHODS: All patients declined for ECMO support by a large regional health care system between March 2020 and July 2021 were included. Restrictive selection criteria were enacted midway through the study stratifying the cohort into 2 groups. Primary outcomes included 30-day mortality. Secondary outcomes included reasons for declining ECMO and survival stratified by phase. RESULTS: One hundred ninety-three patients with COVID-19 acute respiratory distress syndrome were declined for ECMO within the study period out of 260 ECMO consults. At the time of consult, 71.0% (n = 137) were mechanically ventilated and 38% (n = 74) were proned and chemically paralyzed. Thirty-day mortality was 66% (n = 117), which increased from 53% to 73% (P = .010) when restrictive criteria were enacted. Patients with multisystem organ failure, prolonged ventilator time, and advanced age had respectively an 11-fold (odds ratio, 10.6; 95% CI, 1.7-65.2), 4-fold (odds ratio, 3.5; 95% CI, 1.1-12.0), and 4-fold (odds ratio, 4.4; 95% CI, 1.9-10.2) increase in the odds of mortality. CONCLUSIONS: Patients with COVID-19 acute respiratory distress syndrome declined for ECMO represent a critically ill cohort. We observed an increase in the severity of disease and 30-day mortality in consults in the latter phase of our study period. These findings may reflect our use of tiered selection criteria coupled with ongoing education and communication with referring centers, sparing both patients likely to respond to medical therapy and those who were unsalvageable by ECMO.

Harnessing mHealth technologies to increase physical activity and prevent cardiovascular disease.

Research into prevention of cardiovascular disease has increasingly focused on mobile health (mHealth) technologies and their efficacy in helping individuals adhere to heart-healthy recommendations, including daily physical activity levels. By including the use of mHealth technologies in the discussion of physical activity recommendations, clinicians empower patients to play an active daily role in modifying their cardiovascular risk-factor profile. In this review, we critically evaluate the mHealth and physical activity literature to determine how these tools may lower cardiovascular risk while providing real-time tracking, feedback, and motivation on physical activity levels. We analyze the various domains-including user knowledge, social support, behavioral change theory, and self-motivation-that potentially influence the effectiveness of smartphone applications to impact individual physical activity levels. In doing so, we hope to provide a thorough overview of the mHealth landscape, in addition to highlighting many of the administrative, reimbursement, and patient-privacy challenges of using these technologies in patient care. Finally, we propose a behavioral change model and checklist for clinicians to assist patients in utilizing mHealth technology to best achieve meaningful changes in daily physical activity levels.