Background: Lung transplant (LT) centers are increasingly evaluating patients with multiple risk factors for adverse outcomes. The effects of these stacked risks remains unclear. Our aim was to determine the relationship between the number of comorbidities and post-transplant outcomes.

Methods: We performed a retrospective cohort study using the National Inpatient Sample (NIS) and UNOS Starfile (USF). We applied a probabilistic matching algorithm using 7 variables (transplant: month, year, and type; recipient: age, sex, race, payer). We matched recipients in the USF to transplant patients in the NIS between 2016 and 2019. The Elixhauser methodology was used to identify comorbidities present on admission. We determined the associations between mortality, length of stay (LOS), total charges, and disposition with comorbidity numbers using penalized cubic splines, Kaplan-Meier, and linear and logistic regression methods.

Results: From 28,484,087 NIS admissions, we identified 1,821 LT recipients. Matches were exact in 76.8% of the cohort. While the remaining cohort had a probability match of ≥0.94. Penalized splines of Elixhauser comorbidity number identified 3 knots defining 3 groups of stacked risk: low (<3), medium (3-6), and high risk (>6). Inpatient mortality increased from low to medium to high-risk categories: (1.6%, 3.9%, and 7.0%; p < 0.001), as did LOS (16, 21, 29 days, p < 0.001), total charges ($553,057, $666,791, $821,641.5; p = 0.004) and discharge to a skilled nursing facility (15%, 20%, 31%; p < 0.001).

Conclusions: Stacked risks adversely affect post-LT mortality, LOS, charges, and discharge disposition. Further study to understand the details of specific stacked risks is warranted.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10527778PMC
http://dx.doi.org/10.1016/j.healun.2023.05.020DOI Listing

Publication Analysis

Top Keywords

stacked risks
8
transplanting candidates
4
candidates stacked
4
risks negatively
4
negatively outcomes
4
outcomes background
4
background lung
4
lung transplant
4
transplant centers
4
centers increasingly
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!