Background Liver transplants account for a high number of procedures with major investments from all stakeholders involved; however, limited studies address liver transplant population heterogeneity pretransplant predictive of posttransplant survival. Objective The aim of the study was to identify novel and meaningful patient clusters predictive of mortality that explains the heterogeneity of liver transplant population, taking a holistic approach. Methods A retrospective cohort study of 344 adult patients who underwent liver transplantation between 2008 through 2014. Predictors were summarized severity scores for comorbidities and other suboptimal health states grouped into 11 body systems, the primary reason for transplantation, demographics/environmental factors, and Model for End Liver Disease score. Logistic regression was used to compute the severity scores, hierarchical clustering with weighted Euclidean distance for clustering, Lasso-penalized regression for characterizing the clusters, and Kaplan-Meier analysis to compare survival across the clusters. Results Cluster 1 included patients with more severe circulatory problems. Cluster 2 represented older patients with more severe primary disease, whereas Cluster 3 contained healthiest patients. Clusters 4 and 5 represented patients with musculoskeletal (e.g., pain) and endocrine problems (e.g., malnutrition), respectively. There was a statistically significant difference for mortality between clusters (p <.001). Conclusions This study developed a novel methodology to address heterogeneous and high-dimensional liver transplant population characteristics in a single study predictive of survival. A holistic approach for data modeling and additional psychosocial risk factors has the potential to address holistically nursing challenges on liver transplant care and research.
Bibliographical noteFunding Information:
Accepted for publication February 9, 2018. The authors acknowledge Lisiane Pruinelli was supported by the 2015/ 2016 University of Minnesota Doctoral Dissertation Fellowship and the Midwest Nursing Research Society 2016 Joseph and Jean Buckwalter Grant. This study was approved by the University of Minnesota Institutional Review Board (No. 1502E62121). The authors have no conflict of interest to report. Corresponding author: Lisiane Pruinelli, PhD, MS, RN, University of Minnesota School of Nursing, 6-183 Weaver-Densford Hall, 308 Harvard Street SE, Minneapolis, MN 55455 (e-mail: email@example.com).
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- holistic nursing
- liver transplantation
- predictive modeling