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Patients were split between Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) Classes 1, 2 and 3 (25%, 38% and 34%, respectively). Within this group, \u2018provisional RVF\u2019 patients were identified, along with \u2018no RVF\u2019 patients. \u2018No RVF\u2019 patients were defined as patients who never demonstrated more than moderate RV dysfunction on a post-LVAD transthoracic echocardiogram (TTE) (ordinal RV function &amp;lt;3), never required an RV assist device (RVAD), were not discharged on sildenafil and were not on a pulmonary vasodilator or inotropic medication at 3 months after LVAD implant. In total, n = 67 patients were defined as \u2018no RVF\u2019. The remaining patients represented the \u2018provisional RVF\u2019 population (n = 165). Extensive electronic health records queries yielded &amp;gt;1200 data points per patient. Using &amp;lt;1 and &amp;gt;1 month post-LVAD time windows motivated by established, expert-consensus definitions of \u2018early\u2019 and \u2018late\u2019 post-implant RVF, unbiased clustering analysis was performed to identify hidden patient \u2018phenogroups\u2019 within these two established RVF populations. Clusters were compared on post-implant clinical metrics and 1 year outcomes. Lastly, pre-implant metrics were used to generate models for predicting post-implant RVF phenogroup.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Within the \u2018early RVF\u2019 time window, distinct \u2018well\u2019 and \u2018sick\u2019 patient phenogroup clusters were identified. These clusters had similar RV function and pulmonary vasodilator usage during the first month after LVAD but differed significantly in heart failure therapy tolerance, renal (P &amp;lt; 0.001) and hepatic (P = 0.013) function, RVAD usage (P = 0.001) and 1 year mortality (P = 0.047). Distinct \u2018well\u2019 and \u2018sick\u2019 phenogroups were also identified in the \u2018late RVF\u2019 time window. These clusters had similar RV function (P = 0.111) and RVAD proportions (P = 0.757) but differed significantly in heart failure medication tolerance, pulmonary vasodilator usage (P = 0.001) and 1 year mortality (P &amp;lt; 0.001). Prediction of phenogroup clusters from the \u2018early RVF\u2019 population achieved an area under the receiver operating characteristic curve (AUROC) of 0.84, with top predictors including renal function, liver function, heart rate and pre-LVAD RV function.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Distinct, potentially predictable phenogroups of patients who have significantly different long-term outcomes exist within consensus-defined post-LVAD RVF populations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ehf2.15200","type":"journal-article","created":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T04:48:32Z","timestamp":1737348512000},"page":"1916-1931","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Predicting Right Ventricular Failure After Left Ventricular Assist Device 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