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Dynamic prediction of left ventricular assist device pump thrombosis based on lactate dehydrogenase trends

AIMS: The risk of HeartMate II (HMII) left ventricular assist device (LVAD) thrombosis has been reported, and serum lactate dehydrogenase (LDH), a biomarker of haemolysis, increases secondary to LVAD thrombosis. This study evaluated longitudinal measurements of LDH post‐LVAD implantation, hypothesiz...

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Autores principales: Hurst, Thomas E., Xanthopoulos, Andrew, Ehrlinger, John, Rajeswaran, Jeevanantham, Pande, Amol, Thuita, Lucy, Smedira, Nicholas G., Moazami, Nader, Blackstone, Eugene H., Starling, Randall C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6816063/
https://www.ncbi.nlm.nih.gov/pubmed/31318170
http://dx.doi.org/10.1002/ehf2.12473
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author Hurst, Thomas E.
Xanthopoulos, Andrew
Ehrlinger, John
Rajeswaran, Jeevanantham
Pande, Amol
Thuita, Lucy
Smedira, Nicholas G.
Moazami, Nader
Blackstone, Eugene H.
Starling, Randall C.
author_facet Hurst, Thomas E.
Xanthopoulos, Andrew
Ehrlinger, John
Rajeswaran, Jeevanantham
Pande, Amol
Thuita, Lucy
Smedira, Nicholas G.
Moazami, Nader
Blackstone, Eugene H.
Starling, Randall C.
author_sort Hurst, Thomas E.
collection PubMed
description AIMS: The risk of HeartMate II (HMII) left ventricular assist device (LVAD) thrombosis has been reported, and serum lactate dehydrogenase (LDH), a biomarker of haemolysis, increases secondary to LVAD thrombosis. This study evaluated longitudinal measurements of LDH post‐LVAD implantation, hypothesizing that LDH trends could timely predict future LVAD thrombosis. METHODS AND RESULTS: From October 2004 to October 2014, 350 HMIIs were implanted in 323 patients at Cleveland Clinic. Of these, patients on 339 HMIIs had at least one post‐implant LDH value (7996 total measurements). A two‐step joint model combining longitudinal biomarker data and pump thrombosis events was generated to assess the effect of changing LDH on thrombosis risk. Device‐specific LDH trends were first smoothed using multivariate boosted trees, and then used as a time‐varying covariate function in a multiphase hazard model to analyse time to thrombosis. Pre‐implant variables associated with time‐varying LDH values post‐implant using boostmtree were also investigated. Standardized variable importance for each variable was estimated as the difference between model‐based prediction error of LDH when the variable was randomly permuted and prediction error without permuting the values. The larger this difference, the more important a variable is for predicting the trajectory of post‐implant LDH. Thirty‐five HMIIs (10%) had either confirmed (18) or suspected (17) thrombosis, with 15 (43%) occurring within 3 months of implant. LDH was associated with thrombosis occurring both early and late after implant (P < 0.0001 for both hazard phases). The model demonstrated increased probability of HMII thrombosis as LDH trended upward, with steep changes in LDH trajectory paralleling trajectories in probability of pump thrombosis. The most important baseline variables predictive of the longitudinal pattern of LDH were higher bilirubin, higher pre‐implant LDH, and older age. The effect of some pre‐implant variables such as sodium on the post‐implant LDH longitudinal pattern differed across time. CONCLUSIONS: Longitudinal trends in surveillance LDH for patients on HMII support are useful for dynamic prediction of pump thrombosis, both early after implant and late. Incorporating upward and downward trends in LDH that dynamically update a model of LVAD thrombosis risk provides a useful tool for clinical management and decisions.
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spelling pubmed-68160632019-10-31 Dynamic prediction of left ventricular assist device pump thrombosis based on lactate dehydrogenase trends Hurst, Thomas E. Xanthopoulos, Andrew Ehrlinger, John Rajeswaran, Jeevanantham Pande, Amol Thuita, Lucy Smedira, Nicholas G. Moazami, Nader Blackstone, Eugene H. Starling, Randall C. ESC Heart Fail Original Research Articles AIMS: The risk of HeartMate II (HMII) left ventricular assist device (LVAD) thrombosis has been reported, and serum lactate dehydrogenase (LDH), a biomarker of haemolysis, increases secondary to LVAD thrombosis. This study evaluated longitudinal measurements of LDH post‐LVAD implantation, hypothesizing that LDH trends could timely predict future LVAD thrombosis. METHODS AND RESULTS: From October 2004 to October 2014, 350 HMIIs were implanted in 323 patients at Cleveland Clinic. Of these, patients on 339 HMIIs had at least one post‐implant LDH value (7996 total measurements). A two‐step joint model combining longitudinal biomarker data and pump thrombosis events was generated to assess the effect of changing LDH on thrombosis risk. Device‐specific LDH trends were first smoothed using multivariate boosted trees, and then used as a time‐varying covariate function in a multiphase hazard model to analyse time to thrombosis. Pre‐implant variables associated with time‐varying LDH values post‐implant using boostmtree were also investigated. Standardized variable importance for each variable was estimated as the difference between model‐based prediction error of LDH when the variable was randomly permuted and prediction error without permuting the values. The larger this difference, the more important a variable is for predicting the trajectory of post‐implant LDH. Thirty‐five HMIIs (10%) had either confirmed (18) or suspected (17) thrombosis, with 15 (43%) occurring within 3 months of implant. LDH was associated with thrombosis occurring both early and late after implant (P < 0.0001 for both hazard phases). The model demonstrated increased probability of HMII thrombosis as LDH trended upward, with steep changes in LDH trajectory paralleling trajectories in probability of pump thrombosis. The most important baseline variables predictive of the longitudinal pattern of LDH were higher bilirubin, higher pre‐implant LDH, and older age. The effect of some pre‐implant variables such as sodium on the post‐implant LDH longitudinal pattern differed across time. CONCLUSIONS: Longitudinal trends in surveillance LDH for patients on HMII support are useful for dynamic prediction of pump thrombosis, both early after implant and late. Incorporating upward and downward trends in LDH that dynamically update a model of LVAD thrombosis risk provides a useful tool for clinical management and decisions. John Wiley and Sons Inc. 2019-07-18 /pmc/articles/PMC6816063/ /pubmed/31318170 http://dx.doi.org/10.1002/ehf2.12473 Text en © 2019 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of the European Society of Cardiology. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Research Articles
Hurst, Thomas E.
Xanthopoulos, Andrew
Ehrlinger, John
Rajeswaran, Jeevanantham
Pande, Amol
Thuita, Lucy
Smedira, Nicholas G.
Moazami, Nader
Blackstone, Eugene H.
Starling, Randall C.
Dynamic prediction of left ventricular assist device pump thrombosis based on lactate dehydrogenase trends
title Dynamic prediction of left ventricular assist device pump thrombosis based on lactate dehydrogenase trends
title_full Dynamic prediction of left ventricular assist device pump thrombosis based on lactate dehydrogenase trends
title_fullStr Dynamic prediction of left ventricular assist device pump thrombosis based on lactate dehydrogenase trends
title_full_unstemmed Dynamic prediction of left ventricular assist device pump thrombosis based on lactate dehydrogenase trends
title_short Dynamic prediction of left ventricular assist device pump thrombosis based on lactate dehydrogenase trends
title_sort dynamic prediction of left ventricular assist device pump thrombosis based on lactate dehydrogenase trends
topic Original Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6816063/
https://www.ncbi.nlm.nih.gov/pubmed/31318170
http://dx.doi.org/10.1002/ehf2.12473
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