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Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations

Background and Objectives: There are no nationally representative studies of mortality and cost effectiveness for fractional flow reserve (FFR) guided percutaneous coronary interventions (PCI) in patients with cancer. Our study aims to show how this patient population may benefit from FFR-guided PCI...

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Autores principales: Chauhan, Siddharth, Monlezun, Dominique J., Kim, Jin wan, Goel, Harsh, Hanna, Alex, Hoang, Kenneth, Palaskas, Nicolas, Lopez-Mattei, Juan, Hassan, Saamir, Kim, Peter, Cilingiroglu, Mehmet, Marmagkiolis, Konstantinos, Iliescu, Cezar A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320131/
https://www.ncbi.nlm.nih.gov/pubmed/35888578
http://dx.doi.org/10.3390/medicina58070859
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author Chauhan, Siddharth
Monlezun, Dominique J.
Kim, Jin wan
Goel, Harsh
Hanna, Alex
Hoang, Kenneth
Palaskas, Nicolas
Lopez-Mattei, Juan
Hassan, Saamir
Kim, Peter
Cilingiroglu, Mehmet
Marmagkiolis, Konstantinos
Iliescu, Cezar A.
author_facet Chauhan, Siddharth
Monlezun, Dominique J.
Kim, Jin wan
Goel, Harsh
Hanna, Alex
Hoang, Kenneth
Palaskas, Nicolas
Lopez-Mattei, Juan
Hassan, Saamir
Kim, Peter
Cilingiroglu, Mehmet
Marmagkiolis, Konstantinos
Iliescu, Cezar A.
author_sort Chauhan, Siddharth
collection PubMed
description Background and Objectives: There are no nationally representative studies of mortality and cost effectiveness for fractional flow reserve (FFR) guided percutaneous coronary interventions (PCI) in patients with cancer. Our study aims to show how this patient population may benefit from FFR-guided PCI. Materials and Methods: Propensity score matched analysis and backward propagation neural network machine learning supported multivariable regression was performed for inpatient mortality in this case-control study of the 2016 National Inpatient Sample (NIS). Regression results were adjusted for age, race, income, geographic region, metastases, mortality risk, and the likelihood of undergoing FFR versus non-FFR PCI. All analyses were adjusted for the complex survey design to produce nationally representative estimates. Results: Of the 30,195,722 hospitalized patients meeting criteria, 3.37% of the PCIs performed included FFR. In propensity score adjusted multivariable regression, FFR versus non-FFR PCI significantly reduced inpatient mortality (OR 0.47, 95%CI 0.35–0.63; p < 0.001) and length of stay (LOS) (in days; beta −0.23, 95%CI −0.37–−0.09; p = 0.001) while increasing cost (in USD; beta $5708.63, 95%CI, 3042.70–8374.57; p < 0.001), without significantly increasing complications overall. FFR versus non-FFR PCI did not specifically change cancer patients’ inpatient mortality, LOS, or cost. However, FFR versus non-FFR PCI significantly increased inpatient mortality for Hodgkin’s lymphoma (OR 52.48, 95%CI 7.16–384.53; p < 0.001) and rectal cancer (OR 24.38, 95%CI 2.24–265.73; p = 0.009). Conclusions: FFR-guided PCI may be safely utilized in patients with cancer as it does not significantly increase inpatient mortality, complications, and LOS. These findings support the need for an increased utilization of FFR-guided PCI and further studies to evaluate its long-term impact.
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spelling pubmed-93201312022-07-27 Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations Chauhan, Siddharth Monlezun, Dominique J. Kim, Jin wan Goel, Harsh Hanna, Alex Hoang, Kenneth Palaskas, Nicolas Lopez-Mattei, Juan Hassan, Saamir Kim, Peter Cilingiroglu, Mehmet Marmagkiolis, Konstantinos Iliescu, Cezar A. Medicina (Kaunas) Article Background and Objectives: There are no nationally representative studies of mortality and cost effectiveness for fractional flow reserve (FFR) guided percutaneous coronary interventions (PCI) in patients with cancer. Our study aims to show how this patient population may benefit from FFR-guided PCI. Materials and Methods: Propensity score matched analysis and backward propagation neural network machine learning supported multivariable regression was performed for inpatient mortality in this case-control study of the 2016 National Inpatient Sample (NIS). Regression results were adjusted for age, race, income, geographic region, metastases, mortality risk, and the likelihood of undergoing FFR versus non-FFR PCI. All analyses were adjusted for the complex survey design to produce nationally representative estimates. Results: Of the 30,195,722 hospitalized patients meeting criteria, 3.37% of the PCIs performed included FFR. In propensity score adjusted multivariable regression, FFR versus non-FFR PCI significantly reduced inpatient mortality (OR 0.47, 95%CI 0.35–0.63; p < 0.001) and length of stay (LOS) (in days; beta −0.23, 95%CI −0.37–−0.09; p = 0.001) while increasing cost (in USD; beta $5708.63, 95%CI, 3042.70–8374.57; p < 0.001), without significantly increasing complications overall. FFR versus non-FFR PCI did not specifically change cancer patients’ inpatient mortality, LOS, or cost. However, FFR versus non-FFR PCI significantly increased inpatient mortality for Hodgkin’s lymphoma (OR 52.48, 95%CI 7.16–384.53; p < 0.001) and rectal cancer (OR 24.38, 95%CI 2.24–265.73; p = 0.009). Conclusions: FFR-guided PCI may be safely utilized in patients with cancer as it does not significantly increase inpatient mortality, complications, and LOS. These findings support the need for an increased utilization of FFR-guided PCI and further studies to evaluate its long-term impact. MDPI 2022-06-28 /pmc/articles/PMC9320131/ /pubmed/35888578 http://dx.doi.org/10.3390/medicina58070859 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chauhan, Siddharth
Monlezun, Dominique J.
Kim, Jin wan
Goel, Harsh
Hanna, Alex
Hoang, Kenneth
Palaskas, Nicolas
Lopez-Mattei, Juan
Hassan, Saamir
Kim, Peter
Cilingiroglu, Mehmet
Marmagkiolis, Konstantinos
Iliescu, Cezar A.
Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations
title Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations
title_full Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations
title_fullStr Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations
title_full_unstemmed Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations
title_short Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations
title_sort fractional flow reserve cardio-oncology effects on inpatient mortality, length of stay, and cost based on malignancy type: machine learning supported nationally representative case-control study of 30 million hospitalizations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320131/
https://www.ncbi.nlm.nih.gov/pubmed/35888578
http://dx.doi.org/10.3390/medicina58070859
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