Validation of the International Society for Heart and Lung Transplantation primary graft dysfunction instrument in heart transplantation

Foroutan, Farid; Alba, Ana Carolina; Stein, Madeleine; Krakovsky, John; Chien, Kevin; Chih, Sharon; Guyatt, Gordon; Ross, Heather J.

doi:10.1016/j.healun.2018.12.007

Cited by 23 publications

(11 citation statements)

References 13 publications

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“…Some of the above factors are used to calculate a RADIAL score which stratifies patients into low-, intermediate-, and highrisk for developing PGD after HTx. This risk score has subsequently been validated [94][95][96][97].…”

Section: Graft Dysfunction and Failurementioning

confidence: 99%

Current status and outcomes in heart transplantation: a narrative review

Awad¹,

Shah²,

Griffith³

2022

Rev. Cardiovasc. Med.

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The first human heart transplantation was performed by Christian Barnard in 1967. While the technical aspect had been worked out, allograft rejection was a major limitation in the early days of heart transplant. The discovery of cyclosporine revolutionized the field and led to the modern era of transplant. Heart transplantation now offers the best survival benefit for patients with end-stage heart failure with a median survival over 12 years. However, there are still limitations including the impact of limited availability of graft, graft dysfunction, and rejection, and long-term non-cardiac complications. This review serves as an update on the short-and long-term outcomes following heart transplantation focusing on the new donor allocation system, efforts to expand the donor pool, primary graft dysfunction, acute cellular and antibody-mediated rejection, cardiac allograft vasculopathy, and post-transplant malignancy and renal dysfunction.

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Section: Graft Dysfunction and Failurementioning

confidence: 99%

Current status and outcomes in heart transplantation: a narrative review

Awad¹,

Shah²,

Griffith³

2022

Rev. Cardiovasc. Med.

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“…Since the establishment of the International Society for Heart and Lung Transplantation (ISHLT) consensus definition in 2014, 21 the incidence of PGD has been reported to be between 10% and 36% with severe PGD incidence as high as 18%. 22 Due to the association of PGD with significantly decreased early and long-term survival after heart transplant, 23 the identification of risk factors has become a critical component in the prevention and management of this life-threatening condition.…”

Section: Primary Graft Dysfunction After Heart Transplantationmentioning

confidence: 99%

“…29 The finding of recipient pretransplant VAD as a risk factor for PGD was also identified in other recent studies. 23,30 In 2017, more than 50% of heart transplant recipients were bridged to transplant with MCS compared with 19.1% just 7 years prior. 30 This underscores the need for a predictive tool that can be applied as a means of prevention and treatment of PGD.…”

Section: Primary Graft Dysfunction After Heart Transplantationmentioning

confidence: 99%

Noteworthy Literature From 2019 for Cardiothoracic Critical Care

Shen

Tam

Jones

et al. 2020

Semin Cardiothorac Vasc Anesth

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“…5,6 Previous studies by the International Society of Heart and Lung Transplantation (ISHLT) have attempted to investigate mortality rates and ascertain the variables most predictive for patient's post-transplant by utilizing traditional regression models and multivariable analysis. 7,8 These models remain underutilized in clinical practice due to their relatively weak and variable predictive powers of outcomes that are multidimensional in nature.…”

Section: Introductionmentioning

confidence: 99%

Machine learning and artificial intelligence in cardiac transplantation: A systematic review

et al. 2022

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Background This review aims to systematically evaluate the currently available evidence investigating the use of artificial intelligence (AI) and machine learning (ML) in the field of cardiac transplantation. Furthermore, based on the challenges identified we aim to provide a series of recommendations and a knowledge base for future research in the field of ML and heart transplantation. Methods A systematic database search was conducted of original articles that explored the use of ML and/or AI in heart transplantation in EMBASE, MEDLINE, Cochrane database, and Google Scholar, from inception to November 2021. Results Our search yielded 237 articles, of which 13 studies were included in this review, featuring 463 850 patients. Three main areas of application were identified: (1) ML for predictive modeling of heart transplantation mortality outcomes; (2) ML in graft failure outcomes; (3) ML to aid imaging in heart transplantation. The results of the included studies suggest that AI and ML are more accurate in predicting graft failure and mortality than traditional scoring systems and conventional regression analysis. Major predictors of graft failure and mortality identified in ML models were: length of hospital stay, immunosuppressive regimen, recipient's age, congenital heart disease, and organ ischemia time. Other potential benefits include analyzing initial lab investigations and imaging, assisting a patient with medication adherence, and creating positive behavioral changes to minimize further cardiovascular risk. Conclusion ML demonstrated promising applications for improving heart transplantation outcomes and patient‐centered care, nevertheless, there remain important limitations relating to implementing AI into everyday surgical practices.

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Validation of the International Society for Heart and Lung Transplantation primary graft dysfunction instrument in heart transplantation

Cited by 23 publications

References 13 publications

Current status and outcomes in heart transplantation: a narrative review

Current status and outcomes in heart transplantation: a narrative review

Noteworthy Literature From 2019 for Cardiothoracic Critical Care

Machine learning and artificial intelligence in cardiac transplantation: A systematic review

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