Literature DB >> 12973108

Diagnostic accuracy of coronary angiography and risk factors for post-heart-transplant cardiac allograft vasculopathy.

Linda D Sharples1, Christopher H Jackson, Jayan Parameshwar, John Wallwork, Stephen R Large.   

Abstract

Cardiac allograft vasculopathy (CAV) is a common cause of death after heart transplantation. Coronary angiography is used to monitor the progress of recipients. Diagnostic accuracy of angiography and risk factors for CAV have not been clearly established. Between August 1979 and January 2002, 566 1-year survivors of heart transplantation underwent 2168 angiograms and were classified as having no CAV (0% stenosis), mild-moderate CAV (up to 70% stenosis), or severe CAV (>70% stenosis). We used serial measurements of stenosis to estimate the diagnostic accuracy of angiography and to assess the following risk factors for CAV onset, progression, and survival: recipient and donor age and sex, preoperative ischemic heart disease (IHD), acute rejection rates, cytomegalovirus (CMV) infection, and serologic status. CAV was diagnosed by angiography in 248 of 556 (45%) 1-year survivors, with a mean onset time of 8.6 years. Patients spent a mean of 3.4 years with mild-moderate disease and 3.4 years with severe disease before death. Angiography specificity was 97.8%, and sensitivity was 79.3%. The following variables were found to significantly increase the risk of CAV onset: recipient age relative rate (95% confidence interval) 1.16 (1.01-1.34), donor age by 1.27 (1.13-1.43), male recipient by 2.00 (1.11-2.57), pretransplant IHD by 1.75 (1.30-2.36), cumulative rejection by 1.13 (1.05-1.21), and CMV infection by 1.42 (1.06-1.92). Acute rejection increased risk of death by 1.48 (1.19-1.85). Angiography is highly specific and moderately sensitive for diagnosis of CAV. Risk of CAV onset is related to donor age and recipient history of pretransplant IHD and is further increased by immune-related insults of acute rejection and CMV infection.

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Year:  2003        PMID: 12973108     DOI: 10.1097/01.TP.0000071200.37399.1D

Source DB:  PubMed          Journal:  Transplantation        ISSN: 0041-1337            Impact factor:   4.939


  6 in total

1.  Multicenter Analysis of Immune Biomarkers and Heart Transplant Outcomes: Results of the Clinical Trials in Organ Transplantation-05 Study.

Authors:  R C Starling; J Stehlik; D A Baran; B Armstrong; J R Stone; D Ikle; Y Morrison; N D Bridges; P Putheti; T B Strom; M Bhasin; I Guleria; A Chandraker; M Sayegh; K P Daly; D M Briscoe; P S Heeger
Journal:  Am J Transplant       Date:  2015-08-10       Impact factor: 8.086

2.  Reduced Myocardial Flow Reserve by Positron Emission Tomography Predicts Cardiovascular Events After Cardiac Transplantation.

Authors:  Matthew C Konerman; John J Lazarus; Richard L Weinberg; Ravi V Shah; Michael Ghannam; Scott L Hummel; James R Corbett; Edward P Ficaro; Keith D Aaronson; Monica M Colvin; Todd M Koelling; Venkatesh L Murthy
Journal:  Circ Heart Fail       Date:  2018-06       Impact factor: 8.790

3.  Qualitative Perfusion Cardiac Magnetic Resonance Imaging Lacks Sensitivity in Detecting Cardiac Allograft Vasculopathy.

Authors:  Monica Colvin-Adams; Salam Petros; Ganesh Raveendran; Emil Missov; Eduardo Medina; Robert Wilson
Journal:  Cardiol Res       Date:  2011-11-20

4.  Analysis of Fibrotic Plaques in Angiographic Manifest Cardiac Allograft Vasculopathy in Long-term Heart Transplanted Patients Using Optical Coherence Tomography.

Authors:  Madeleine Orban; Dominic Dischl; Christoph Müller; Sarah Ulrich; Tobias Petzold; Konstantinos Rizas; Martin W Orban; Daniel Braun; Jörg Hausleiter; Christian Hagl; Julinda Mehilli; Steffen Massberg
Journal:  Transplant Direct       Date:  2021-12-23

5.  Cytomegalovirus infection and disease reduce 10-year cardiac allograft vasculopathy-free survival in heart transplant recipients.

Authors:  Inger Johansson; Rune Andersson; Vanda Friman; Nedim Selimovic; Lars Hanzen; Salmir Nasic; Ulla Nyström; Vilborg Sigurdardottir
Journal:  BMC Infect Dis       Date:  2015-12-24       Impact factor: 3.090

6.  Multistate Markov Model to Predict the Prognosis of High-Risk Human Papillomavirus-Related Cervical Lesions.

Authors:  Ayumi Taguchi; Konan Hara; Jun Tomio; Kei Kawana; Tomoki Tanaka; Satoshi Baba; Akira Kawata; Satoko Eguchi; Tetsushi Tsuruga; Mayuyo Mori; Katsuyuki Adachi; Takeshi Nagamatsu; Katsutoshi Oda; Toshiharu Yasugi; Yutaka Osuga; Tomoyuki Fujii
Journal:  Cancers (Basel)       Date:  2020-01-22       Impact factor: 6.639

  6 in total

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