2026-04-29T04:08:41Zhttps://repisalud.isciii.es/rest/oai/request
oai:repisalud.isciii.es:20.500.12105/192472024-09-21T11:42:54Zcom_20.500.12105_19604com_20.500.12105_2051col_20.500.12105_19605
Repisalud author Arana-Achaga, Xabier author Goena-Vives, Cristina author Villanueva-Benito, Iñaki author Solla-Ruiz, Itziar author Rengel Jimenez, Ainhoa author Gaspar, Teresa Iglesias author Urreta-Barallobre, Iratxe author Barge-Caballero, Gonzalo author Seijas-Marcos, Sara author Cabrera, Eva author Garcia-Pavía, Pablo author Basurte Elorz, María Teresa author Ayestarán, Nerea Mora author Sierra, Lucas Tojal author Robledo Iñarritu, Maria author Lozano-Bahamonde, Ainara author Escolar-Perez, Vanesa author Gómez-Ramírez, Cristina author Alzola, Elisabete author Andrés, Rubén Natividad author Francisco Matias, Jose Luis author Limeres Freire, Javier author Armengou Arxe, Arola author Negre Busó, Montserrat author Piqueras-Flores, Jesus author Martínez-Del Río, Jorge author Onaindia Gandarias, Jose Juan author Rodriguez Sanchez, Ibon author Querejeta Iraola, Ramón funder Pfizer funder Unión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF) funder Ministerio de Ciencia e Innovación (España) funder Fundación ProCNIC funder Ministerio de Ciencia e Innovación. Centro de Excelencia Severo Ochoa (España) 2024-05-06T12:48:00Z 2024-05-06T12:48:00Z 2023-12 JACC Cardiovasc Imaging . 2023 Dec;16(12):1567-1580. http://hdl.handle.net/20.500.12105/19247 37389511 10.1016/j.jcmg.2023.05.002 1876-7591 JACC. Cardiovascular imaging BACKGROUND Although transthyretin cardiac amyloidosis (ATTR-CA) is often underdiagnosed, clinical suspicion is essential for early diagnosis. OBJECTIVES The aim of this study was to develop and validate a feasible prediction model and score to facilitate the diagnosis of ATTR-CA. METHODS This retrospective multicenter study enrolled consecutive patients who underwent 99mTc-DPD scintigraphy for suspected ATTR-CA. ATTR-CA was diagnosed if Grade 2 or 3 cardiac uptake was evidenced on 99mTc-DPD scintigraphy in the absence of a detectable monoclonal component or by demonstration of amyloid by biopsy. A prediction model for ATTR-CA diagnosis was developed in a derivation sample of 227 patients from 2 centers using multivariable logistic regression with clinical, electrocardiography, analytical, and transthoracic echocardiography variables. A simplified score was also created. Both of them were validated in an external cohort (n = 895) from 11 centers. RESULTS The obtained prediction model combined age, gender, carpal tunnel syndrome, interventricular septum in diastole thickness, and low QRS interval voltages, with an area under the curve (AUC) of 0.92. The score had an AUC of 0.86. Both the T-Amylo prediction model and the score showed a good performance in the validation sample (ie, AUC: 0.84 and 0.82, respectively). They were tested in 3 clinical scenarios of the validation cohort: 1) hypertensive cardiomyopathy (n = 327); 2) severe aortic stenosis (n = 105); and 3) heart failure with preserved ejection fraction (n = 604), all with good diagnostic accuracy. CONCLUSIONS The T-Amylo is a simple prediction model that improves the prediction of ATTR-CA diagnosis in patients with suspected ATTR-CA. eng Development and Validation of a Prediction Model and Score for Transthyretin Cardiac Amyloidosis Diagnosis: T-Amylo. journal article 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 URL https://repisalud.isciii.es/bitstreams/0d46878e-f3ae-45c4-8974-50ef7ccdf237/download File MD5 55dd910979c07e1b33fec1e6196c6099 1220369 application/pdf Development and Validation of a Prediction Model_JACC Cardiovasc Imaging_2023.pdf URL https://repisalud.isciii.es/bitstreams/9c22015f-3ad6-48ed-88fb-0f2b08de0d14/download File MD5 d30fd29c4bff0531e33be88e86d52f49 55919 text/plain Development and Validation of a Prediction Model_JACC Cardiovasc Imaging_2023.pdf.txt