000168741 001__ 168741
000168741 005__ 20260217214838.0
000168741 0247_ $$2doi$$a10.1016/j.medcli.2025.107283
000168741 0248_ $$2sideral$$a147976
000168741 037__ $$aART-2026-147976
000168741 041__ $$aeng
000168741 100__ $$aPérez Abad, Laura$$uUniversidad de Zaragoza
000168741 245__ $$aUnlocking the potential of nailfold videocapillaroscopy in diagnosing and staging wild-type transthyretin amyloidosis: A preliminary approach
000168741 260__ $$c2026
000168741 5060_ $$aAccess copy available to the general public$$fUnrestricted
000168741 5203_ $$aBackground. Wild-type transthyretin amyloidosis (ATTRwt) is a serious condition. At early stages, symptoms resemble those of heart failure with preserved ejection fraction (HFpEF). Our aim was to perform software-supported nailfold videocapillaroscopy (NVC) analysis to identify hallmarks useful for diagnosis and build machine learning (ML)-based models to assess severity.
Methods. Thirty-two ATTRwt patients underwent NVC. Nineteen initiated TTR-stabilizing therapy and had a new NVC 12 months afterwards. Forty-one capillary-related variables were analyzed. Thirty NVCs were randomly chosen to train models to discriminate between poorer or less poor prognosis according to N-terminal pro-B-type natriuretic peptide (NT-proBNP) or Cheng score (cut-offs: 2000 pg/mL and 4 points, respectively). The remaining 21 NVCs were used for validation purposes. A control population of 99 patients with heart failure with preserved ejection fraction (HFpEF) but without signs of amyloidosis was included.
Results. A profound disorganization in the nailfold capillary architecture was generally observed. The models achieved accuracies of 0.81 and 0.90, respectively, in predicting disease severity. An additional model designed to distinguish a profile suggestive of amyloidosis (vs. HFpEF controls) achieved an accuracy of 0.73.
Conclusions. NVC-based ML models may contribute to early diagnosis and staging of ATTRwt.
000168741 536__ $$9info:eu-repo/grantAgreement/ES/IISAragón/GIIS-009$$9info:eu-repo/grantAgreement/ES/IISAragón/GIIS-084
000168741 540__ $$9info:eu-repo/semantics/embargoedAccess$$aby-nc-nd$$uhttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
000168741 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000168741 700__ $$0(orcid)0000-0002-1774-6488$$aAibar Arregui, Miguel Ángel
000168741 700__ $$aAramburu Llorente, Jimena
000168741 700__ $$aRamón y Cajal Calvo, Juan$$uUniversidad de Zaragoza
000168741 700__ $$0(orcid)0000-0003-3501-0121$$aAndrés Gracia, Alejandro$$uUniversidad de Zaragoza
000168741 700__ $$aRevilla Martí, Pablo$$uUniversidad de Zaragoza
000168741 700__ $$0(orcid)0000-0003-0715-2843$$aAtienza Ayala, Saida
000168741 700__ $$aLahuerta Pueyo, Carmen
000168741 700__ $$aCampos Sáenz de Santamaría, Amelia$$uUniversidad de Zaragoza
000168741 700__ $$aRamos Ibañez, Eduardo
000168741 700__ $$0(orcid)0000-0003-3248-2908$$aGracia Tello, Borja del Carmelo$$uUniversidad de Zaragoza
000168741 7102_ $$11011$$2770$$aUniversidad de Zaragoza$$bDpto. Microb.Ped.Radio.Sal.Pú.$$cÁrea Radiol. y Medicina Física
000168741 7102_ $$11007$$2610$$aUniversidad de Zaragoza$$bDpto. Medicina, Psiqu. y Derm.$$cArea Medicina
000168741 773__ $$g166, 2 (2026), 107283 [8 pp.]$$pMed. clín.$$tMedicina clinica$$x0025-7753
000168741 8564_ $$s294116$$uhttps://zaguan.unizar.es/record/168741/files/texto_completo.pdf$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2027-02-14
000168741 8564_ $$s1096121$$uhttps://zaguan.unizar.es/record/168741/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2027-02-14
000168741 909CO $$ooai:zaguan.unizar.es:168741$$particulos$$pdriver
000168741 951__ $$a2026-02-17-20:14:41
000168741 980__ $$aARTICLE