Echocardiographic Nomogram Model: A Tool for Assessing Cardiac Involvement in Patients With Systemic Amyloidosis.
Objectives: Cardiac involvement is significantly relevant to a poor prognosis in patients with systemic amyloidosis, often leading to adverse outcomes. The objective of this study was to develop a diagnostic model for cardiac amyloidosis (CA) in primary light chain amyloidosis (pAL) to facilitate ea...
| Publicado en: | Echocardiography Vol. 42; no. 8; pp. 1 - 10 |
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| Autores principales: | , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Aug2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=187574150&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 187574150 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 07422822 GSE jtl: Echocardiography issn: 07422822 maglogo: Y pubinfo: dt: Aug2025 vid: 42 iid: 8 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 187574150 187574150 187574150 10.1111/echo.70252 187574150 ppf: 1 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Echocardiographic Nomogram Model: A Tool for Assessing Cardiac Involvement in Patients With Systemic Amyloidosis. aug: au: Lin, Qiongwen Li, Xiaoshan Tan, Zekun Xu, Ruixue Fei, Hongwen Chen, Oudi affil: Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou Guangdong Province, , China sug: subj: Heart Pathology Amyloidosis Prognosis Amyloidosis Complications Amyloidosis Radiography Echocardiography Methods Prediction Models Early Diagnosis Human Male Female Middle Age Aged Retrospective Design Record Review Magnetic Resonance Imaging Methods Risk Assessment Univariate Statistics Logistic Regression Random Forest Algorithms ROC Curve Sensitivity and Specificity Predictive Value of Tests Cardiac Output Ventricular Function Confidence Intervals T-Tests Data Analysis Software Descriptive Statistics Funding Source Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Objectives: Cardiac involvement is significantly relevant to a poor prognosis in patients with systemic amyloidosis, often leading to adverse outcomes. The objective of this study was to develop a diagnostic model for cardiac amyloidosis (CA) in primary light chain amyloidosis (pAL) to facilitate early detection and improve prognostic evaluation. Methods: In this retrospective study involving 72 patients with primary pAL amyloidosis (51 with cardiac involvement), we systematically employed cardiac magnetic resonance imaging (CMR) for cardiac assessment. CA diagnosis was confirmed histologically via noncardiac tissue biopsy, positive for light chain systemic amyloidosis. To dissect the risk factors for cardiac involvement, we applied both univariate logistic regression and a random forest algorithm. Subsequently, the findings from these analyses informed the construction of a predictive nomogram. We rigorously evaluated the nomogram's performance using receiver operating characteristic curve analysis, calibration curve assessment, and decision curve analysis. Results: The nomogram model included relative wall thickness (RWT), the ratio of mitral peak flow velocity in early diastolic (E wave) to the pulsed tissue Doppler imaging‐derived early diastolic peak velocity (e′ wave) at the interventricular septal mitral annulus (E/e′ sep), ejection fraction to peak systolic global longitudinal strain ratio (EFSR) and right ventricular fractional area change (RV FAC). The model exhibited good diagnostic performance, with an area under the ROC curve of 0.85 (95% CI, 0.75–0.92), a sensitivity of 80.4% (95% CI, 66.9%–90.2%), and a specificity of 85.7% (95% CI, 63.7%–97.0%). Conclusions: The nomogram provided a noninvasive and effective means of assessing cardiac involvement in systemic amyloidosis, offering a valuable aid for clinical decision‐making and patient management. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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