Background: Use of the current echocardiography-based indications for aortic regurgitation (AR) surgery might result in late valve replacement at the stage of irreversible myocardial damage. Therefore, we aimed to identify simple models combining multiple echocardiography or magnetic resonance imaging (MRI)-derived indices and natriuretic peptides (BNP [brain natriuretic peptide] or NT-proBNP [N-terminnal pro-B type natriuretic peptide]) to predict early disease decompensation in asymptomatic severe AR.
Methods: This prospective and multicenter study included asymptomatic patients with severe AR, preserved left ventricular ejection fraction (>50%), and sinus rhythm. The echocardiography and MRI images were analyzed centrally in the CoreLab. The study end point was the onset of indication for aortic valve surgery as per current guidelines.
Results: The derivative cohort consisted of 127 asymptomatic patients (age 45±14 years, 84% males) with 41 (32%) end points during a median follow-up of 1375 (interquartile range, 1041-1783) days. In multivariable Cox regression analysis, age, BNP, 3-dimensional vena contracta area, MRI left ventricular end-diastolic volume index, regurgitant volume, and a fraction were identified as independent predictors of end point (all <0.05). However, a combined model including one parameter of AR assessment (MRI regurgitant volume or regurgitant fraction or 3-dimensional vena contracta area), 1 parameter of left ventricular remodeling (MRI left ventricular end-diastolic volume index or echocardiography 2-dimensional global longitudinal strain or E wave), and BNP showed significantly higher predictive accuracy (area under the curve, 0.74-0.81) than any parameter alone (area under the curve, 0.61-0.72). These findings were confirmed in the validation cohort (n=100 patients, 38 end points).
Conclusions: In asymptomatic severe AR, multimodality and multiparametric model combining 2 imaging indices with natriuretic peptides, showed high accuracy to identify early disease decompensation. Further prospective studies are warranted to explore the clinical benefit of implementing these models to guide patient management.
Registration: URL: https://www.
Clinicaltrials: gov; Unique identifier: NCT02910349.
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http://dx.doi.org/10.1161/CIRCIMAGING.122.014901 | DOI Listing |
J Med Internet Res
January 2025
Univ Rennes, CHU Rennes, INSERM, LTSI - UMR 1099, F-35000 Rennes, France.
Background: To reduce the mortality related to bladder cancer, efforts need to be concentrated on early detection of the disease for more effective therapeutic intervention. Strong risk factors (eg, smoking status, age, professional exposure) have been identified, and some diagnostic tools (eg, by way of cystoscopy) have been proposed. However, to date, no fully satisfactory (noninvasive, inexpensive, high-performance) solution for widespread deployment has been proposed.
View Article and Find Full Text PDFPLOS Digit Health
January 2025
Department of Mathematics & Statistics, York University, Toronto, Canada.
Chronic kidney disease (CKD) affects over 13% of the population, totaling more than 800 million individuals worldwide. Timely identification and intervention are crucial to delay CKD progression and improve patient outcomes. This research focuses on developing a predictive model to classify diabetic patients showing signs of kidney function impairment based on their CKD development risk.
View Article and Find Full Text PDFAnxiety Stress Coping
January 2025
Department of Psychology, Brandeis University, Waltham, MA, USA.
Background And Objective: Poor executive functioning (EF) has been consistently linked to depression, but questions remain regarding mechanisms driving this association. The current study tested whether poor EF is linked to depression symptoms six weeks later via dependent stressors (model 1) and stressors perceived to be uncontrollable (model 2) at week two (W2) and repetitive negative thinking (RNT) at W4 during early COVID-19 in college students.
Design: This was a longitudinal study with four timepoints spanning six weeks (April-June 2020).
Schizophr Bull
January 2025
Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China.
Background And Hypothesis: Identifying biomarkers at onset and specifying the progression over the early course of schizophrenia is critical for better understanding of illness pathophysiology and providing novel information relevant to illness prognosis and treatment selection. Studies of antipsychotic-naïve first-episode schizophrenia in China are making contributions to this goal.
Study Design: A review was conducted for how antipsychotic-naïve first-episode patients were identified and studied, the investigated biological measures, with a focus on neuroimaging, and how they extend the understanding of schizophrenia regarding the illness-related brain abnormality, treatment effect characterization and outcome prediction, and subtype discovery and patient stratification, in comparison to findings from western populations.
Ann Surg Oncol
January 2025
Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Background: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of infection. This study aimed to develop a machine-learning model to predict postoperative infection after cytoreductive surgery (CRS) and HIPEC with splenectomy.
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