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Non-ischemic dilated cardiomyopathy (DCM) is a disease characterized by left ventricular dilation and systolic dysfunction. Patients with DCM are at higher risk for ventricular arrhythmias and sudden cardiac death (SCD). According to current international guidelines, left ventricular ejection fraction (LVEF) ≤ 35% represents the main indication for prophylactic implantable cardioverter defibrillator (ICD) implantation in patients with DCM. However, LVEF lacks sensitivity and specificity as a risk marker for SCD. It has been seen that the majority of patients with DCM do not actually benefit from the ICD implantation and, on the contrary, that many patients at risk of SCD are not identified as they have preserved or mildly depressed LVEF. Therefore, the use of LVEF as unique decision parameter does not maximize the benefit of ICD therapy. Multiple risk factors used in combination could likely predict SCD risk better than any single risk parameter. Several predictors have been proposed including genetic variants, electric indexes, and volumetric parameters of LV. Cardiac magnetic resonance (CMR) can improve risk stratification thanks to tissue characterization sequences such as LGE sequence, parametric mapping, and feature tracking. This review evaluates the role of CMR as a risk stratification tool in DCM patients referred for ICD.
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http://dx.doi.org/10.3390/jcm12247752 | DOI Listing |
Knee Surg Relat Res
September 2025
Florida Orthopaedic Institute, Gainesville, FL, 32607, USA.
Background: A clear understanding of minimal clinically important difference (MCID) and substantial clinical benefit (SCB) is essential for effectively implementing patient-reported outcome measurements (PROMs) as a performance measure for total knee arthroplasty (TKA). Since not achieving MCID and SCB may reflect suboptimal surgical benefit, the primary aim of this study was to use machine learning to predict patients who may not achieve the threshold-based outcomes (i.e.
View Article and Find Full Text PDFGeroscience
September 2025
Department of Emergency and Internal Medicine, Skåne University Hospital, Malmö, Sweden.
To evaluate a simplified version of the Clinical Frailty Scale (SCFS) among older adults presenting to the emergency department (ED) with acute dyspnea. In this retrospective single-center cohort study, we included patients from the Acute Dyspnea Study (ADYS) cohort. Severity of illness was assessed using the Medical Emergency Triage and Treatment System (METTS).
View Article and Find Full Text PDFGeroscience
September 2025
Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
This study aims to investigate the predictive value of combined phenotypic age and phenotypic age acceleration (PhenoAgeAccel) for benign prostatic hyperplasia (BPH) and develop a machine learning-based risk prediction model to inform precision prevention and clinical management strategies. The study analyzed data from 784 male participants in the US National Health and Nutrition Examination Survey (NHANES, 2001-2008). Phenotypic age was derived from chronological age and nine serum biomarkers.
View Article and Find Full Text PDFBr J Cancer
September 2025
Istituto Oncologico Veneto IOV-IRCCS, Padova, Italy.
The European Council recommends adopting risk-based screening when relevant. In triaging HPV-positive women, it can be an effective strategy to reduce overtreatment and referral to colposcopy. HPV genotyping and p16/ki67 expression may allow a better risk stratification than cytology.
View Article and Find Full Text PDFEur J Nutr
September 2025
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, PO Box 1627, 70211, Kuopio, Finland.
Purpose: To investigate how a group-based lifestyle intervention affects food choices and if the dietary patterns at the end of the intervention are associated with incidence type 2 diabetes (T2D). We also investigated if the possible associations between diet and T2D risk were modified by the genetic risk for T2D.
Methods: Participants in the T2D-GENE study were men with prediabetes aged 50-75 years, body mass index ≥ 25 kg/m, belonging in either low or high genetic risk score (GRS) tertile for T2D.