Challenging the guidelines: Longitudinal Trends in Left Ventricular Diameter and Function in Severe Aortic Regurgitation
Schwartzenberg, S.; Berkovitz, A.; Lerman, T. T.; Bental, T.; Vaturi, M.; Goldberg, Y.; Shapira, Y.
Show abstract
BACKGROUNDGuidelines recommend aortic valve replacement (AVR) in patients with severe aortic regurgitation (AR) based on progressive changes in left ventricular (LV) function or size. We aimed to reassess the clinical relevance of current guideline recommendations pertaining to traditional echocardiographic measurements in routine practice. METHODSRetrospective analysis of patients with severe AR who underwent serial echocardiographic follow-up over at least 18 months. The composite outcome was symptom-driven AVR, acute heart failure hospitalization, or death. We used a joint modelling approach to handle within-subject correlation and censoring. RESULTSThe cohort consisted of 140 patients, with a median follow-up of 93 months (interquartile range 58-130). LV end-systolic (LVESD) and fractional shortening (FS) showed a small but statistically significant longitudinal trend, while LVEDD did not. Changes in all three parameters in parallel joint models adjusted for age and gender were consistently associated with increased risk of the composite event. Each 1 mm increase in LVESD and LVEDD was associated with a 6% and 5% increase in risk, respectively; each 1% decrease in FS corresponded to a 12% increase in risk. Only 8 (5.7%) of patients were predicted to exceed the guideline-recommended LVEDD threshold of 65 mm over 10 years. Age at onset was also a significant risk factor, with each decade increasing risk by 65% for each of the three parallel joint models. CONCLUSIONSLV parameters show modest changes over time, despite holding strong prognostic value in patients with severe AR. LVEDD, while associated with overall risk, does not predictably or significantly dilate over time in most patients. AVR decisions should be based on comprehensive clinical and volumetric assessment rather than waiting for simple linear progression to guideline cutoffs.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Prognostic Value of Patient-Reported Outcomes in Predicting Long-term Mortality after Transcatheter Aortic Valve Replacement (TAVR) 96%
- Right Heart Remodeling After Pulmonary Valve Replacement in Patients with Pulmonary Atresia or Critical Stenosis with Intact Ventricular Septum 96%
- An International Longitudinal Natural History Study of Danon Disease Patients: Unique Cardiac Trajectories Identified Based on Sex and Heart Failure Outcomes 95%
Similar papers in this journal
- Decreased Diastolic Hydraulic Forces Incrementally Associate With Survival Beyond Conventional Measures of Diastolic Dysfunction 97%
- Left ventricular mass and global wall thickness – prognostic utility and characterization of left ventricular hypertrophy 97%
- Premature Ventricular Contractions During the Recovery Phase of Exercise Are Only Associated with Increased Cardiovascular Mortality when Present Together with Echocardiographic Abnormalities 96%
Similar papers in this journal
- Prognostic value of compact myocardial thinning in patients with left ventricular non-compaction 96%
- A Multicenter Evaluation of the Impact of Procedural and Pharmacological Interventions on Deep Learning-based Electrocardiographic Markers of Hypertrophic Cardiomyopathy 95%
- Sex-Related Outcomes of Transcatheter Aortic Valve Implantation with Self-Expanding or Balloon-Expandable Valves: Insights from the OPERA-TAVI Registry 95%
Similar papers in this journal
- Algorithm for Predicting Valvular Heart Disease from Heart Sounds in an Unselected Cohort 95%
- Autologous cardiac micrografts as support therapy to coronary artery bypass surgery 95%
- Fragmented QRS is independently predictive of long-term adverse clinical outcomes in Asian patients hospitalized for heart failure: a retrospective cohort study 95%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.