Why the study?
Does age and prosthesis-patient mismatch impact long-term survival in patients undergoing aortic valve replacement?
Does age and prosthesis-patient mismatch impact long-term survival in patients undergoing aortic valve replacement?
Age is a significant predictor of long-term survival after aortic valve replacement, whereas categorized prosthesis-patient mismatch is not, though continuous effective orifice area index significantly affects survival.
Age predicts post-AVR survival while categorized PPM does not; continuous EOAi association is hypothesis-generating and needs prospective confirmation.
Aim: We studied the effect of age on survival in the setting of prosthesis-patient mismatch (PPM). Study Design: Retrospective single surgeon practice. Place and Duration of Study: Cardiothoracic department, Mater Dei Hospital Malta, between January 1995 and December 2014. Methodology: 572 consecutive patients undergoing aortic valve replacement (AVR) were divided into four age groups and followed up for a maximum of 20 years (mean 8.2). Date of death was derived from the National Statistics Office. PPM was classified according to defined criteria, and calculated according to manufacturers’ tables (in-vitro) and from in-vivo values published by independent researchers. The impact of age and PPM on long-term survival was studied using the Cox proportional hazard model. Results: Mean in-vitro derived indexed effective orifice area (EOAi) was significantly higher than in-vivo EOAi (1.04±0.22 vs 0.93±0.16, p=0.000) and incidence of PPM was lower using in-vitro criteria (moderate 18.0% vs 24.1%, p=0.01, severe 1.9% vs 4.7%, p=0.008). For patients with mismatch the odds of dying (in-vitro vs in-vivo) was increased by 9.2% vs 38.1%, with moderate PPM 7.6% vs 30.9%, and with severe PPM 85.7% vs 69.7%. The odds of dying increased with age (by 7-8% for every year) and PPM severity. Age was a significant predictor of survival but PPM was not. For every 0.1unit increase in EOAi the risk of dying decreased by 8.0% (in-vitro) and 8.7% (in-vivo). Conclusion: Age is a significant predictor of survival times, with the odds of dying increasing by about 7% for every additional year. Long-term survival hazard was increased by PPM but the effect was not significant. When EOAi is analysed as a continuous variable it significantly effects survival.
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Manché et al. (2016) studied this question.
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