Alexander , Aaron A , and Liberato: Long-Term Survival Following Aortic Valve Replacement: The Influence of Age, Prosthesis-Patient Mismatch and Indexed Effective Orifice Area.


The concept of prosthesis-patient mismatch was introduced in 1978.[1] PPM occurs when the effective orifice area (EOA) of a prosthesis is too small for the patient’s body size, resulting in excessively high postoperative valve gradients.[2] Independent researchers evaluating valve performance in vivo by echocardiography have underlined the overestimation of EOA in tables[3,4] issued by valve manufacturers (based on in-vitro testing)[5,6] and this has resulted in revised valve specifications.[7]

Valve design has evolved from intra-annular implantation where the internal orifice diameter is smaller than the tissue annular diameter (TAD) to the introduction of supra-annular implantation where these diameters are equivalent.[8] This feature allows for supra-annular implantation of a larger valve for a fixed TAD, often of the magnitude of one valve size. Various additional design features such as the TopHat design,[4] a lower-profile sewing ring and external mounting of pericardial tissue contribute to a larger EOA.[9]

The improvements in EOA are based on the premise that inferior haemodynamics result in suboptimal clinical outcomes. Studies have linked PPM with persistent left ventricular hypertrophy, diastolic dysfunction and curtailed functional improvement.[10] Late cardiac complications [11] and accelerated degeneration of bioprostheses have also been reported.[12] However, in the setting of advancing age, the combined effects of these factors on survival remains unclear.[13,14]

Although age undoubtedly increases early and late mortality after aortic valve replacement, the direct effect of mismatch remains debatable.[15-17] We studied the effect of the interaction of age and mismatch as well as the influence of iEOA on long-term survival both as a continuous variable, and as a categorical determinant of moderate or severe PPM.


586 consecutive patients (61.6% male, mean age 63.6±12.0) undergoing AVR ±CABG between January 1995 and December 2016 in a single-surgeon’s practice were enrolled in the study and grouped according to age: 15-59 (n=148), 60-67 (n=145), 68-74 (n=149), 74 or more (n=144). Patients were excluded if they underwent transcatheter valve implantation or other procedures. Baseline patient characteristics as well as postoperative complications were recorded in the presence or absence of PPM (table 1). Mortality data was obtained from the National Statistics database. Patients were followed up for a mean of 7.8 years (median 7.3) up to a maximum of 20 years. The Hospital Scientific Ethical Committee waived the necessity for consent as the study was retrospective and patient data was anonymized. The study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki.

Surgery was performed in a standard fashion under normothermic bypass with antegrade cold cardioplegia. We used the internal thoracic artery supplemented by saphenous vein grafts when additional coronary bypass was necessary. No patient included in this series underwent root enlargement. Ninety three percent of patients below 70 received a mechanical valve whereas 96% of patients over 70 received a bioprosthesis. The choice of valves implanted evolved with the introduction of models with a larger EOA, potentially providing superior haemodynamics (table 2).

No PPM was defined as an indexed effective orifice area (iEOA) of >0.85cm2/m2, moderate PPM as 0.65-0.85cm2/m2 and severe as <0.65cm2/m2, and was calculated according to published data on valve EOA derived from independent researchers’ post-operative echocardiographic studies (table 3).

Statistical Methods

The student’s t-test was used to compare age groups with or without PPM. The Cox proportional hazard model was used to study the impact of age, iEOA and PPM category on long-term survival. Survival analysis was performed using the facilities of the Statistical Package for Social Sciences (SPSS, Inc, Chicago, IL) by using both a non-parametric approach (Kaplan-Meier estimates) and semi-parametric approach (Cox regression analysis). The Log-Rank (Mantel-Cox) test was used to determine whether the Kaplan Meier survival curves for different age-groups differed significantly at the 0.05 level.

Table 1.

Baseline patient characteristics and postoperative complications

parameter No PPM Yes PPM p value
n 419 167
age 65.87±11.69 63.35±10.61 0.016
female 155 (36.9%) 72 (42.9%) 0.180
urgent surgery 48 (11.4%) 21 (12.5%) 0.715
concomitant CABG 139 (33.1%) 59 (35.1%) 0.639
ejection fraction (%) 70.44±14.31 69.71±13.59 0.717
mean Parsonnet score 13.96±7.17 13.40±6.61 0.375
mean EuroScore 5.31±2.07 4.87±1.99 0.037
mean logistic EuroScore 5.02±3.94 4.26±3.00 0.046
mean hospital stay (survivors) 6.20±3.62 6.30±4.87 0.797
median ventilation time (hours) 8 7 0.387
patients transfused 118 (28.1%) 53 (31.5%) 0.405
mean transfusion volume (units) 1.26±2.41 1.11±2.20 0.576
mean haemorrhage volume (ml) 459.8±311.0 476.4±348.1 0.617
IABP usage 18 (4.3%) 4 (2.4%) 0.272
>24 hours inotropic support 116 (27.6%) 43 (25.6%) 0.618
atrial fibrillation/flutter 97 (23.1%) 47 (28.0%) 0.214

Table 2.

Valves implanted during the study period

valve size 1995-2001* 2002-2015**
mechanical 19, 21 CarboMedics Reduced CarboMedics TopHat
23 CarboMedics Standard CarboMedics TopHat
25 CarboMedics Standard CarboMedics Standard
bioprosthetic 19, 21, 23 Carpentier Edwards Perimount Sorin Mitroflow
25 Carpentier Edwards Perimount Carpentier Edwards Perimount/Magna

*11 St Jude Medical Toronto SPV valves inserted during this period

**7 Perceval valves inserted during this period


Baseline characteristics and postoperative complications in patients without or with PPM did not differ, except for logistic/ EuroSCORE risk, which was affected by age (table 1).

Table 3.

EOA values

valve model size19 EOA size 21 EOA size 23 EOA size 25 EOA reference source*
CarboMedics 1.0 1.54 1.63 1.98 [18,19]
Carpentier Edwards 1.1 1.5 1.8 1.8 [13,20,21]
Sorin Mitroflow 1.2 1.5 1.8 2.3 [13,22,23,24]
St Jude Medical Toronto SPV 1.3 1.5 1.7 [25]

*reference source refers to the publications quoting the EOA values used in this study

412 of 586 patients were alive at the completion of the study. The survival curves display the Kaplan-Meier survival probabilities for each age group against survival duration (figure 1). The log-rank test show that the Kaplan Meier survival curves of the four age-groups differ significantly when compared pairwise (table 4).

Figure 1:

Kaplan-Meier survival curves for the four age groups


Table 4.

Log-Rank (Mantel-Cox) test relating survival time to age

age groups Chi-Square df p value
group 1 versus group 2 11.607 1 0.001
group 1 versus group 3 30.722 1 0.000
group 1 versus group 4 66.560 1 0.000
group 2 versus group 3 4.360 1 0.037
group 2 versus group 4 28.157 1 0.000
group 3 versus group 4 13.345 1 0.000
four groups collectively 80.057 3 0.000

Figure 2:

Kaplan-Meier survival curves versus date of surgery (in five-year quartiles)


Table 5.

PPM incidence in five-year quartiles

period No PPM Yes PPM
1995-1999 89 37
70.6% 29.4%
2000-2004 117 49
70.5% 29.5%
2005-2009 93 36
72.1% 27.9%
2010-2015 120 45
72.7% 27.3%
total 419 167
71.5% 28.5%

X2(3) = 0.275, p = 0.965

Survival was also plotted and analysed in relation to operative date, in five-year quartiles (figure 2). There was no influence on survival and the incidence of PPM within these quartiles was similar (p = 0.965) (table 5).

140 patients received a size 25 valve, 202 patients received a size 23, 195 patients received a size 21, and 49 patients received a size 19 valve. The incidence of moderate PPM was 24.6% and severe PPM was 3.9% (figure 3). Mismatch was present in 167 patients and was more prevalent in younger patients. In fact, the mean age of patients with mismatch (63.35±10.61) was 2.52 years lower than their counterparts with no mismatch (65.87±11.69) and this difference is significant (p=0.016) (figure 4).

There was no correlation between PPM and perioperative mortality. There were 11 early deaths (1.9%), and of these, 10 patients had no PPM and one had moderate PPM. Seven patients who died underwent concomitant coronary grafting and 8 were over 70 years old, both recognized risk factors for increased perioperative mortality.

Survival probability was significantly affected by patient’s age with the hazard of dying increasing by around 7.3% for every incremental year. In patients with severe and moderate mismatch the hazards of dying were respectively 70.3% and 31.2% higher compared to patients with no PPM, but the increase was not statistically significant. In patients with mismatch the hazards of dying were 86.5% higher for 19mm valves, 68.7% for 21mm valves and 13.7% for 23mm valves compared to 25mm valves. These hazard ratios are not significant mainly because the incidence of mismatch was low, particularly for the larger valves. (table 6).

Table 6.

Cox regression relating survival time to age and PPM

parameter estimate SE Wald test p value Hazard Ratio 95% lower CI higher
age 0.0701 0.0092 58.06 0.000 1.073 1.053 1.092
severe PPM 0.5324 0.3251 2.682 0.101 1.703 0.901 3.221
moderate PPM 0.2715 0.2073 1.715 0.190 1.312 0.874 1.969
no PPM 0 1
size 19 PPM 0.6234 0.3584 3.026 0.082 1.865 0.924 3.765
size 21 PPM 0.5232 0.3143 2.771 0.096 1.687 0.911 3.124
size 23 PPM 0.1287 0.2927 0.193 0.660 1.137 0.641 2.019
size 25 PPM 0 1

SE: standard error, CI confidence interval

Mean iEOA was 0.94±0.15cm2/m2. When iEOA was analysed as a continuous parameter rather than a categorical parameter, a higher iEOA was associated with a significantly reduced hazard ratio of dying. The chance of survival increased by 8.8% for every 0.1 unit increment in iEOA (table 7).

In conclusion, age was a significant predictor of long-term survival whereas prosthesis-patient mismatch failed to exert a statistically significant effect. This situation applied for both moderate and severe mismatch and for all valve sizes used. In contrast long-term survival was affected by iEOA when this was analyzed as a continuous variable.

Figure 3:

Distribution of PPM by severity: gray moderate, black severe


Table 7.

Cox regression relating survival time to age and iEOA:

parameter estimate SE Wald test df p value Hazard Ratio 95% lower CI higher
age 0.0683 0.0082 69.38 1 0.000 1.071 1.054 1.088
iEOA -0.0921 0.0312 8.714 1 0.003 0.912 0.858 0.970

Wald test: used to test the true value of the parameter, based on the sample estimate df: degrees of freedom associated with each parameter estimate


Cardiac-related mortality was shown to be increased by prosthesis-patient mismatch in a meta-analysis of 34 observational studies published in 2012.[26] This analysis included a number of studies that failed to demonstrate a significant effect of PPM, amongst which were one study [27] with a longer mean follow-up (9.1 vs. 7.8 years) and a second [28] with a comparable follow-up (median of 7.3 vs. 7.3 years) to our study. Both these studies failed to show a significant effect on survival, raising the possibility that a longer follow-up may be salient. The authors stressed the value of preventing PPM, particularly in younger patients in whom long-term survival may be impacted to a greater extent.

The incidence of common postoperative complications was similar in patients with or without PPM. Certain complications have been shown, by multivariate analysis, to affect long-term outcome. [29] In this study risk stratification was higher by logistic (p=0.046) and additive EuroSCORE (p=0.037) in patients without PPM because this group was older by 2.52 years, age being a contributor to the score. The incidence of mismatch is higher in younger patients and this may attenuate its effect on survival. Follow-up duration is inversely proportional to advancing age at operation. Studies with a longer follow-up have failed to demonstrate a deleterious effect of mismatch. The combined effect of a younger age and a longer follow-up may overshadow the importance of mismatch in determining long-term survival. Although mismatch leads to adverse cardiac events its effect on survival is reduced by advancing age.[29] Our results suggest that age, and its direct effect on follow-up duration, significantly affects survival whereas mismatch does not.

A long follow-up necessarily entails evolving practices including the implantation of novel valves that may significantly affect survival. Analysis of survival by operative date, in four five-year quartiles, showed no significant difference in survival in these groups.

When valve haemodynamics are translated into a continuum of iEOA a significant effect on long-term survival becomes evident. This relationship failed to reach statistical significance with mismatch because of the low incidence of moderate PPM, and the very low incidence of severe PPM. All data pertaining to valve EOA was obtained from published studies and not from our own post-operative measurements. These values should be readily available in theatre and act as a guide to the surgeon implanting an aortic prosthesis with the goal of avoiding mismatch. Our study suggests that the largest size valve with the best possible EOA should always be implanted. In extreme circumstances of a small aortic root, enlargement may be performed. However, the increased operative risk of this procedure has not been shown to benefit long-term survival.[30]

Figure 4:

Distribution of PPM by age



The data was derived from a single surgeon’s practice and may not be representative of a wider population. A change in the use of certain valve models during the study period may have influenced the outcome. The low incidence of mismatch may have been a factor limiting statistical significance.


PPM, whether moderate or severe, did not significantly curtail long-term survival. A larger iEOA increased survival by 8.8% per 0.1 unit increase. Age exerted a significant effect on survival, reducing it by 7.3% for each incremental year.

Declarations of interests

The authors declare no conflict of interest.


The authors agree to abide by the requirements of the “Statement of publishing ethics of the International Cardiovascular Forum Journal.[31]



Rahimtoola SH The problem of valve prosthesis-patient mismatch. Circulation 1978; 58: 20–20 10.1161/01.CIR.58.1.20


Zoghbi WA, Chambers JB, Dumesnil JG, Foster E, Gottdiener JS, Grayburn PA et al Recommendations for evaluation of prosthetic valves with echocardiography and Doppler ultrasound. J Am Soc Echocardiograph 2009; 9: 975–975 10.1016/j.echo.2009.07.013




Pibarot P, Dumesnil JG, Lemieux M, Cartier P, Metras J, Durand LG Impact of prosthesis-patient mismatch on hemodynamic and symptomatic status, morbidity and mortality after aortic valve replacement with a bioprosthetic heart valve. J Heart Valve Dis 1998; 7: 211–211


Cohen RG, Bourne ET Industry-generated charts for the selection of stented aortic valve prostheses: clinical tool or marketing ploy?. Ann Thorac Surg 2011; 91: 1001–1002 10.1016/j.athoracsur.2011.01.051


Dumesnil JG, Honos GN, Lemieux M, Beauchemin J Validation and applications of indexed aortic prosthetic valve areas calculated by Doppler echocardiography. J Am Coll Cardiol 1990; 16: 637–637 10.1016/0735-1097(90)90355-S


Gillinov AM, Blackstone EH, Alster JM, Craver JM, Baumgartner WA, Brewster SA, Kleinman LH, Smedira NG The CarboMedics Top Hat supraannular aortic valve: a multicenter study. Ann Thorac Surg 2003; 75: 1175–1175


Jamieson WR, Koerfer R, Yankah CA, Zittermann A, Hayden RI, Ling H, Hetzer R, Dolman WB Mitroflow aortic pericardial bioprosthesis – clinical performance. Eur J Cardiothorac Surg 2009; 36: 818–818 10.1016/j.ejcts.2009.05.020


Pibarot O, Dumesnil JG Prosthesis-patient mismatch: definition, clinical impact, and prevention. Heart 2006; 92: 1022–1022 10.1136/hrt.2005.067363


Tasca G, Mhagna Z, Perotti S, Centurini PB, Sabatini T, Amaducci A, Brunelli F, Cirillo M, Dalla Tomba M, Quaini E, Troise G, Pibarot P Impact of prosthesis-patient mismatch on cardiac events and midterm mortality after aortic valve replacement in patients with pure aortic stenosis. Circulation 2006; 113: 570–570 10.1161/CIRCULATIONAHA.105.587022


Flameng W, Herregods MC, Vercalsteren M, Herijgers P, Bogaerts K, Meuris B Prosthesis-patient mismatch predicts structural valve degeneration in bioprosthetic heart valves. Circulation 2010; 121: 2123–2123 10.1161/CIRCULATIONAHA.109.901272


Pibarot P, Dumesnil JG Hemodynamic and clinical impact of prosthesispatient mismatch in the aortic valve position and its prevention. J Am Coll Cardiol 2000; 36: 1131–1131 10.1016/S0735-1097(00)00859-7


Blackstone EH, Cosgrove DM, Jamieson WR, Birkmeyer NJ, Lemmer JH jr, Miller DC, Butchart EG, Rizzoli G, Yacoub M, Chai A Prosthesis size and long-term survival after aortic valve replacement. J Thorac Cardiovasc Surg 2003; 126: 783–783 10.1016/S0022-5223(03)00591-9


Asimakopoulos G, Edwards MB, Taylor KM Aortic valve replacement in patients 80 years of age and older. Survival and cause of death based on 1100 cases: Collective results from the UK Heart Valve Registry. Circulation 1997; 96: 3403–3408 10.1161/01.CIR.96.10.3403


Brennan JM, Edwards FH, Zhao Y, O’Brien SM, Douglas PS Peterson ED on behalf of the Developing Evidence to Inform About Effectiveness 2013; Aortic Valve Replacement (DEcIDE AVR) research team. Long-term survival after aortic valve replcement among high-risk elderly patients in the United States. Insights from the Society of Thoracic Surgeons Adult Cardiac Surgery Database, 1991 to 2007. Circulation 2012; 126: 1621–1629 10.1161/CIRCULATIONAHA.112.091371


Mrowczynski W, Lutter G, Attmann T, Hoffmann G, Quaden R, Cremer J, Boning A Does patient-prosthesis mismatch influence the results of combined aortic valve replacement and coronary bypass grafting?. Kardiol Pol 2009; 67: 865–873


Chambers J, Cross J, Deverall P, Sowton E Echocardiographic description of the CarboMedics bileaflet prosthetic heart valve. J Am Coll Cardiol 1993; 21: 398–398 10.1016/0735-1097(93)90681-P


Mosquera VX, Bouzas-Mosquera A, Bautista-Hernandez V, Estévez-Cid F, Herrera-Noreña JM, Alvarez-García N, Cuenca-Castillo JJ The CarboMedics supra-annular Top Hat valve improves long-term left ventricular mass regression. J Thorac Cardiovasc Surg 2014; 148: 2845–2845 10.1016/j.jtcvs.2014.06.082


Wiseth R, Levang DW, Sande E, Tangen G, Skjaerpe T, Hatle L Hemodynamic evaluation by Doppler echocardiography of small (≤21mm) prostheses and bioprostheses in the aortic valve position. Am J Cardiol 1992; 70: 240–240


Botzenhardt F, Eichinger WB, Guenzinger R, Bleiziffer S, Wagner I, Bauernschmitt R, Lange R Hemodynamic performance and incidence of patient-prosthesis mismatch of the complete supraannular perimount magna bioprosthesis in the aortic position. The Thoracic and Cardiovascular Surgeon 2005; 53: 226–226 10.1055/s-2005-837678


Bleiziffer S, Eichinger WB, Hettich IM, Ruzicka D, Badiu CC, Guenzinger R, Bauernschmitt R, Lange R Hemodynamic characterization of the Sorin Mitroflow pericardial bioposthesis at rest and exercise. J Heart Valve Dis 2009; 18: 95–95


Jamieson WR, Koerfer R, Yankah CA, Zittermann A, Hayden RI, Ling H et al Mitroflow aortic pericardial bioprosthesis – clinical performance. Eur J Cardiothorac Surg 2009; 36: 818–818 10.1016/j.ejcts.2009.05.020


Yankah CA, Pasic M, Musci M, Stein J, Detschades C, Siniawski H, Hetzer R Aortic valve replacement with the Mitroflow pericardial bioprosthesis: durability results up to 21 years. J Thorac Cardiovasc Surg 2008; 136: 688–688 10.1016/j.ejcts.2008.05.022


Del Rizzo DF, Goldman BS, Christakis GT, David TE Hemodynamic benefits of the Toronto stentless valve. J Thorac Cardiovasc Surg 1996; 112: 1431–1431 10.1016/S0022-5223(96)70001-6


Head SJ, Mokhles MM, Osnabrugge RL, Pibarot P, Mack MJ, Takkenberg JJ, Bogers AJ The impact of prosthesis-patient mismatch on long-term survival after aortic valve replacement: a systematic review and metaanalysis of 34 observational studies comprising 27186 patients with 133141 patient-years. Eur Heart J 2012; 33: 1518–1518 10.1093/eurheartj/ehs003


Tsutsumi K, Nagumo M, Nishikawa K, Takahashi R Effect of prosthesispatient mismatch on survival after aortic valve replacement using mechanical prostheses in patients with aortic stenosis. Gen Thorac Cardiovasc Surg 2008; 56: 577–577 10.1007/s11748-008-0317-9


Frapier JM, Rouviere P, Razcka F, Aymard T, Albat B, Chaptal PA Influence of patient-prosthesis mismatch on long-term results after aortic valve replacement with a stented bioprosthesis. J Heart Valve Dis 2002; 11: 543–543


Manché A, Camilleri L, Gauci D Dies aortic valve replacement restore normal life expectancy: a twenty-year relative survival study. International Cardiovascular Forum Journal 2016; 6: 46–53 10.17987/icfj.v6i0.138


Kulik A, Al-Saigh M, Chan V, Masters RG, Bedard P, Lam BK et al Enlargement of the small aortic root during aortic valve replacement: is there a benefit?. Ann Thorac Surg 2008; 85: 94–100 10.1016/j.athoracsur.2007.07.058


Shewan LG, Coats AJS, Henein M Requirements for ethical publishing in biomedical journals. International Cardiovascular Forum Journal 2015; 2: 2 10.17987/icfj.v2i1.4

Copyright (c) 2017 The authors

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.