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Ann Thorac Surg 2006;81:481-489
© 2006 The Society of Thoracic Surgeons
Division of Cardiothoracic Surgery, Washington University School of Medicine, St. Louis, Missouri
Accepted for publication July 26, 2005.
* Address correspondence to Dr Moon, Division of Cardiothoracic Surgery, Washington University School of Medicine, 3108 Queeny Tower, 1 Barnes-Jewish Plaza, St. Louis, MO 63110-1013 (Email: moonm{at}msnotes.wustl.edu).
Presented at the Forty-first Annual Meeting of The Society of Thoracic Surgeons, Tampa, FL, Jan 24–26, 2005.
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Abstract |
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METHODS: Over a 12-year period, 1,400 consecutive patients underwent bioprosthetic (933 patients) or mechanical (467) aortic valve replacement. Prosthesis-patient mismatch was defined as prosthetic effective orifice area/body surface area less than 0.75 cm2/m2 and was present with 11% mechanical and 51% bioprosthetic valves.
RESULTS: With bioprosthetic valves, prosthesis-patient mismatch was associated with impaired survival for patients less than 60 years old (10-year: 68% ± 7% mismatch versus 75% ± 7% no mismatch, p< 0.02) but not older patients (p= 0.47). Similarly, with mechanical valves, prosthesis-patient mismatch was associated with impaired survival for patients less than 60 years old (10-year: 62% ± 11% versus 79% ± 4%, p < 0.005) but not older patients (p = 0.26). For small patients (body surface area less than 1.7 m2), prosthesis-patient mismatch did not impact survival with bioprosthetic (p = 0.32) or mechanical (p= 0.71) valves. For average-size patients (body surface area 1.7 to 2.1 m2), prosthesis-patient mismatch was associated with impaired survival with both bioprosthetic (p < 0.05) and mechanical (p< 0.005) valves. For large patients (body surface area greater than 2.1 m2), prosthesis-patient mismatch was associated with impaired survival with mechanical (p< 0.04) but not bioprosthetic (p= 0.40) valves.
CONCLUSIONS: Prosthesis-patient mismatch had a negative impact on survival for young patients, but its impact on older patients was minimal. In addition, although prosthesis-patient mismatch was not important in small patients, prosthesis-patient mismatch negatively impacted survival for average-size patients and for large patients with mechanical valves.
The impact of prosthesis-patient mismatch (PPM) after aortic valve replacement (AVR) remains controversial. Previous investigators have suggested that PPM may result in higher transvalvular gradients, blunted left ventricular (LV) mass regression, and increased early and late morbidity and mortality [1–7]. Others, however, have suggested that prosthesis size may play a lesser role in determining survival in the late postoperative period [8–11], but the use of internal orifice diameter to quantify effective valve size in some of these studies and a lack of subgroup analysis have led some to question the clinical applicability of these findings [5, 6, 12, 13].
Intuitively, implantation of a small valve in a large patient is not ideal, but it remains unknown in which patients the impact of an "undersized" valve would be most detrimental. Long-term survival after AVR has also been related to patient age and body size [5, 8, 14–17], but the role of these factors in determining the impact of PPM on late survival remains unclear [3, 5, 6, 8, 11, 18]. Two important clinical questions are as follows: (1) In which subgroups of patients is it necessary to upsize an aortic prosthesis to avoid PPM? (2) In which subgroups of patients does PPM not impact survival, such that a "get in and get out" approach would be most appropriate? The purpose of the current investigation was to identify patient subgroups in which PPM most influenced late survival; specifically, the impact of patient age and body size was examined.
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Material and Methods |
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Survival data were obtained for all 2004 patients during a 2-month closing interval ending August 2004 through interrogation of the Barnes-Jewish Hospital medical records database and the Social Security Death Index, which has been shown to be highly specific (99.5%) and unbiased [42]. Cumulative long-term follow-up totaled 5,194 patient-years. Mean follow-up for all patients was 45 ± 37 months, and 947 patients (68%) were alive an average of 52 ± 37 months postoperatively.
Data Analysis
Operative mortality included any death that occurred during the initial hospitalization or within 30 days of operation for discharged patients. Late survival data included death from all causes. Continuous data are reported as mean ± 1 SD and were compared between groups using Student's t test or analysis of variance as appropriate. Clinically important ratios are reported with 95% confidence limits. Actuarial survival estimates were calculated using the Kaplan-Meier method and were compared using the log-rank test. Variability of the actuarial estimates is expressed as ± 1 SEM. Univariate and multivariate analysis were used to determine the preoperative and intraoperative risk factors that were significant, independent predictors of operative mortality and late death (SigmaStat 2.03; SPSS, Chicago, Illinois). Univariate analysis was performed for categorical variables using the 
2 test and for continuous variables using linear regression. Multivariate analysis was performed using stepwise backward regression including only factors identified to be significant during univariate analysis (p < 0.05). Odds ratios (OR) are reported with 95% confidence intervals (CI).
Twenty-four variables were analyzed: age; year of operation; sex; hypertension; diabetes; pulmonary disease; cerebrovascular disease; peripheral vascular disease; chronic renal insufficiency; history of myocardial infarction; smoking history; family history of coronary disease; congestive heart failure; ejection fraction; status (urgent, elective); ascending aortic aneurysm; endocarditis; New York Heart Association (NYHA) class; previous cardiac operation; concomitant coronary artery bypass grafting; concomitant mitral repair or replacement; valve type (mechanical, bioprosthetic); BSA (small, average, large); and PPM (EOA / BSA < 0.75 cm2/m2).
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Results |
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Operative Mortality
Operative mortality for patients included in the PPM analysis was 8.3% ± 1.4% overall (116 of 1,400 patients); 9.8% ± 2.5% (52 of 528) with PPM and 7.3% ± 1.7% (64 of 872) without PPM (p = 0.12). The difference in operative mortality between PPM and no PPM was not significant with either bioprosthetic (p = 0.28) or mechanical (p = 0.68) AVR (Table 2). The causes of operative death in 52 patients with PPM were cardiac (n = 33), pulmonary (n = 5), infection (n = 5), and other (n = 9). The causes of operative death in 64 patients without PPM were cardiac (n = 44), pulmonary (n = 7), infection (n = 6), and other (n = 7). Univariate analysis identified 13 factors associated with operative mortality (Table 3), of which multivariate analysis identified 9 factors to be independent predictors of operative mortality:: advanced age, chronic renal insufficiency, peripheral vascular disease, congestive heart failure, endocarditis, concomitant mitral procedure, previous cardiac surgery, urgent or emergent status, and NYHA class IV (Table 3).
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Comment |
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The current findings demonstrate that PPM is a size- and age-dependent phenomenon. In patients receiving mechanical valves, PPM should be avoided in average-size or large patients, especially if they are young. Patients with BSA greater than 2.1 m2 had a dramatic fall in survival from 78% to 25% with PPM, whereas patients with BSA less than 1.7 m2 did not experience the same response with PPM. In patients receiving bioprosthetic valves, the data suggest that PPM should be avoided in average-size patients as 10-year survival diminished from 40% to 23%, but smaller and larger patients did not demonstrate a similar decline in survival. With both mechanical and bioprosthetic AVR, young patients were more prone to experience the negative impact of PPM on late survival than were older patients.
In an elegant, large, multicenter retrospective study, Blackstone and coinvestigators [11] found increased operative mortality, but no change in late survival with diminished valve-to-patient sizing; however, internal orifice diameter was used instead of EOA to quantify prosthesis size. This approach has limitations when comparing various mechanical and bioprosthetic valves that may have the same internal orifice diameter but widely varying flow patterns and opening characteristics [5, 6, 12, 13]. Similar to the Blackstone study, the current report focused on survival alone, not taking into account left ventricular mass regression or late functional status [2, 5, 7, 33, 43]. It is likely that PPM also impacts these two important endpoints. Reul and colleagues [7] found that PPM was independently associated with persistent or recurrent congestive heart failure in the late postoperative period. They did not identify an impact of PPM on late mortality, but subgroup analysis based on age and body size was not performed.
Blais and associates [6] examined the impact of PPM on operative mortality in 1,266 patients collected over 10 years. They quantified PPM as absent (greater than 0.85 cm2/m2), moderate (0.65 to 0.85 cm2/m2), or severe (less than 0.65 cm2/m2). Moderate or severe PPM was present in 38% of their patients, similar to the current series. Operative mortality for the entire series was 4.6% but increased significantly from 3% without PPM to 6% with moderate PPM and 26% with severe PPM. In the current report, when the analyses were performed using other EOA/BSA values as the PPM cutoff point, the impact on late survival was similar. The impact of PPM is likely linear, rather than binary. Below a critical level of PPM, which likely varies for each subgroup identified to be at increased risk with PPM, the impact of PPM increases as the mismatch becomes more severe. However, whether one chooses a cutoff value for PPM of 0.75 cm2/m2, 0.85 cm2/m2, or 1.0 cm2/m2, the impact of age and body size is similar. When a cutoff value of 1.2 cm2/m2 was employed, the impact of PPM on late survival was no longer significant in most subgroups.
Study Limitations
The current study was subject to all the limitations inherent to a retrospective, nonrandomized comparison of surgical results, including selection bias as to which patients received which prostheses during valve replacement. Multivariate analysis was used to help account for selection bias and other confounding risk factors, but the possible impact of undersizing valves in sicker patients to "get in and get out" may have influenced the results. We were not surprised that PPM was not an independent predictor of operative mortality (p = 0.14) or late death (p = 0.07) in the initial univariate and multivariate analyses. That is consistent with our impression that PPM is not important in all patients. It was our initial impression that analysis of the entire group was not what was going to be of interest, and that is why we additionally focused on specific subgroups of patients that we thought were of most clinical interest (body surface area, age, and mechanical versus bioprosthetic recipients).
This series included 1,400 patients who underwent AVR by 21 different surgeons over a 12-year period. Some may consider such diversity a limitation of the study because of a lack of a consistent approach to the patient with a small aortic root, but we believe that our data may better predict the expected outcome for a given patient and a given surgeon in practice than does a similar series from a single surgeon or from a center with a standard surgical approach.
In the current report, late functional status and quality of life were not assessed and left ventricular mass regression was not evaluated with postoperative echocardiographic data. The goal of the current study was to identify in which patient subgroups late survival was most affected by PPM and in whom consideration of advanced surgical techniques to increase valve size during AVR may be warranted on a survival basis. We made no attempt to correlate PPM findings with functional status or symptomatic improvements. Previous reports have suggested that PPM may impact each of these parameters and that larger valves are associated with improved LV mass regression and improved functional status [2, 5, 7]. Further analysis would be required to assess these findings in our series in which postoperative echocardiography data was inconsistent.
In summary, the current findings demonstrated that PPM is a real phenomenon and can impact late survival in selected patients. With an EOA/BSA ratio of 1.2 cm2/m2, PPM was not present in any subgroup. However, with an EOA/BSA ratio of 0.75 cm2/m2, PPM had a significant negative impact on survival in average-size and large patients, especially if they were young. Thus, it is in these patients that we should focus our attempts to improve prosthesis-patient matching [31–33, 45], while adopting a less aggressive approach in small, elderly patients [8, 13, 18]. Castro and associates [45] demonstrated that an aggressive approach to aortic root enlargement can decrease the incidence of PPM from 17% to 3% without a significant rise in operative mortality. However, while the increased perioperative mortality rate that surely accompanies more complex procedures in most hands may be warranted in young patients of average size or greater, small patients, especially when elderly, may be better served with a "get in and get out" approach, as PPM does not appear to have a significant impact on late survival.
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Discussion |
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DR MOON: Well, St. Jude or Carbomedics. I did the analysis with 0.65, 0.75, 0.85, 1, 1.1, 1.2, 1.4. The results were similar when we used 0.75, 0.85, and 1. When we went to the extremes, though, the numbers in the groups became so small, especially with mechanical valves, we had very few mechanical patients that were less than 0.65. So that is why we picked 0.75 as our cutoff point. As I mentioned, prosthesis-patient mismatch is probably not a binary effect but more of a linear effect and the results may be different with various levels.
DR BOLLING: But even given that, please explain how you would have a different conclusion from the previous paper.
DR MOON: Overall in our mechanical patients when we had patient-prosthesis mismatch less than 0.75, we had diminished survival. At 0.65, when I redid the analysis, in our series anyway, our numbers of patients were quite small and none of our differences came out statistically significant. So I think with more numbers and more power maybe these small differences can come out. We put in a lot of bioprosthetic valves, especially in older patients, and maybe in their series it was a little bit older. It is hard to say.
DR ROBERT W. M. FRATER (Bronxville, NY): The value for your effective orifice area is, I presume, a derived EOA from echocardiography, and I wonder whether the ventricle has any idea of what an EOA is. What the ventricle notices is the pressure generated in order to open the valve and eject. Do you have any data on left ventricular pressure in the patients who were supposed to have patient-prosthesis mismatch?
DR MOON: The short answer is no, I don't have any specific data. I have looked at some small subsets of recent patients in whom we do have data, and I have found substantial differences in the gradients, but we don't have any consistent data on that, especially for the valves, and it makes it difficult to compare all the different types of valves. They have all been studied in different ways, in vitro, in vivo. I tried to pick studies to use for our reference values that appeared to be unbiased, and any studies that had values that were way out of whack, I essentially didn't use.
DR W. R. ERIC JAMIESON (Vancouver, British Columbia): A question with regard to your biological population. In the United States, it has only been in the last few years that you have had the advanced bioprosthetic valves, the SupraAnnular type valves to implant. What percentage of your population of bioprostheses were old standard Hancocks and standard Edwards? There has been a tremendous advance in the use of bioprostheses in the United States in the last year or so, up to 77%. We have to take these data with some consideration that your old valves are contributing to your biological results.
DR MOON: One nice thing about using the effective orifice area and having a series that is so old is that we have got patients and valves all over the map. Any given valve can have any given effective orifice area, and if we take a new SupraAnnular 17 valve, it is probably no better than a 21 porcine Hancock. We don't have to know the specifics. All we have to know is the effective orifice area in order to compare the effects of the mismatch. Obviously, we will have mismatch less often now with the new SupraAnnulars that have better flow characteristics than we did in the past.
DR ROBERT W. EMERY (St. Paul, MN): That was a very nice presentation. The differences in our two series are interesting. In thinking about this, three things seem to differentiate what we both reported and may offer some answers. One is duration of follow-up. In a 10-year follow-up, there has not been enough time for biologic valves to degenerate. If you look at Steve Kahn's 20-year follow-up between mechanical and tissue valves, the incidence curves cross at 10 years and the incidence of valve-related complications are higher in the latter 10 years in tissue valves, predominantly due to valve failure. That may be an answer to one of the differences in what we are seeing things.
The second is our surgical technique was very consistent, because basically all of us were taught by Dr Nicoloff. So for 25 years, the members of our group were using standard interrupted mattress sutures in the aortic annulus and just changed a little bit the number of sutures to make the valves fit with the diameter-enhanced model. So we had a very consistent surgical approach, and in your series there were 26 different surgeons and a multiple admixture of both mechanical and biologic valves; it may be that one type of valve or one surgical technique contributed to the different in our results.
The third issues is that we followed only one valve type whereas your report contains multiple valve models.
DR MOON: I agree with you one hundred percent. One thing we found amazingly when we looked at the data was how low our 10-year survival was for patients all across the board: patients just don't live as long as we think they are going to. And so to make a 30-year decision in an older patient is probably not warranted. And I agree, we did have quite a diverse group, and all of my partners and previous partners know, none of us did anything the same.
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