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Ann Thorac Surg 2008;85:2040-2045. doi:10.1016/j.athoracsur.2008.02.082
© 2008 The Society of Thoracic Surgeons
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Original Articles: Adult Cardiac

Gender Differences in Mortality After Mitral Valve Operation: Evidence for Higher Mortality in Perimenopausal Women

Howard K. Song, MD, PhDa,*, Joshua D. Grab, MSb, Sean M. O'Brien, PhDb, Karl F. Welke, MDa, Fred Edwards, MDc, Ross M. Ungerleider, MDa

a The Division of Cardiothoracic Surgery, Oregon Health & Science University, Portland, Oregon
b Duke Clinical Research Institute, Duke University, Durham, North Carolina
c Division of Cardiothoracic Surgery, University of Florida College of Medicine, Jacksonville, Florida

Accepted for publication February 27, 2008.

* Address correspondence to Dr Song, Division of Cardiothoracic Surgery, Oregon Health & Science University, Mail Code L353, 3181 SW Sam Jackson Park Rd, Portland, OR 97239 (Email: songh{at}ohsu.edu).

Presented at the Fifty-fourth Annual Meeting of the Southern Thoracic Surgical Association, Bonita Springs, FL, Nov 7–10, 2007.


   Abstract
Top
 Abstract
Introduction
 Patients and Methods
 Results
 Comment
 Discussion
 References
 
Background: Hormonal status is a potentially important cause for gender differences in outcomes after cardiovascular operations. Estrogen withdrawal states may potentiate ischemia–reperfusion injury by impairing endothelial cell function and increasing inflammatory cytokine levels. We hypothesized that gender influences mortality after mitral valve operations and that it varies with age, especially during periods of declining ovarian function.

Methods: We studied 24,977 patients (49% women) in The Society of Thoracic Surgeons National Database who underwent isolated mitral valve repair or replacement from 2002 to 2005. Age-related gender differences in mortality after mitral valve operation were compared by risk-adjusted analysis.

Results: Gender and age had a pronounced impact on hospital mortality. Women aged 40 to 49 and 50 to 59 had significantly greater hospital mortality than risk-matched men. The adjusted female/male odds ratio for hospital mortality in the group aged 40 to 49 was 2.56 (95% confidence interval, 1.31 to 5.01) but progressively decreased in the four subsequent age groups. This pattern was statistically significant (p = 0.028 and p = 0.018 for 40 to 49 vs 70 to 79 and 80 to 89, respectively) and represents a declining relative mortality risk for women of advanced age.

Conclusions: In patients aged 40 to 59 years, the mortality of mitral valve operation is approximately 2.5 times higher in women compared with men with similar risk factors. This survival disadvantage diminishes with further aging. Changes in ovarian function may be an important cause for this gender–age interaction and are a potential target for novel hormone-based therapies.


   Introduction
Top
 Abstract
 Introduction
Patients and Methods
 Results
 Comment
 Discussion
 References
 
Gender differences in outcomes after coronary artery bypass grafting (CABG) procedures have been well documented. Women have consistently been found to have poorer outcomes after CABG than men [1–11]. Initial studies focused on the higher incidence of risk factors found in women at the time of operation, such as advanced coronary artery disease, advanced age, diabetes, and renal insufficiency [1–4, 6–8, 10, 11]. Subsequent studies have found that female sex persists as an independent risk factor for adverse outcomes after CABG, even when these differences in presentation are taken into account [10, 12, 13]. More important, studies of gender differences in outcomes after CABG have focused predominantly on women of postmenopausal age because women have delayed onset of coronary artery disease and delayed presentation for CABG compared with men [1–4, 6–8, 10, 11].

Hormonal status is a potentially important cause for gender differences in outcomes after cardiovascular surgery. Experimental studies have consistently demonstrated that premenopausal women are protected against acute injuries such as myocardial infarction, stroke, burns, and hemorrhage [14–24]. This protective effect is mediated by ovarian hormones [16, 18, 25, 26]. Estrogen has numerous effects that modulate the inflammatory response to acute injury, such as reduced levels of tumor necrosis factor (TNF)-{alpha}, interleukin (IL)-1, and IL-6 [27–29, 23]. In contrast, estrogen withdrawal states, such as occur with perimenopause, may potentiate ischemia–reperfusion injury by impairing endothelial function, increasing endothelial cell apoptosis, and increasing levels of TNF-{alpha} and IL-6 [30–34].

In this study, we hypothesized that gender influences outcomes after mitral valve operation. We were particularly interested in studying outcomes of women undergoing mitral valve repair or replacement because of the relatively broad age range of patients undergoing this procedure, in contrast with CABG. Given the potential harmful effects of estrogen withdrawal, we further hypothesized that the gender influence may vary with age, especially during periods of declining ovarian function. The Society of Thoracic Surgeons (STS) National Cardiac Database was used because it provides a large and contemporary series of patients undergoing mitral valve intervention with pertinent associated clinical data.


   Patients and Methods
Top
 Abstract
 Introduction
 Patients and Methods
Results
 Comment
 Discussion
 References
 
This study was approved by the Institutional Review Board at Oregon Health and Science University. Individual consent for the study was waived.

Patient Population
We analyzed data on patients undergoing mitral valve replacement or mitral valve repair. We limited our analysis to 24,977 patients aged 30 to 89 who were not considered high risk, who were operated on from January 1, 2002, through June 30, 2005, at STS participant sites. High-risk patients were defined as having any of the following: an emergency or salvage operation or resuscitation, cardiogenic shock, myocardial infarction within 24 hours, or percutaneous coronary intervention within 6 hours. Patients who were receiving dialysis or who were in renal failure before their operation were excluded from the analysis of renal failure as an outcome.

Methods
We performed a retrospective analysis of patients undergoing mitral valve replacement or repair between 2002 and 2005 and enrolled in more than 600 hospitals participating in the STS National Database. Results are presented for hospital mortality; other investigated outcomes were stroke/coma, renal failure/dialysis, reintubation, prolonged ventilation, composite morbidity/mortality, and atrial fibrillation. The STS definitions for all patient variables and outcomes were used.

A logistic regression risk-adjustment model was constructed using a comprehensive set of covariates (Table 1) that were based on previously published STS valve models [35], with the addition of interaction between gender and age. Age was categorized to facilitate the inclusion of age–gender interaction into the model, using a separate term within each age category to estimate the effect of gender. This approach allowed estimation of odds ratios comparing men with women for each age group and testing for gender differences among the age groups.


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  		Table 1 Patient Characteristics and Operative Mortality Rates
 
Because patients within a hospital were more likely to be similar, all adjusted analyses were performed using generalized estimating equation models to account for correlations among clustered responses (eg, within-hospital correlations). The STS participating center, typically a single hospital or surgical group, was included in the model as the unit of clustering to account for this within-center correlation.

Finally, the overall time frame of the study population was divided into 6-month intervals to account for potential time-varying effects within the population, with the first 6 months of 2004 acting as the reference group. All analyses were performed using SAS 8.2 software (SAS Institute, Cary, NC).


   Results
Top
 Abstract
 Introduction
 Patients and Methods
 Results
Comment
 Discussion
 References
 
The study included 24,977 patients, 49% of whom were women. Men and women were subdivided into age decade groups to investigate a gender–age interaction. The distribution of patients in the 40s through 70s decades was fairly consistent, with 4052 to 5946 patients in each age decade. As expected, fewer patients were in the age decades 30 to 39 (n = 1517) and 80 to 89 (n = 1810).

Table 1 reports the incidence of selected adjustor variables and the hospital mortality rate associated with each variable. All variables other than year of operation had a highly significant association with mortality (p < 0.0001 for all variables).

Hospital mortality before risk adjustment was noted to be higher in women than men when patients were not subdivided by age (3.9% vs 2.4%). When women and men were subdivided by age decade, this difference was accentuated in the 40s and 50s age decades (1.7% vs 0.6% and 2.8% vs 1.2%, respectively).

A generalized estimating equation analysis was performed to determine if gender influenced outcomes in any age decade after mitral valve intervention. In addition to hospital mortality, other outcomes studied were stroke/coma, renal failure/dialysis, reintubation, prolonged ventilation, atrial fibrillation, and composite morbidity/mortality. No significant gender effects were exhibited for any outcomes except hospital mortality. Table 2 lists the model covariates with odds ratios and confidence intervals. Note that the effect of gender and age decade was modeled with three groups of terms for the age decades: a separate intercept term for each age group, a separate slope for each age group, and a set of gender difference terms for each age group, with our primary interest being in the latter set.


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  		Table 2 Operative Mortality Odds Ratio Estimates With 95% Confidence Intervals For Model Parameters
 
As reported in Table 2, a striking difference in risk-adjusted mortality was observed between genders in different age decades. Women in the 30- to 39-age-decade group had hospital mortality that was similar to that of risk-matched men. In contrast, women in the 40- to 49-age-decade group had approximately 2.5 times the mortality as risk-matched men, and this was a statistically significant finding. Women in the 50- to 59-age-decade group had approximately twice the mortality as risk-matched men, which also was statistically significant. The adverse effect of female gender on risk-adjusted mortality for subjects in the 40- to 49-age-decade group was exceeded only by the adverse effect associated with dialysis. In subsequent age decades, the risk for hospital mortality progressively declined, such that women and men aged in the decade groups 60 to 69, 70 to 79, and 80 to 89 had similar frequency of risk-adjusted hospital mortality.

Table 3 summarizes age group differences between the female/male odds ratios for hospital mortality. A {chi}2 analysis was performed to compare the hospital mortality female/male odds ratios of patients aged 40 to 49 years with patients in other age decades. This analysis confirmed that women aged 40 to 49 had a significantly higher relative risk for hospital mortality than women in the age groups 30 to 39, 70 to 79, and 80 to 89 (p = 0.0408, p = 0.0204, p = 0.0183, respectively).


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  		Table 3 Differences in Operative Mortality Female/Male Odds Ratios by Age Group a
 
Because of studies demonstrating that outcomes after mitral valve operation may be affected by whether mitral valve repair or replacement is performed, we became concerned that the differences in mortality seen in this study may be biased by the type of intervention [36, 37]. We therefore repeated the analysis using mitral valve replacement as an adjustor variable in addition to the comprehensive set of adjustor variables used in the original analysis (Table 2). None of the results of the original analysis were substantively changed by adding mitral valve replacement as an adjustor variable.


   Comment
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Comment
Discussion
 References
 
This study's focus on mitral valve operation outcomes allowed us to examine gender effects over a relatively broad age range. By segregating patients by gender and age decade, we were able to demonstrate an interaction between these two variables. Strikingly, the relative risk for operative mortality among women in their 40s rose to approximately 2.5 times that of men. Women in their 50s also had an increased relative risk for death that was approximately two times that of men. The odds ratios for operative mortality in subsequent age decades progressively declined, representing a declining relative mortality risk for women of advanced age.

Changes in ovarian function are a potential mechanism for this gender-age interaction. The median age of menopause is 51 years [38]. Menopause is typically preceded by a period of perimenopause that lasts several years, during which time ovarian production of estrogen is in decline [38]. Estrogen withdrawal states have been demonstrated to trigger changes in endothelial cell function and inflammatory responses that may potentiate ischemia–reperfusion injury and may contribute to the dramatic rise in risk for operative mortality among women of perimenopausal age demonstrated in this study [23, 27–29].

A major limitation of this study is that information on women's hormonal status is not available through the STS National Cardiac Database. Age was therefore used as a surrogate for ovarian function in this study. Although this is an imperfect approximation of hormonal status, it is notable that approximately 80% of women undergo menopause between the ages of 45 and 55, which corresponds with the striking increase in the relative risk for operative mortality among women [38]. The progressively lower relative mortality risk for women of advanced age is also consistent with the hypothesis that the estrogen withdrawal state associated with perimenopause may play a role in gender-specific operative mortality after mitral valve intervention.

Of interest was that other outcomes such as stroke, renal failure, prolonged ventilation, atrial fibrillation, and composite morbidity/mortality were not influenced by gender. The broad estrogen withdrawal effects postulated to affect operative mortality would also be expected to influence other outcomes that occur as a result of ischemia–reperfusion injury, such as stroke and renal failure. It is possible that our failure to detect a gender effect on these outcomes is related to under-reporting of nonfatal complications in the STS database. Operative mortality, as an unequivocal end point, is less likely to be under-reported.

Estrogen effects are being actively studied in a number of acute injury models. The broad array of modulatory effects of estrogen on the ischemia–reperfusion injury pathway may also be important in the context of cardiovascular operation. Understanding how ovarian function influences female outcomes after cardiovascular procedures may reveal opportunities for novel hormone-based therapies.


   Discussion
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Comment
 Discussion
References
 
DR THORALF SUNDT (Rochester, MN): Thanks very much, Howard. That was very nicely presented. They are intriguing data and it is a creative population to try and look at this problem that plagues us: understanding why mortality risks are higher in women than in men. If I understood Tara's data, that is even true in the congenital population. We see it over and over and over again, and we still don't understand it. Of course, the greatest weakness in your data is the lack of actual data about hormonal status, about menopausal status among the women. I suppose with the STS database there is no way around that, but that has to be recognized as a significant weakness.

Now, I am allowed two questions, so the first is, I actually share Dr Cerfolio's mistrust of sophisticated statistical methods that may hide more than they reveal, and so my naive question is, why did you choose this approach rather than a case-matched type approach. I admit it may be simplistic, but I would be more comfortable looking at cases that are matched rather than trusting the multivariable risk model to correct for everything else. There are so many unmeasured covariates given clinical decision making and so on that it is hard to allow for them all. So the first question is, would you have considered a matching-type design? You have got an enormous amount of data with the STS database.

And the second is the obvious one. What can you imagine is the mechanism for this? If estrogen's impact is ischemia–reperfusion and yet you saw no difference in stroke and you saw no difference in renal failure, what are these people dying of? What do you think is the mechanism? Thanks very much.

DR SONG: Thanks for your comments, Dr Sundt. To address your first comment about hormonal status not being part of the STS database, that is obviously the major weakness of our study. We tried to use age as basically a surrogate for that, and going through the gynecology literature, we were quite satisfied that the age range of 40 to 59 was quite consistent with perimenopausal status.

As far as the approach that was taken, we actually used a number of approaches—case-matched was not one of them—but we were finding that this pattern of a higher odds ratio for perimenopausal women was quite consistent regardless of the statistical approach that was taken or even the various set of adjuster variables that were used. So we were satisfied that this is a real result. It was primarily a difference in the degree of statistical significance, but the pattern was very consistent.

DR SUNDT: Any idea about the mechanism? If it has to do with ischemia–reperfusion, why was there no difference in renal failure?

DR SONG: Well, I think that we are looking at some of the limitations of the database. The nice thing about the mortality end point is it is a hard end point and it is consistently reported, I believe, whereas things like subclinical stroke or renal failure or prolonged intubation may be less reliable in the STS database.

DR J. SCOTT RANKIN (Nashville, TN): Very nice paper, as usual. The aspect of this presentation that is a little disconcerting is just going straight to the relative risk data. I would like to see the raw mortality, and then the risk-adjusted mortality, and then finally the relative risk, because this result could be obtained if the male mortality went down for that interval of time. So my question is, what happened with the raw mortality data? Did it progressively increase with age in each gender, but it increased more in the females over that period of time? What was going on?

DR SONG: I apologize for leaving that table out. It probably would have been a candidate for the Tiki award, though, if I put it all onto one slide. We do plan on publishing that in our full manuscript in the upcoming paper. I can tell you that the patterns we saw in the raw mortality figures paralleled what we saw after risk adjustment. The raw mortality for women in the fourth and fifth decades was 3 to 4 times that of men of similar age. So even just looking at unadjusted numbers, the mortality difference was quite striking.

DR FREDERICK GROVER (Denver, CO): That was a nice paper and I think it points out, I mean, there is no doubt I would think that there is a higher mortality in that group. The question is really, why is it, because the database, and as you look back you always wished in a way you had added certain variables, but I don't think we have in there the disease process itself that caused the mitral situation.

I think the value of a study like this is that you have identified a higher risk in that group of patients, and then you would hope that somebody will take it a step further and bore down more to find out what are the reasons. Is it a different etiology of their mitral disease, is it whatever? The thing that worries me about the concept of purely the estrogen is that you don't see the difference in the older age group later on. If it was persistent throughout, that would be interesting, and we also obviously don't know whether they are getting estrogen replacement. But I think it is something that stimulates further investigation. Thanks.


   References
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Comment
 Discussion
 References
 

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