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Eur J Cardiothorac Surg 2003;23:696-702
© 2003 Elsevier Science NL

Left ventricular mass index in aortic valve surgery: a new index for early valve replacement?

Rafael García Fuster*, José A. Montero Argudo, Oscar Gil Albarova, Fernando Hornero Sos, Sergio Cánovas López, Ma José Dalmau Sorlí, María Bueno Codoñer, José A. Buendía Miñano

University General Hospital of Valencia, Ar. Tres Cruces s/n 46104 Valencia, Spain

Received 1 September 2002; received in revised form 29 January 2003; accepted 4 February 2003.

* Corresponding author. C/Artes Gráficas n°4, esc. izq. pta. 3, 46010 Valencia, Spain. Tel.: +34-96-362-2216
e-mail: rgfuster{at}terra.com


   Abstract
Top
 Abstract
1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 References
 
Objective: Increased left ventricular mass index has been associated with higher mortality. We analyze the effect of increased left ventricular mass index on outcomes in patients undergoing aortic valve replacement. Methods: Echocardiographic left ventricular dimensions were used to calculate left ventricular mass index in 614 patients who underwent aortic valve replacement between June 1993 and November 2001. Left ventricular mass index was considered increased if higher than the value of the superior decile (277 g/m2 in males and 251 in females). Results: Mean left ventricular mass index was: 178±111 g/m2, and increased index was considered in 9.9% of patients. Postoperative complications (low cardiac output syndrome, respiratory failure, arrhythmias, pneumonia and mediastinitis), median length of hospital stay: 12 days (6–57) versus 11 days (5–51), and in-hospital mortality (11.4, 3.2%, P<0.01) were higher in patients with increased left ventricular mass index. Multivariable analysis identified increased left ventricular mass index (odds ratio: 5.6; 95% confidence interval: 1.2–25.0; P=0.02) and other three variables: age (P=0.04), history of chronic renal failure (P=0.03) and cardiopulmonary bypass time (P=0.004), as independent predictors of early mortality. Conclusions: Increased left ventricular mass index is associated with an in-hospital adverse outcome and a significantly higher in-hospital mortality in patients undergoing aortic valve replacement. Outcomes in asymptomatic patients could be improved before a clinically significant increase in left ventricular mass index. Further studies should be performed to determine the usefulness of this index in selecting patients for earlier aortic valve replacement.

Key Words: Ventricular mass • Aortic valve replacement • In-hospital mortality


   1. Introduction
Top
 Abstract
 1. Introduction
2. Materials and methods
 3. Results
 4. Discussion
 References
 
Left ventricular hypertrophy is a well-known predictor of morbidity in hypertensive patients [1,2]. Preoperative left ventricular hypertrophy is also a negative factor in aortic valve replacement. Several studies have documented the early and late prognostic importance of a preoperatively increased left ventricular mass index (LVMI) [3,4]. On one hand, incomplete recovery of left ventricular function and a lower late survival after aortic valve replacement are frequently associated with residual hypertrophy. This fact might be due to a excessively high initial hypertrophy with an incomplete postoperative reduction in left ventricular mass [5]. On the other hand, the implications of increased LVMI on early mortality are less evident [3].

So our study analyzes the effect of increased LVMI on early outcome in patients undergoing aortic valve replacement.


   2. Materials and methods
Top
 Abstract
 1. Introduction
 2. Materials and methods
3. Results
 4. Discussion
 References
 
2.1. Study group
We investigated a global group of 647 consecutive patients who underwent aortic valve replacement between June 1993 and November 2001. They were identified through a prospectively mantained surgical database (PATS, Cormedica®, Palex) and medical charts were reviewed retrospectively in order to confirm information and complete missing data of interest. Emergency operations (six patients) and 27 patients without preoperative echocardiographic data were excluded. Finally, 614 patients were included in the analysis.

2.2. Echocardiographic study
Most of echocardiographic data were collected from the Section of Echocardiography database in our hospital. All preoperative echocardiograms were reviewed and diastolic measurements of left ventricular internal diameter (LVID), interventricular septal thickness (IVST) and posterior wall thickness (PWT) (in milimeters) were used to calculate LVMI by means of the formula described by Devereux and colleagues [6,7]:

According to this author, LVMI was considered as increased if greater than 134 g/m2 in men and greater than 110 g/m2 in women. More than 80% of our patients were over these values so, for the purpose of this analysis, the superior decile of LVMI values was taken as a new cut-off point for dividing our patients into these two groups: with and without increased LVMI. LVMI was considered increased if higher than 277 g/m2 in males and 251 g/m2 in females.

As an additional analysis, we have evaluated the influence of different degrees of LVMI on in-hospital mortality. We have divided the patients in quartiles according to these new cut-off points of LVMI values: 146, 189 and 228 g/m2 in males and 132, 163 and 199 g/m2 in females.

2.3. Operative technique
Standard anesthesia and surgical techniques, extracorporeal circulation and myocardial protection methods were used. Myocardial protection employed was intermittent cold blood cardioplegia. Most of the patients received both antegrade and retrograde cardioplegia and ‘hot-shot’ (or reperfusion with warm blood cardioplegia). Lowest core temperature varied from 28 to 32°C depending on individual surgeon's preference. Continuous retrograde perfusion of cold blood was mantained, if possible, during the ischemic period.

Operations were performed by nine surgeons; of these, five performed 50 or more operations (surgeon A). The remaining four performed less than 20 operations each (surgeon B). They were grouped in two variables (surgeon A and B) that were included in the analysis.

2.4. Definitions
Chronic renal insufficiency was defined as a serum creatinine >=2 mg/dl. Respiratory failure was considered as the need for respiratory support for more than 48 h. Previous stroke was defined as history of a central neurologic deficit persisting for more than 72 h. Diabetes was defined as a history of diabetes mellitus regardless of its duration or need for oral or insulin treatment. Finally, low cardiac output syndrome was considered in the analysis when postoperative inotropic support was used for more than 24 h.

2.5. Statistical analysis
Statistical analysis was carried out with SPSS 9.0 for Windows.

Continuous data are presented as mean±SD if normally distributed or as median and inter-quartiles ranges if skewed distributed. Nominal data are presented as frequencies and percentages. Associations among nominal variables were compared by Pearson's Chi-square test, continuity correction or two-sided Fisher exact test as appropriate. Continuous univariate predictors for LVMI and mortality were tested by unpaired t-test. Mann–Whitney test was used to compare not normally distributed data.

Stepwise logistic-regression models were used to determine independent predictors of elevated LVMI and death. Models fit was evaluated using the Hosmer and Lemeshow goodness-of-fit statistic and residual analysis. Odds ratios, 95% confidence intervals and P values were reported. Area under the receiver-operating characteristic curve (or c-statistic) was calculated as a measure of predictive power.

Because a dichotomy was applied to the variable LVMI, propensity scores [8,9] were developped from a logistic model predicting normal or elevated LVMI. We used propensity analysis in order to balance the effect of varying LVMI on the outcome. The propensity score is just the result of a multivariable risk model for the event ‘LVMI: increased versus normal’. For each patient it provides the probability he or she had an elevated LVMI given a set of observed covariates. So a group of patients with the same propensity score are thus equally likely to have been asigned to the elevated LVMI group. Initially, a predictive model for increased LVMI was generated by using a set of variables suggestive of an association (P<0.20). Then, the predicted probabilities of elevated LVMI were ranked into quintiles and the distributions of the model covariates were compared accross LVMI groups in order to evaluate an adequate balance within each stratum. Thereafter, a logistic regression analysis was performed with in-hospital mortality as the outcome. This predictive model was also generated by a set of variables suggestive of an association with death in a previous univariable analysis including all patients irrespective of their preoperative LVMI. Finally, propensity scores were used in a new logistic regression in conjunction with this model of in-hospital mortality (or a final logistic regression model for mortality adjusted with propensity scores for the probability of increased LVMI).


   3. Results
Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
4. Discussion
 References
 
3.1. Preoperative characteristics of study patients
A total of 614 patients were included in the study. Univariate comparisons between patients with and without increased LVMI are presented in Table 1. Patients with elevated LVMI were older. But other demographic characteristics, clinical symptoms, comorbidities and previous cardiovascular risk factors were similar, except for a higher percentage of patients with normal LVMI presenting with chronic obstructive pulmonary disease.


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  		Table 1. Comparison of preoperative characteristics between patients with and without increased LVMIa

 
The mean LVMI for the global group was 178±111 g/m2. An increased LVMI was considered in 9.9% of patients studied. In this subgroup of patients the preoperative ejection fraction (EF) was lower (45.7 versus 55.5%; P=0.006).

3.2. Operative data
The most frequent indication for aortic valve replacement was aortic stenosis (41 and 49% in patients with and without elevated LVMI, respectively). Urgent operations were performed in three (5.1%) and 20 (3.6%) patients in both groups (P not significant). The mean ischemic and cardiopulmonary bypass (CPB) times were similar for both groups. A total of 129 bioprosthesis (21%) and 485 mechanical prosthesis (79%) were implanted in the aortic position. Other associated procedures were coronary artery bypass grafting in 70 patients, mitral valve surgery in 135 patients (17 mitral commissurothomies and 118 valve replacements). There was no difference between these two groups (with and without increased LVMI) with respect to combined procedures: associated myocardial revascularization in five (8.1%) and 65 patients (11%), P=0.340; and mitral surgery in 12 (19%) and 123 patients (22%), P=0.638; in the respective groups. Myocardial protection methods were also similar in both groups.

3.3. Postoperative outcome
Postoperative hospital stay was slightly longer in increased LVMI group: a median hospital stay of 12 days (interquartile range: 6–57 days) in contrast to 11 days (5–51 days) in the other group (P=0.33). Univariate comparisons of postoperative morbidity and in-hospital mortality in both groups of patients (increased versus normal LVMI) are presented in Table 2.


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  		Table 2. Comparison of postoperative outcomes between patients with and without increased LVMIa

 
Univariate associations to mortality included three vessel disease, older age, ischemic and CPB time and increased LVMI (Table 3). Independent predictors of mortality identified from a subsequent multiple logistic model are presented in Table 4. LVMI and its confounders were included in the model. There was no evidence of lack of fit and there was no indication of multicollinearity among the independent variables.


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  		Table 3. Univariate associations to mortalitya

 

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  		Table 4. Independent predictors of mortality (model not adjusted with propensity scores)a

 
3.4. Propensity analysis
Propensity scores were generated from a logistic model predicting normal or elevated LVMI. This model included the confounding variables with strong univariate association to increased LVMI. These propensity scores were ranked and classified into quintiles (Table 5). Stratification is a common way to use the propensity score to adjust comparisons and reduce bias. The probability of elevated or normal LVMI was relatively similar within a quintiled stratum (data not shown). So, it was possible to achieve balance between LVMI groups within each quintile conditional on the observed covariates. Another way of using propensity score is to use it in a logistic regression either by itself or in conjunction with other model, like our mortality risk model. So, finally we regenerated the logistic regression model for mortality adjusting with propensity scores for the probability of elevated LVMI (Table 6). The propensity score was not a significant addition and forcing it into the model changed the odds-ratio for increased LVMI only slightly to 5.69. On the contrary, ischemic time was removed from this model. The final model retained all other covariates including LVMI. Increased LVMI remained the strongest predictor of mortality. The final model provided a good predictive fit (P=0.5423, df=8; c-statistic=0.716).


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  		Table 5. Distribution of patient characteristics across propensity-matched quintilesa

 

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  		Table 6. Final logistic regression model for mortality adjusted with propensity scores for the probability of increased LVMIa

 
3.5. Different degrees of LVMI
We have evaluated in the whole group of patients the relationship between increasingly higher LVMI values and in-hospital mortality (Fig. 1) . Cummulative mortality was increasingly higher for LVMI values around 180 g/m2. We have divided the patients in quartiles according to LVMI values (see cut-off points values in Section 2) and we have looked at the in-hospital mortality in these four groups. Ten patients died in the higher quartile group (group 4) in comparison to five patients in each one of the other groups. The respective mortality rates were: 3.2% (5/154), 3.2% (5/154), 3.3% (5/153) and 6.5% (10/153), in groups 1–4. The difference between the global mortality in groups 1–3 and the mortality in group 4 was nearly significant: 3.2% (15/461) versus 6.5% (10/153), P=0.06.



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  		Fig. 1. Relation between LVMI (in g/m2) and in-hospital mortality (%/100).

 

   4. Discussion
Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
References
 
Many factors that increase operative morbimortality in patients undergoing aortic valve replacement have been identified by several studies [10–15]: LV dysfunction, associated coronary artery disease, renal insufficiency, advanced age, prior aortic valve replacement, aortic regurgitation, atrial fibrillation, patient-prosthesis mismatch, low body surface area, CPB time, type of prosthesis, etc.

Elevated LVMI has also been considered a risk factor for increased morbimortality in several circumstances by other investigations reported in the literature [1–4]. The aim of our study was to compare the outcome of two subsets of patients: those with normal and elevated preoperative LVMI. We have identified an increased LVMI as the strongest predictor of poor outcome after aortic valve replacement in our patients. These patients had a higher incidence of morbidity, length of stay and, above all, a significant increase in in-hospital mortality.

These results are similar to those of Mehta [3] and Orsinelli [4]. The last one showed that LV hypertrophy was a risk factor of postoperative mortality after aortic valve replacement for aortic stenosis. Mehta and colleagues studied 473 consecutive patients undergoing elective aortic valve replacement and the conclusion of their analysis was that increased LVMI was associated with increased in-hospital clinical events, greater length of stay and increased in-hospital mortality. They called for special attention to perioperative management of such patients and hypothesized about the potential benefit of earlier surgery in asymptomatic patients with significant increased LVMI.

Our findings are similar to those of Mehta and colleagues, but our patients had a different preoperative profile: a group of patients with a very low body surface area, specially in older women. We also included all patients undergoing aortic valve replacement for a variety of origins and not only isolated aortic stenosis. But the operations of our study were performed in a larger amount of patients (n=614) and during a longer period of time. We also used the same method to calculate LVMI: the formula described by Devereux and colleagues [6,7]. LVMI was considered as increased by these authors if greater than 134 g/m2 in men and greater than 110 g/m2 in women. But a differential factor have been identified in our patient population in comparison to other studies: a extremely high LVMI. More than 80% of them had an elevated LVMI according to the values accepted by this formula. So we established a new cut-off in a higher level (the superior decile) in order to performe our analysis. Patients considered with increased LVMI according to this cut-off point (9.9% of our study group) had values over 277 g/m2 in males and 251 g/m2 in females; so this subgroup of patients had, indeed, a very extensive hypertrophy. Similar values of LVMI were reported by Natsuaki and colleagues [5] on a Japanese patient population. Several factors could explain this finding: demographic differences in the severity of muscle hypertrophy, a significant number of patients who underwent surgery in an advanced phase of the disease, a population with a extremely low body surface area with very high values in LVMI, etc. A possible explanation could be that for a given degree of LV hypertrophy, patients with a very low body surface area may have a greater LVMI value (according to Devereux's formula). In the article by Natsuaki and colleagues [5] the authors reported an evaluation of postoperative cardiac function and long-term results after aortic valve replacement for aortic valve disease in patients with increased left ventricular mass. The mean value of LVMI was 272 g/m2. In fact, Japanese people have a low mean body surface area, a demographic characteristic similar to our Spanish elderly patients with aortic valve disease. On the other hand, when we studied different degrees of LVMI in four groups of our patients (divided in quartiles according to LVMI values), mortality in group 4 (with increased LVMI: over 228 g/m2 in males and 199 g/m2 in females) was clearly higher and with a near statistical significance: 6.5 versus 3.2% (P=0.06).

Increased LVMI could be responsible of this higher operative risk by means of several mechanisms: contractile impairment and pump dysfunction associated to excessive LV hypertrophy [2,16], diastolic dysfunction with abnormal relaxation and reduced distensibility [17,18], abnormalities of coronary flow reserve [19], propensity for cardiac arrhythmias [20], etc.

Although preoperative EF was lower in elevated LVMI group, the variable EF was not significantly associated to mortality in our univariable and multivariable analysis. On the contrary, Mehta and colleagues [3] found that EF was a significant independent predictor of mortality in the final logistic regression model.

Previous studies have identified the associated coronary artery disease as a risk factor for increasing mortality. In our study the number of patients with associated coronary artery disease was even higher in normal LVMI group and thus, it could not have accounted for the difference in outcomes observed in LVMI groups. In our patients, three vessel disease was associated to mortality in univariable analysis, but it was not found as an independent predictor of death in the final model. In these patients, coronary artery bypass grafting must be performed agressively with the objective of a complete myocardial revascularization to prevent perioperative ischemia. Other studies have reported abnormalities of coronary flow reserve in patients with increased LVMI in the absence of epicardial coronary artery disease [19,21]. This hypertrophied LV poses a considerable limitation for effective cardioprotection, so a ‘complete’ myocardial protection is mandatory in these patients. A correct myocardial protection with an adequate cardioplegic solution must be employed and antegrade and retrograde delivery should be considered routinely. Ascione and colleagues [22] found that cold blood cardioplegia was associated with less ischaemic stress and myocardial injury compared to warm blood cardioplegia in patients with aortic stenosis undergoing valve replacement surgery.

Other precautions may help improve the outcomes of these patients. For example, metabolic abnormalities should be promptly corrected to prevent rhythm disturbances. Hypotension should be treated with volume and alfa-agonists avoiding the routine employment of intravenous calcium and positive inotropic support.

In conclusion, increased LVMI is a predictor of poor outcome after aortic valve replacement. Patients with elevated preoperative LVMI have a higher incidence of morbidity, length of stay and a significant increase in in-hospital mortality. So, it is mandatory to optimize cardioprotection and management of these patients to improve outcomes. Also, they might benefit of an earlier surgery in the course of their disease (even in asymptomatic patients). Anyway, future prospective and randomized multi-institutional studies are required to establish LVMI itself like a new parameter in the timing indication for aortic valve replacement.

4.1. Limitations of the study
A number of limitations are inherent to this analysis design: a retrospective single institution study. Although a propensity analysis has been employed this methodology shares the limitations of all risk models. It can only account for factors that are available and the result of the regression is only an estimate of the propensity, not the true propensity itself. Propensity scores are only approximations of reality, randomization. But the consistent results of this analysis reveals a clear association of increased LVMI with suboptimal postoperative outcome and an increased in-hospital mortality.

Another limitation of the present study is the long time period of the analysis (June-1993–November-2001); changes in surgical techniques and intraoperative myocardial protection methods along time may influence outcome and prognostic factors.


   Acknowledgments
 
We thank Dr Rafael Payá and the Section of Echocardiography – Hospital General Universitario de Valencia- for performing the echocardiograms and assembling the echocardiographic data.


   Footnotes
 
Presented at the 16th Annual Meeting of the European Association for Cardio-thoracic Surgery, Monte Carlo, Monaco, September 22–25, 2002.


   References
Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 References
 

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