Predictors of in-hospital mortality following mitral or double valve replacement for rheumatic heart disease

Backgrounds and Aims: Factors affecting outcome of mitral valve replacement in rheumatic population of Nepal is unknown. The aim of this study was to identify the predictors of in-hospital mortality in patients undergoing mitral or double valve replacement in Nepal. Methods: A retrospective observational study was designed to evaluate the outcome of patients who underwent mitral valve replacement with or without concomitant other valvular surgery during a period of one year in a tertiary care cardiac centre in Nepal. Data were analysed to find the significant predictors of in-hospital mortality. Results: A total of 411 patients fulfilled the inclusion criteria. The overall in-hospital mortality was 4.1% (95% CI 2.18-6.02). A cutoff value for higher mortality obtained using ROC curve for age was 37.5 years; and for duration of mechanical ventilation was 8.5 hours. Multivariate logistic regression model identified increasing age (>37.5 years), OR 2.05 (95% CI 0.77-5.45), p=0.001; NYHA Class III and IV, OR 15.18 (95%CI 0.9-54.53), p<0.001; presence of left atrial thrombus, OR 4.96 (95% CI 1.49-16.43), p=0.003; tricuspid regurgitation grade III and IV, OR 2.62 (95% CI 0.95-7.24), p=0.004; re-exploration for bleeding, OR 8.62 (95% CI 1.60-46.32), p=0.03; left ventricular ejection fraction (≤40%), OR 8.22 (95% CI 2.62-25.72), p=0.001; inotrope score >20, OR 9.90 (95% CI 3.48-28.15), p<0.001; duration of mechanical ventilation >8.5 hours, OR 22.96 (95% CI 5.15-52.10), p<0.001; and stay in the intensive care unit > 2 days, OR 1.31 (95% CI 0.49-3.46), p<0.001 as predictors of mortality. Conclusion: Age, NYHA Class, severe tricuspid regurgitation, presence of left atrial clot, re-exploration for bleeding, decreasing left ventricular ejection fraction, high inotrope score, longer duration of mechanical ventilation, and longer stay in the intensive care unit were identified as the independent predictors of in-hospital mortality. Introduction Rheumatic valvular heart disease (RVHD) is a condition of global health importance as more than 15 million people are living with the disease. Most of these patients are living in developing countries. The treatment of choice for severe forms of RVHD is surgical correction; either valve repair or replacement. The outcomes following valve replacement differ in different settings and population. The mortality rate and predictors of outcome after rheumatic mitral or double valve replacement in Nepalese population are yet to be explored. The objective of the study was to identify the risk factors for in-hospital mortality after mitral valve replacement in patients with rheumatic mitral valvular heart disease with or without other valvular involvement. Methods A retrospective study was designed and institutional review committee’s approval was obtained. Data of all patients who underwent elective mitral or double valve replacement with or without other concomitant cardiac surgical procedures from January 2014 to December 2014 was retrieved from the hospital records and analyzed. Patients who underwent emergency mitral valve replacement following complicated percutaneous balloon valvotomy procedures were excluded from the study. Demographic data including age, gender, and place of residence were assessed from the hospital records. To study whether remoteness of place of living contributes to mortality, the remoteness of the usual place of residence was categorized as non-remote, general remote, remote, and most remote based on the classification by Remote Area Development Committee, Government of Nepal, 1991. NYHA class, concomitant coronary artery bypass grafting (CABG) and a pre-existing diagnosis of atrial fibrillation were recorded. The echocardiographic assessment included left ventricular ejection fraction (LVEF), type and number of valves affected, degree of stenosis and regurgitation, left ventricular diastolic and systolic dimensions, dimensions of left ventricular posterior wall, and interventricular septum, and pulmonary artery systolic pressure. Similarly, cardiopulmonary bypass time, aortic cross clamp time, epicardial pacing requirement, and intraoperative events @Nepalese Heart Journal. All right reserved. Nepalese Heart Journal 2016; 13(2): 19-24 Apurba Sharma,et al. Predictors of in-hospital mortality following mitral or double valve replacement for RHD. @Nepalese Heart Journal. All right reserved. 20 Nepalese Heart Journal 2016; 13(2): 19-24 in the form of ventricular arrhythmias after aortic cross clamp release were also recorded. Outcomes associated with the immediate postoperative results like in-hospital mortality, length of mechanical ventilatory support, inotrope score, re-exploration, renal failure, arrhythmias, and lengths of intensive care stay were also recorded. We calculated inotrope score using the following formula described by Cruz DN et al : Inotrope score= (Dopamine dose x 1) + (Dobutamine dose x 1) + (Adrenalline dose x 100) + (Noradrenalline dose x 100) + (Phenylephrine dose x 100). Data collection and missing values Data collection was done by predefined proforma containing the details of the patient from the hospital records. Missing values were managed either by the deletion of the case if the missing variables were more than 50% of the total number of variables, or calculating the missing value through averaging or maximum likelihood strategies. Data analysis and statistical analysis Data were analyzed using IBM SPSS Statistics 16 (SPSS Inc, Chicago, IL). Descriptive data were summarized using standard techniques and reported as percentages with 95 % confidence intervals (95 % CI), means with standard deviation (SD) if the values were evenly distributed or medians with interquartile range (IQR) if the data were non-uniformly distributed. Comparison between subgroups of survivors and nonsurvivors was undertaken using χ2 for categorical data and student’s t-test or Mann-Whitney U test for continuous normally distributed or non-normally distributed data respectively. A p value of < 0.05 was considered statistically significant. Multivariate linear and logistic models were developed to identify independent factors associated with outcome measures. A backwards stepwise approach was used including in the first model all factors associated with a particular outcome variable using bivariate analysis with a p value < 0.1. Factors with a p value ≥ 0.05 were progressively removed from the models starting with those variables with a regression co-efficient closest to 0. Final models were limited to predictive factors with significant coefficients (p < 0.05). Cutoff values for the continuous variables identified as independent predictors of mortality were established through Receiver Operating Characteristic (ROC) curves. Results A total of 486 patients underwent valve surgery during the study period. Sixty six patients who underwent isolated aortic valve replacement, five patients with non-rheumatic mitral valve pathology, two patients with severe mitral regurgitation and one patient with pericardial tamponade after percutaneous balloon valvotomy and one patient with missing variables more than 50% of total number of variables were excluded from the study. Thus, the study sample consisted of 411 patients. Seventeen patients died during the hospital stay resulting in a mortality rate of 4.1% (95% CI 2.18-6.02). Demographic and pre-operative characteristics of the patients and results from the bivariate analysis with respect to outcome are detailed in Table 1. Table 1. Demographic and preoperative characteristics of Survivors and Non-survivors Variables Overall (n=411) Survivors (n=394) Non-survivors (n=17) p-value (Bivariate analysis) Age, years (mean±SD) 32.87±15.13 45.24±11.87 <0.001 Females; n (%) 241 (58.6) 228 (94.6) 13 (5.4) 0.12 Males; n (%) 170 (41.4) 166 (97.6) 4 (2.4)


Introduction
Rheumatic valvular heart disease (RVHD) is a condition of global health importance as more than 15 million people are living with the disease.Most of these patients are living in developing countries.The treatment of choice for severe forms of RVHD is surgical correction; either valve repair or replacement.The outcomes following valve replacement differ in different settings and population.The mortality rate and predictors of outcome after rheumatic mitral or double valve replacement in Nepalese population are yet to be explored.The objective of the study was to identify the risk factors for in-hospital mortality after mitral valve replacement in patients with rheumatic mitral valvular heart disease with or without other valvular involvement.

Methods
A retrospective study was designed and institutional review committee's approval was obtained.Data of all patients who underwent elective mitral or double valve replacement with or without other concomitant cardiac surgical procedures from January 2014 to December 2014 was retrieved from the hospital records and analyzed.Patients who underwent emergency mitral valve replacement following complicated percutaneous balloon valvotomy procedures were excluded from the study.
Demographic data including age, gender, and place of residence were assessed from the hospital records.To study whether remoteness of place of living contributes to mortality, the remoteness of the usual place of residence was categorized as non-remote, general remote, remote, and most remote based on the classification by Remote Area Development Committee, Government of Nepal, 1991.
NYHA class, concomitant coronary artery bypass grafting (CABG) and a pre-existing diagnosis of atrial fibrillation were recorded.
The echocardiographic assessment included left ventricular ejection fraction (LVEF), type and number of valves affected, degree of stenosis and regurgitation, left ventricular diastolic and systolic dimensions, dimensions of left ventricular posterior wall, and interventricular septum, and pulmonary artery systolic pressure.
Similarly, cardiopulmonary bypass time, aortic cross clamp time, epicardial pacing requirement, and intraoperative events @Nepalese Heart Journal. in the form of ventricular arrhythmias after aortic cross clamp release were also recorded.
Outcomes associated with the immediate postoperative results like in-hospital mortality, length of mechanical ventilatory support, inotrope score, re-exploration, renal failure, arrhythmias, and lengths of intensive care stay were also recorded.We calculated inotrope score using the following formula described by Cruz DN et al : Inotrope score= (Dopamine dose x 1) + (Dobutamine dose x 1) + (Adrenalline dose x 100) + (Noradrenalline dose x 100) + (Phenylephrine dose x 100).

Data collection and missing values
Data collection was done by predefined proforma containing the details of the patient from the hospital records.Missing values were managed either by the deletion of the case if the missing variables were more than 50% of the total number of variables, or calculating the missing value through averaging or maximum likelihood strategies.

Data analysis and statistical analysis
Data were analyzed using IBM SPSS Statistics 16 (SPSS Inc, Chicago, IL).Descriptive data were summarized using standard techniques and reported as percentages with 95 % confidence intervals (95 % CI), means with standard deviation (SD) if the values were evenly distributed or medians with interquartile range (IQR) if the data were non-uniformly distributed.
Comparison between subgroups of survivors and nonsurvivors was undertaken using χ2 for categorical data and student's t-test or Mann-Whitney U test for continuous normally distributed or non-normally distributed data respectively.A p value of < 0.05 was considered statistically significant.
Multivariate linear and logistic models were developed to identify independent factors associated with outcome measures.A backwards stepwise approach was used including in the first model all factors associated with a particular outcome variable using bivariate analysis with a p value < 0.1.Factors with a p value ≥ 0.05 were progressively removed from the models starting with those variables with a regression co-efficient closest to 0.
Final models were limited to predictive factors with significant coefficients (p < 0.05).Cutoff values for the continuous variables identified as independent predictors of mortality were established through Receiver Operating Characteristic (ROC) curves.

Results
A total of 486 patients underwent valve surgery during the study period.Sixty six patients who underwent isolated aortic valve replacement, five patients with non-rheumatic mitral valve pathology, two patients with severe mitral regurgitation and one patient with pericardial tamponade after percutaneous balloon valvotomy and one patient with missing variables more than 50% of total number of variables were excluded from the study.Thus, the study sample consisted of 411 patients.Seventeen patients died during the hospital stay resulting in a mortality rate of 4.1% (95% CI 2.18-6.02).Demographic and pre-operative characteristics of the patients and results from the bivariate analysis with respect to outcome are detailed in Table 1.Age of the patient and duration of mechanical ventilation had area under the curve of 0.732 and 0.923, showing significant correlation between them and mortality.A cut off value for increase in mortality was after the age of 37.5 years and duration of mechanical ventilation longer than 8.5 hours.
Preoperative and postoperative renal function was excluded from analysis due to high degree of missing values.

Limitations
The most important limiting factor is retrospective nature of the study.Another limitation of the study was inclusion of limited number of predicting variables.The basic difficulty in prediction of outcomes in patients undergoing cardiac surgery is the occurrence of wide range of complications.Unforeseen events may occur that influence the perioperative course.Furthermore, the diversity and individuality of biological response to anesthesia, cardiopulmonary bypass, and surgery may hinder the accuracy of prediction.An important predictor (preoperative and postoperative renal dysfunction) was excluded from analysis due to large number of missing values.Apart from that, logistic regression assumes a parametric distribution which is unstable for small numbers, e.g; a small number of re-exploration turned out to be significant in this study.Our study consists of only inhospital mortality and further studies with post-surgical follow up will demonstrate long term outcome predictors. In

Table 1 .
Demographic and preoperative characteristics of Survivors and Non-survivorsDetails of preoperative echocardiographic assessment and results of bivariate analysis are depicted in table 2.
DiscussionThis study is an attempt to identify the predictors of in hospital mortality in RVHD patients undergoing mitral or double valve replacement in Nepal.Demographic characteristics did not show differences between survivors and non-survivors.More females of reproductive age group presented for valve replacements for RVHD.This is similar to the global trend of 61% prevalence in females.However, our study population comprised of young patients of productive age group with mean age of 33 years.This signifies the necessity of more aggressive primary prophylaxis for RHD in the country.In the study, large number of patients presented from the non-remote areas; mostly from the districts around the Kathmandu valley.Patients from the most-remote areas comprised only 2.6% probably because most of the remote and most-remote population still has poor access to cardiac care.Remote location was not a significant predictor of either short or long term outcome in Australia , but remote location of Australia and Nepal differs hugely in terms of affordability and accessibility to health care.Since prevalence of RHD in two of the neighboring countries, India and China, is described as higher;3 a detailed nationwide population based study is needed to quantify the disease burden in the country.Our study population showed a very high prevalence of atrial fibrillation (AF); almost two thirds (70%) presenting with AF.The global rheumatic heart disease registry (REMEDY) documented 21.8% of RHD patients with atrial fibrillation.AF is a late feature of rheumatic heart disease and its incidence increases with age and disease progression, dilatation of left atrium associated with mitral stenosis and regurgitation.This added pre-operative AF burden limits the choice of prosthesis to mechanical alone with need of anticoagulation and its associated risks.Most of the patients (71.3%) had a poor functional class (NYHA III and IV); which signifies late presentation for treatment.Our results emphasize the need for awareness programs in the community for early hospital visit if symptoms of acute rheumatic fever or RHD are seen.Increasing age has been associated with poorer outcome in previous studies.10Previous studies have identified age above fifty as risk factor for operative mortality in mitral valve surgery.Our study has identified age as a risk factor for mortality in rheumatic valve replacement patients; however the age at which mortality increases is much lower for rheumatic population.
Association, ICU-intensive care unit Nepalese Heart Journal 2016; 13(2): 19-24 conclusion, we identified age, NYHA class, severe TR, thrombus in left atrium, re-exploration for bleeding , decreasing LVEF, high inotrope score, longer duration of mechanical Nepalese Heart Journal 2016; 13(2): 19-24 ventilation, and ICU stay as the independent predictors of inhospital mortality among patients undergoing mitral or double valve replacement for rheumatic heart disease.Sources of funding: none