Abstract
Objectives
Analyses of mechanical circulatory support (MCS) in pediatric heart surgery have primarily focused on single-center outcomes or narrow applications. We describe patterns of use, patient characteristics, and MCS-associated outcomes across a large multicenter cohort.
Methods
Patients (<18yrs) in the STS Congenital Heart Surgery Database (2000-2010) were included. Characteristics and outcomes of those receiving post-operative MCS were described, and Bayesian hierarchical models were used to examine variation in adjusted MCS rates across institutions.
Results
Of 96,596 operations (80 centers), MCS was used in 2.4%. MCS patients were younger (13d v. 195d, p<0.0001) and more often had STS-defined preoperative risk factors (57.2% v. 32.7%, p<0.0001). Operations with the highest MCS rates included the Norwood procedure (17%) and complex biventricular repairs (arterial switch/VSD/arch repair-14%). Over half of MCS patients (53.2%) did not survive to hospital discharge (vs. 2.9%, non-MCS patients, p<0.0001). MCS-associated mortality was highest for truncus arteriosus and Ross-Konno operations (both 71%). Hospital-level MCS rates adjusted for patient characteristics and case mix varied by 15-fold across institutions; both high and low volume hospitals had substantial variation in MCS rates.
Conclusion
Perioperative MCS use varies widely across centers. MCS rates are highest overall for the Norwood procedure and complex biventricular repairs. Although MCS can be a life-saving therapy, over half of MCS patients do not survive to hospital discharge with mortality >70% for some operations. Future studies aimed at better understanding appropriate indications, optimal timing, and management of MCS may help to reduce variation in MCS across hospitals and improve outcomes.
INTRODUCTION
Mechanical circulatory support (MCS) is utilized perioperatively in the care of critically ill children with congenital heart disease and is often life-saving. Although several devices are being investigated, including those being evaluated currently in the National Institutes of Health in the Pumps for Kids, Infants, and Neonates (PumpKIN) trial, the most common form of pediatric MCS is extracorporeal membrane oxygenation (ECMO). ECMO is rapidly and simply initiated. It was first used in a pediatric patient in 1974 at Orange County Medical Center in Los Angeles, CA, and Robert Bartlett, MD first successfully supported a neonate with ECMO (to treat meconium aspiration).1 Since then, the application of ECMO has expanded to include cardiopulmonary support of patients with congenital heart disease. As surgical repairs of congenital heart disease have become increasingly complex, ECMO use has become more common. Reports of its use in this population include bridge to heart transplant, rescue cardiopulmonary resuscitation, and failure to wean from cardiopulmonary bypass.2-4 However, these reports primarily include small cohorts, are most often from single institutions, and tend to be narrowly focused on a specific patient population. There is currently a limited understanding of use and outcomes associated with ECMO following congenital heart surgery across institutions.
The Society of Thoracic Surgeons (STS) Congenital Heart Surgery Database collects perioperative information on all patients at participating institutions undergoing pediatric and congenital heart surgery, including information regarding the use of perioperative MCS. Approximately 85% of all US pediatric heart surgery centers participate in this database, and therefore it is a valuable repository of information regarding the use of MCS in congenital heart surgery patients.5 The primary objective of this study was to utilize the STS Congenital Heart Surgery Database to describe patterns of use, patient characteristics, and outcomes associated with MCS across a large multicenter cohort.
MATERIALS AND METHODS
Data Source
The STS Congenital Heart Surgery Database contains operative, perioperative, and outcomes data on >250,000 patients undergoing congenital heart surgery since 1998, and currently includes information from 105 participating hospitals. Data on all patients undergoing pediatric and congenital heart surgery at participating centers are entered into the database. Data quality and reliability are assured through intrinsic verification of data and a formal process of site visits and data audits.6 The Duke Clinical Research Institute serves as the data warehouse and analytic center for all of the STS National Databases. This analysis was approved by the Duke University Institutional Review Board, and by the STS Access and Publications Committee.
Patient Population
For the present study, a total of 132,854 cardiac operations (with or without cardiopulmonary bypass) performed on patients <18 years of age from 2000-2010 at 96 hospitals participating in the STS Congenital Heart Surgery Database were eligible for inclusion. Sixteen centers with >15% missing data on study variables were excluded. While the STS Database contains nearly complete data for the standard data fields required to calculate operative mortality, not all centers submit complete data for all variables such as patient pre-operative characteristics or post-operative complications. Therefore, it is standard practice to exclude centers with missing data for key study variables in order to maximize data integrity and minimize missing data.7 From the remaining 80 centers, patients with missing data for study variables were also excluded, leaving a final study population of n = 96,596 patients.
Data Collection
Data collected from the STS Congenital Heart Surgery Database included demographic information, cardiac diagnoses, presence of non-cardiac/genetic abnormality, and the presence of any STS-defined preoperative risk factors.8 Operative data included information regarding the primary procedure of the index (first) cardiovascular operation of the admission, which was analyzed individually and also categorized using the Society of Thoracic Surgeons-European Association for Cardiothoracic Surgery (STAT) risk stratification system (category 1 = lowest mortality risk, category 5 = highest mortality risk).9 This system was recently developed based on empiric data from nearly 80,000 patients, and it includes a greater number of operations compared with other risk stratification systems.9 The number of prior cardiothoracic operations was also collected, as well as cardiopulmonary bypass (CPB) times. The use of both pre- and post-operative MCS (of any type) was collected. In the earlier years of data collection, detailed information regarding the specific type of MCS was not collected in the database; therefore this study analyzes MCS use in aggregate. In addition, detailed information regarding the timing of initiation and duration of MCS is not currently collected in the database. Outcomes data included in-hospital mortality and post-operative length of stay.
Analysis
Pre-operative, operative, and outcomes data were described for the overall cohort as well as for subgroups of patients undergoing the most common operations using standard summary statistics, and compared in those who received MCS vs. those who did not using the chi-square test or Wilcoxon rank sum test. The majority of the analysis focused on post-operative MCS given the relative rarity of pre-operative MCS.
In order to examine variation in post-operative MCS rates across hospitals, Bayesian hierarchical models were used to calculate adjusted post-operative MCS rates for each hospital. The models were adjusted for patient characteristics and case mix in order to account for any differences across hospitals, including patient age, gender, weight at surgery, the presence of any STS-defined pre-operative risk factors or non-cardiac/genetic abnormality, previous cardio-thoracic surgery, use of pre-operative MCS, STAT category, and date of surgery. This methodology also accounts for increased variability in outcomes from centers with smaller sample size, and shrinks estimates form smaller centers toward the population average to provide more stable estimates.10 The distribution of adjusted MCS rates across hospitals was described, and plotted against hospital average annual overall cardiac surgical volume. Finally, in order to further investigate the relationship between center volume and MSC rates, we also calculated adjusted MCS rates across center volume categories (<150, 150-249, 250-349, and ≥350 total cardiac cases per year) as adjusted rate = observed rate/predicted rate*sample average rate, where the predicted rates were from a marginal logistic model including the aforementioned patient and operative factors detailed above. All analyses were performed using SAS version 9.3 (SAS Institute Inc, Cary, NC), and WinBUGS version 1.4.3 (the BUGS project, Cambridge, UK). A p-value <0.05 was considered statistically significant.
RESULTS
A total of 96,596 congenital cardiac operations from 80 hospitals were included. Included hospitals were diverse geographically (44% South, 24% Midwest, 21% West, and 11% Northeast). The overall MCS rate was 2.8% (n=2750), including: preoperative 0.5% (n=463), postoperative 2.2% (n=2136), or both 0.1% (n=151). Further analysis focused on the group receiving any post-operative MCS (n=2287, 2.4%). Extracorporeal membrane oxygenator support accounted for >95% of the instances of post-operative MCS.
Study Population Characteristics
Table 1 displays characteristics of the study cohort overall and those who received post-operative MCS vs. those who did not. Patients receiving postoperative MCS were younger, weighed less, and more-often had an STS-defined preoperative risk factor than patients without MCS. Of note, patients receiving MCS were more likely to have pre-operative shock (7.4% v. 1.7%), pre-operative arrhythmia (4.6% v. 2.6%), and to have been mechanically ventilated (36.6% v. 15.3%). There were no clinically meaningful differences in race/ethnicity, sex, and the proportion with a non-cardiac/genetic abnormality in the MCS vs. non-MCS groups. Operative characteristics are also displayed in Table 1. The MCS cohort was more likely to have undergone higher complexity operations involving longer CPB times.
Table 1.
Study Population – Patient Characteristics, Operative Characteristics, and Outcomes
| Patient Characteristics | Overall (n=96596) | Postoperative MCS (n=2287) | No MCS (n=94309) | p value |
|---|---|---|---|---|
| Age (days) | 189 [28-1227] | 13 [5-124] | 195 [31-1259] | <0.0001 |
| Weight (kilograms) | 6.3 [3.5-14.2] | 3.4 [2.9-5.1] | 6.4 [3.6-14.4] | <0.0001 |
| Race, White | 47605 (49.3%) | 1094 (47.8%) | 46511 (49.3%) | <0.0001 |
| Sex, male | 52670 (54.5%) | 1262 (55.2%) | 51408 (54.5%) | 0.004 |
| Non-cardiac abnormality | 29464 (30.5%) | 677 (29.6%) | 228787 (30.5%) | 0.3 |
| STS preoperative risk factors | ||||
| Any | 32115 (33.3%) | 1310 (57.3%) | 30805 (32.7%) | <0.0001 |
| Mechanical ventilation | 15303 (15.8%) | 837 (36.6%) | 14466 (15.3%) | <0.0001 |
| Arrhythmia | 2206 (2.6%) | 90 (4.6%) | 2116 (2.6%) | <0.0001 |
| Shock | 1727 (1.8%) | 170 (7.4%) | 1047 (1.7%) | <0.0001 |
| Operative Characteristics | ||||
| Prior CT operation | 26939 (27.9%) | 458 (20.0%) | 26481 (28.1%) | <0.0001 |
| STAT Category | ||||
| Low (1-3) | 69447 (71.9%) | 581 (25.4%) | 68866 (73.0%) | <0.0001 |
| High (4-5) | 23756 (24.6%) | 1653 (72.3%) | 22103 (23.4%) | <0.0001 |
| CPB time (minutes) | 95 [64-140] | 175 [121-252] | 94 [63-137] | <0.0001 |
| Outcomes | ||||
| In-hospital mortality | 3940 (4.1%) | 1217 (53.2%) | 2723 (2.9%) | <0.0001 |
| Length of stay (days) | 6 [4-14] | 28 [12-56] | 6 [4-13] | <0.0001 |
Continuous variables are presented as median [interquartile range]
MCS=Mechanical circulatory support; STAT=Society of Thoracic Surgeons-European Association for Cardiothoracic Surgery; CT=cardiothoracic; CPB=cardiopulmonary bypass
Overall Outcomes
Over half of those who received postoperative MCS did not survive to hospital discharge (Table 1). In-hospital mortality was 53.2% compared to 2.9% in those who did not receive MCS (p<0.0001). As expected, length of stay was prolonged in those who received MCS (median 28d v. 6d, p<0.0001) (Table 1).
Post-operative MCS Rates and Outcomes for the Most Common Operations
Operations with n>100 in the overall cohort were evaluated further. Those with the highest postoperative MCS rates are listed in Table 2. The highest rates of MCS were observed for the Norwood procedure (17.0%), and in complex biventricular repairs including the arterial switch operation + ventricular septal defect + aortic arch repair (14.0%), truncus arteriosus repair (9.4%), and the Ross Konno procedure (9.3%). For all of the operations examined, post-operative MCS was associated with a higher risk of in-hospital mortality. This risk was greatest for the Ross-Konno procedure (mortality with MCS 71%, vs. without MCS 3.4%, unadjusted odds ratio 70.4, p<0.0001) and truncus arteriosus repair (mortality with MCS 71%, vs. without MCS 5.5%, unadjusted odds ratio 42.0, p<0.0001).
Table 2.
Operations with Highest Post-operative MCS Rates and Associated Outcomes
| Operation | Total Cases (n) | MCS Rate (%) | Mortality with MCS (%) | Mortality without MCS (%) | Unadjusted OR (MCS vs. No MCS) | p-value |
|---|---|---|---|---|---|---|
| Norwood procedure | 3272 | 17 | 57 | 13 | 8.7 | <0.0001 |
| ASO+VSD+aortic arch repair | 139 | 14 | 40 | 3 | 19.2 | <0.0001 |
| Damus-Kaye-Stansel | 430 | 13 | 40 | 10 | 6.0 | <0.0001 |
| Truncus arteriosus repair | 689 | 9.4 | 71 | 5.5 | 42.0 | <0.0001 |
| Ross-Konno operation | 225 | 9.3 | 71 | 3.4 | 70.4 | <0.0001 |
| Unifocalization MAPCA | 466 | 8.4 | 41 | 8 | 8.0 | <0.0001 |
| TAPVC repair | 1850 | 8.2 | 59 | 7.4 | 18.1 | <0.0001 |
| ASO+VSD | 855 | 7.5 | 53 | 3.2 | 34.7 | <0.0001 |
| ALCAPA repair | 397 | 7.3 | 14 | 1 | 19.5 | <0.0001 |
MCS=mechanical circulatory support; ASO=arterial switch operation; VSD=ventricular septal defect; MAPCA=major aortopulmonary collateral artery; TAPVC=total anomalous pulmonary venous connection; ALCAPA=anomalous origin of coronary artery from pulmonary artery
The STS-defined “benchmark” operations of varying levels of complexity were also evaluated (Norwood procedure, truncus arteriosus repair, Fontan operation, arterial switch operation +/− ventricular septal defect repair, tetralogy of Fallot repair, complete atrioventricular canal repair, and ventricular septal defect repair), in addition to bidirectional Glenn/hemi-Fontan and atrial septal defect repair. MCS rates and associated outcomes for these operations are displayed in Figure 1. As expected, MCS rates increased with operation complexity. MCS rates were >5% for 3 of these 10 common operations. Post-operative MCS was associated with a higher in-hospital mortality for all of the benchmark operations.
Figure 1. Post-operative MCS Rates for Benchmark Procedures and Associated Mortality.
MCS=mechanical circulatory support; ASD=atrial septal defect; VSD=ventricular septal defect; BDG/HF=bidirectional Glenn/hemiFontan; TOF=tetralogy of Fallot; CAVC=complete atrioventricular canal; ASO=arterial switch operation; ASO/VSD=arterial switch operation/ventricular septal defect; TA=truncus arteriosus; Nwood=Norwood
Variation in Post-operative MCS Rates Across Hospitals
Variation in post-operative MCS rates across hospitals, adjusted for any differences in patient characteristics and case mix, was evaluated. As displayed in Figure 2, the median hospital-level adjusted MCS rate was 2.5%, and varied from 0.6% to 9.3% across the 80 hospitals included in this study (15-fold variation). We also examined the relationship of overall cardiac surgical volume with adjusted MCS rate. While lower volume hospitals as a group had slightly higher MCS rates (Figure 3), the magnitude of this difference was relatively small and a plot of each hospital's MCS rate vs. total surgical volume did not demonstrate a clear overall relationship. Both high and low volume hospitals appeared to have substantial variation in MCS rates.
Figure 2. Variation in Adjusted MCS Rates Across Hospitals.
Adjusted post-operative MCS rates are listed for each hospital (black box represents adjusted estimate and lines indicate 95% confidence intervals). The horizontal dotted line indicates the post-operative MCS rate in the overall cohort.
Figure 3. Relationship of Adjusted MSC Rates with Total Surgical Volume Across Hospitals.
Adjusted post-operative MCS rates are listed for each hospital in order of increasing average annual total cardiac surgical volume (black box represents adjusted estimate and lines indicate 95% confidence intervals). The horizontal dotted line indicates the post-operative MCS rate in the overall cohort. Adjusted MCS rates in volume groups are also listed at the bottom of the plot.
DISCUSSION
This report based on the STS Congenital Heart Surgery Database focuses on patterns of use and outcomes associated with post-operative MCS. We found that MCS rates were >5% in nearly one third of the most common congenital cardiac operations performed, and were highest for neonates undergoing single ventricle palliative procedures and complex biventricular repairs. Despite being a potentially lifesaving therapy, over half of patients requiring MCS do not survive to hospital discharge, and MCS-associated in-hospital mortality for some operations is greater than 70%. There is substantial variation in MCS rates across hospitals, including both high and low volume centers.
Mechanical circulatory support remains an emerging technology. Devices such as the intra-aortic balloon pump and ventricular assist pumps were initially developed primarily to meet the needs of adult patients, and occasional application in the pediatric population was limited to relatively large patients. The emergence and refinement of ECMO support for respiratory failure in neonates and infants led logically to the application of similar technology for cardiopulmonary support and to increasingly frequent use in patients with congenital heart disease. While ECMO is still by far the most widely used form of MCS in pediatric cardiac surgery, it has recently been joined by alternative devices for univentricular or biventricular support.
The relatively young median age and lower weight for those receiving post-operative MCS is not surprising. Improvements in perioperative care of the neonate with congenital heart disease has led to increased interest in early operative intervention in this population.11 Even in the setting of an acceptable anatomic reconstruction, animal studies and clinical observation suggest that the neonatal myocardium is uniquely susceptible to ischemia/reperfusion injury.12,13 Published reports have also demonstrated that the presence of various preoperative risk factors increase morbidity and mortality after complex neonatal repairs.14 Although survival has improved significantly in complex operations over the past two decades, these operations (including the Norwood procedure, arterial switch/aortic arch repair, and truncus/interrupted aortic arch repair) have been shown to carry the highest mortality risk of all operations in congenital heart surgery.15
The in-hospital mortality and length of stay reported here are comparable and perhaps slightly lower than previously published data including reports from the Extracorporeal Life Support Organization (ELSO) database.16,17 An ELSO study from 1989-2004 including 5,151 neonatal and pediatric cardiac cases reported that in-hospital mortality for the neonatal and pediatric cardiac cohorts was 62% and 57% respectively. Subgroups examined included congenital defect, cardiac arrest, cardiogenic shock, cardiomyopathy, and myocarditis. The authors also report the incidence of mechanical and patient related complications of ECMO in the cardiac population. The most common complication in each group was oxygenator failure (7.2%) and surgical site bleeding (31.0%). Unlike this study, the ELSO study did not report on specific patient characteristics, preoperative risk factors, operative characteristics, individual congenital heart lesions or interhospital variation.
The Norwood procedure has the highest postoperative MCS rate in this study. This operation can be one of the most challenging operations in congenital heart surgery, and it can be difficult to reliably reproduce technically perfect results.18 Additionally, the resulting physiology is precarious and sensitive to minor changes in preload, afterload, and contractility. This is highlighted by the 13% mortality in this study in those Norwood patients that did not require MCS. However, it is also important to note that the subgroup with highest mortality associated with MCS in this study was not the single ventricle patients, but those patients undergoing biventricular repairs, including truncus arteriosus and Ross-Konno operations. As there are no established and validated risk models for these relatively uncommon operations, which are sometimes performed on infants with severe physiologic embarrassment, we can only speculate as to specific reasons for increased risk of mortality in patients requiring MCS following these procedures. Some common features include right ventriculotomy, the presence of many aortic suture lines that could exacerbate bleeding while using MCS, and the potential for coronary insufficiency with both repairs (coronary buttons and reimplantation usually for the Ross-Konno; abnormal coronary orifice locations possible in truncus arteriosus). What remains unclear is the relative contribution of patient factors and procedural factors to the need for, and ultimate salvage rate associated with post-operative MCS. The balance of pre-operative physiologic compromise, intraoperative myocardial ischemia and reperfusion, and technical complexity of operations (particularly with respect to restoration of adequate coronary artery anatomy and perfusion and potential for residual defects and hemodynamic burdens) constitute a complex field of variables that may influence the need for MCS at the time of separation from bypass or the likelihood of postoperative deterioration requiring resuscitation. It is not at all surprising then, that operations such as the palliative Norwood procedure, repair of transposition with ventricular septal defect and arch obstruction, and the neonatal Ross-Konno are associated with the highest rates of MCS. What remains to be determined is how best to take advantage of available technology to maximize salvage of these patients.19,20
Although mortality associated with MCS is high at 53%, it is important to recognize that likely few to none of these patients would have been discharged alive if it weren't for the use of MCS. Nonetheless, the wide variability in MCS rates that we observed across centers, even after accounting for potential differences in case mix and patient characteristics, suggests there is ample room for improvement. Further study is necessary to better understand the reasons underlying this variation, and whether variation in MCS rates is associated with the known variation in mortality rates across hospitals.21,22 While the reasons for the wide variability in MCS rates across centers are not obvious, there are several potential explanations. The time from inception and rate of maturation of individual institutional ECMO (and other MCS) programs varies from one center to the next. Likewise, the threshold for instituting mechanical support reflects the judgment and experience of individual surgeons and multi-disciplinary critical care teams. In some centers, postoperative MCS may be limited to patients who cannot be weaned from cardiopulmonary bypass or who experience cardiac arrest in the intensive care unit. In others, mechanical support is considered earlier and more frequently, as a desirable alternative to escalating pharmacologic support. What is apparent is that MCS for post-operative support is used in the vast majority of centers, consistent with the Quality Measures for Congenital and Pediatric Cardiac Surgery proposed by the Society of Thoracic Surgeons, which include availability of an institutional pediatric extracorporeal life support program.23
Limitations
The primary limitations of this study are related to the nature of the STS Database. Not all US centers participate in the STS Database or submit complete data. Nonetheless, this report represents the most broad evaluation of MCS use to date, including 80 US pediatric heart centers. In addition, in the earlier years of data collection, detailed information regarding the specific type of MCS was not collected in the database; therefore we were limited to analyzing post-operative MCS in aggregate. The addition of specific fields related to the use of ventricular assist devices in more recent versions of the data collection form will allow more detailed analyses of specific types of peri-operative MCS in the future. The database also currently does not collect details regarding the indication for MCS support or other details related to MCS such as flow rates, specific duration of therapy, and MCS-related complications. There is likely significant interhospital variation in many aspects of clinical care including but not limited to anticoagulation, pump flow, vasoactive medication management, and weaning protocols. Future linkage of the STS Congenital Heart Surgery Database with the ELSO Database could potentially address some of these limitations and allow analyses currently not possible within either dataset alone. Finally, the database currently does not collect longer term follow-up to evaluate the functional capacity and long-term survival of those patients receiving MCS.
CONCLUSION
While MCS can be a life-saving therapy in children undergoing heart surgery, more than half of children who receive MCS do not survive to hospital discharge, with MCS-associated mortality >70% for certain operations. While MCS is used most commonly in those undergoing single ventricle palliative procedures, MCS is also common in patients undergoing complex biventricular repairs, and the greatest mortality risk associated with MCS is in this latter group. MCS use varies widely across hospitals (up to 15-fold), even after accounting for any differences in case mix or patient characteristics, suggesting ample room for improvement. Future study aimed at better understanding and standardizing indications for MCS, optimal timing, and MCS management may help to reduce variation across hospitals and improve outcomes.
Acknowledgments
Sources of funding/Disclosures:
SK Pasquali, MD: Grant support (K08HL103631), National Heart, Lung, and Blood Institute
JP Jacobs, MD: Chair, Society of Thoracic Surgeons Congenital Heart Surgery Database Task Force
Footnotes
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