Karamlou, Tara

Evidence from medicine and other fields has shown that gender diversity results in better decision making and outcomes. The incoming workforce of congenital heart specialists (especially in pediatric cardiology) appears to be more gender balanced, but past studies have shown many inequities. Gender‐associated differences in leadership positions, opportunities presented for academic advancement, and recognition for academic contributions to the field persist. In addition, compensation packages remain disparate if evaluated based on gender with equivalent experience and expertise. This review explores these inequities and has suggested individual and institutional changes that could be made to recruit and retain women, monitor the climate of the institution, and identify and eliminate bias in areas like salary and promotions.

Purpose We reviewed all 64 articles ever published by The Congenital Heart Surgeons’ Society (CHSS) Data Center to estimate the academic impact of these peer-reviewed articles. Materials and Methods The Congenital Heart Surgeons’ Society has performed research based on 12 Diagnostic Inception Cohorts. The first cohort (Transposition) began enrolling patients on January 1, 1985. We queried PubMed to determine the number of publications that referenced each of the 64 journal articles generated by the datasets of the 12 Diagnostic Inception Cohorts that comprise the CHSS Database. Descriptive summaries of the data were tabulated using mean with standard deviation and median with range. Results Sixty-four peer-reviewed papers have been published based on the CHSS Database. Fifty-nine peer-reviewed articles have been published based on the 12 Diagnostic Inception Cohorts, and five additional articles have been published based on Data Science. Excluding the recently established Diagnostic Inception Cohort for patients with Ebstein malformation of tricuspid valve, the number of papers published per cohort ranged from 1 for coarctation to 11 for transposition of the great arteries. The 11 articles generated from the CHSS Transposition Cohort were referenced by a total of 111 articles (median number of references per journal article = 9 [range = 0-22, mean = 10.1]). Overall, individual articles were cited by an average of 11 (mean), and a maximum of 41 PubMed-listed publications. Overall, these 64 peer-reviewed articles based on the CHSS Database were cited 692 times in PubMed-listed publications. The first CHSS peer-reviewed article was published in 1987, and during the 35 years from 1987 to 2022, inclusive, the annual number of CHSS publications has ranged from 0 to 7, with a mean of 1.8 publications per year (median = 1, mode = 1). Conclusion Congenital Heart Surgeons’ Society studies are widely referenced in the pediatric cardiac surgical literature, with over 10 citations per published article. These cohorts provide unique information unavailable in other sources of data. A tool to access this analysis is available at: [ https://data-center.chss.org/multimedia/files/2022/CAI.pdf ].

Care and outcomes for the more than 40,000 patients undergoing pediatric and congenital heart surgery in the United States annually are known to vary widely. While consensus recommendations have been published across numerous fields as one mechanism to promote a high level of care delivery across centers, it has been more than two decades since the last pediatric heart surgery recommendations were published in the United States. More recent guidance is lacking, and collaborative efforts involving the many disciplines engaged in caring for these children have not been undertaken to date. The present initiative brings together professional societies spanning numerous care domains and congenital cardiac surgeons, pediatric cardiologists, nursing, and other healthcare professionals from diverse programs around the country to develop consensus recommendations for United States centers. The focus of this initial work is on pediatric heart surgery, and it is recommended that future efforts focus in detail on the adult congenital population. We describe the background, rationale, and methodology related to this collaborative effort, and recommendations put forth for Essential Care Centers (essential services necessary for any program), and Comprehensive Care Centers (services to optimize comprehensive and high-complexity care), encompassing structure, process, and outcome metrics across 14 domains.

Every effort must be made by the leaders in our field, as well as by every individual cardiothoracic surgeon, to assure equal opportunity for all cardiothoracic surgeons, regardless of race, gender or any other sociodemographic source of bias. Every effort must be made by every surgeon, not just those in particular leadership roles. Opportunities for advancement must be equal in multiple domains, including clinical practice, patient referral, clinical leadership, academic leadership, institutional leadership and leadership in professional medical and surgical societies. Such actions to minimize bias and promote inclusivity will also ensure that cardiothoracic surgical care is provided by a workforce that represents the diversity of patients whom we serve. In the final analysis, it is an absolute fact that gender differences in payments to cardiothoracic surgeons are absolutely unacceptable and cannot be tolerated.

Objectives: STAT Mortality Categories (developed 2009) stratify congenital heart surgery procedures into groups of increasing mortality risk to characterize case mix of congenital heart surgery providers. This update of the STAT Mortality Score and Categories is empirically based for all procedures and reflects contemporary outcomes. Methods: Cardiovascular surgical operations in the Society of Thoracic Surgeons Congenital Heart Surgery Database (January 1, 2010 – June 30, 2017) were analyzed. In this STAT 2020 Update of the STAT Mortality Score and Categories, the risk associated with a specific combination of procedures was estimated under the assumption that risk is determined by the highest risk individual component procedure. Operations composed of multiple component procedures were eligible for unique STAT Scores when the statistically estimated mortality risk differed from that of the highest risk component procedure. Bayesian modeling accounted for small denominators. Risk estimates were rescaled to STAT 2020 Scores between 0.1 and 5.0. STAT 2020 Category assignment was designed to minimize within-category variation and maximize between-category variation. Results: Among 161,351 operations at 110 centers (19,090 distinct procedure combinations), 235 types of single or multiple component operations received unique STAT 2020 Scores. Assignment to Categories resulted in the following distribution: STAT 2020 Category 1 includes 59 procedure codes with model-based estimated mortality 0.2% to 1.3%; Category 2 includes 73 procedure codes with mortality estimates 1.4% to 2.9%; Category 3 includes 46 procedure codes with mortality estimates 3.0% to 6.8%; Category 4 includes 37 procedure codes with mortality estimates 6.9% to 13.0%; and Category 5 includes 17 procedure codes with mortality estimates 13.5% to 38.7%. The number of procedure codes with empirically derived Scores has grown by 58% (235 in STAT 2020 vs 148 in STAT 2009). Of the 148 procedure codes with empirically derived Scores in 2009, approximately one-half have changed STAT Category relative to 2009 metrics. The New STAT 2020 Scores and Categories demonstrated good discrimination for predicting mortality in an independent validation sample (July 1, 2017-June 30, 2019; sample size 46,933 operations at 108 centers) with C-statistic = 0.791 for STAT 2020 Score and 0.779 for STAT 2020 Category. Conclusions: The updated STAT metrics reflect contemporary practice and outcomes. New empirically based STAT 2020 Scores and Category designations are assigned to a larger set of procedure codes, while accounting for risk associated with multiple component operations. Updating STAT metrics based on contemporary outcomes facilitates accurate assessment of case mix.

Abstract Background Listed pediatric heart transplant patients have the highest solid‐organ waitlist mortality rate. The donor‐recipient body weight ( DRBW ) ratio is the clinical standard for allograft size matching but may unnecessarily limit a patient's donor pool. To overcome DRBW ratio limitations, two methods of performing virtual heart transplant fit assessments were developed that account for patient‐specific nuances. Method 1 uses an allograft total cardiac volume ( TCV ) prediction model informed by patient data wherein a matched allograft 3‐D reconstruction is selected from a virtual library for assessment. Method 2 uses donor images for a direct virtual transplant assessment. Methods Assessments were performed in medical image reconstruction software. The allograft model was developed using allometric/isometric scaling assumptions and cross‐validation. Results The final predictive model included gender, height, and weight. The 25th‐, 50th‐, and 75th‐percentiles for TCV percentage errors were −13% (over‐prediction), −1%, and 8% (under‐prediction), respectively. Two examples illustrating the potential of virtual assessments are presented. Conclusion Transplant centers can apply these methods to perform their virtual assessments using existing technology. These techniques have potential to improve organ allocation. With additional experience and refinement, virtual transplants may become standard of care for determining suitability of donor organ size for an identified recipient.