The Society of Thoracic Surgeons 2018 Adult Cardiac Surgery Risk Models: Part 2—Statistical Methods and Results (original) (raw)
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The Annals of thoracic surgery, 2018
The last published version of the Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database (ACSD) risk models were developed in 2008 based on patient data from 2002 to 2006 and have been periodically recalibrated. In response to evolving changes in patient characteristics, risk profiles, surgical practice, and outcomes, STS has now developed a set of entirely new risk models for adult cardiac surgery. New models were estimated for isolated coronary artery bypass grafting surgery (CABG, n = 439,092), isolated aortic or mitral valve surgery (n = 150,150), and combined valve + CABG (n = 81,588) procedures. The development set was based on July 2011 to June 2014 STS-ACSD data; validation was performed using July 2014 to December 2016 data. Separate models were developed for operative mortality, stroke, renal failure, prolonged ventilation, reoperation, composite major morbidity or mortality, and prolonged or short postoperative length of stay. Because of its low occurrence rate...
Comparison of Risk Scores for Prediction of Complications following Aortic Valve Replacement
Heart, Lung and Circulation, 2015
Aortic valve replacement (AVR) is the recommended treatment for severe symptomatic aortic valve disease as prognosis is significantly improved when compared to medical treatment [1,2]. Risk models play an important role in stratification as well as decision-making for the optimal treatment modality in high-risk patients, whether it be AVR, transcatheter aortic valve implantation (TAVI) or conservative medical therapy [1,3,4]. Although several studies have Background Risk models play an important role in stratification of patients for cardiac surgery, but their prognostic utilities for post-operative complications are rarely studied. We compared the EuroSCORE, EuroSCORE II, Society of Thoracic Surgeon's (STS) Score and an Australasian model (Aus-AVR Score) for predicting morbidities after aortic valve replacement (AVR), and also evaluated seven STS complications models in this context. Methods We retrospectively calculated risk scores for 620 consecutive patients undergoing isolated AVR at Auckland City Hospital during 2005-2012, assessing their discrimination and calibration for post-operative complications. Results Amongst mortality scores, the EuroSCORE was the best at discriminating stroke (c-statistic 0.845); the EuroSCORE II at deep sternal wound infection (c=0.748); and the STS Score at composite morbidity or mortality (c=0.666), renal failure (c=0.634), ventilation>24 hours (c=0.732), return to theatre (c=0.577) and prolonged hospital stay >14 days post-operatively (c=0.707). The individual STS complications models had a marginally higher c-statistic (c=0.634-0.846) for all complications except mediastinitis, and had good calibration (Hosmer-Lemeshow test P-value 0.123-0.915) for all complications. Conclusion The STS Score was best overall at discriminating post-operative complications and their composite for AVR. All STS complications models except for deep sternal wound infection had good discrimination and calibration for post-operative complications.
Validation and Refinement of Mortality Risk Models for Heart Valve Surgery
The Annals of Thoracic Surgery, 2005
Background. The Northern New England Cardiovascular Disease Study Group (NNE) recently published risk models for hospital mortality after heart valve surgery. The Providence Health System Cardiovascular Study Group (PHS) has been collecting similar heart valve data for 8 years, providing an ideal opportunity to both validate the NNE risk models and attempt to produce an improved model, by using some different modeling techniques. Methods. From 1997 to 2004, 3,324 patients aged 30 to 95 years underwent aortic valve replacement (AVR), and 1,596 underwent mitral valve replacement or repair (MVRR) at one of nine PHS medical centers. We used area under the receiver operating characteristic curve (c-index) to measure model discrimination, and Hosmer-Lemeshow statistic (H-L) to measure calibration. We modified the NNE models by ungrouping continuous variables, seeking optimal transformations of continuous variables, and imputing missing values by multiple regression. Results. The prevalence and the lethality of risk factors were similar in PHS and NNE patients. The NNE models fit PHS patients well: c-index (95% confidence interval) ؍ 0.75 (0.70 to 0.80) for AVR and 0.81 (0.76 to 0.86) for MVRR; H-L ؍ 3.95 (p ؍ 0.861) for AVR and 7.10 (p ؍ 0.526) for MVRR. A single PHS model performed slightly better for both positions: c-index ؍ 0.79 (0.75 to 0.83) for AVR and 0.84 (0.80 to 0.88) for MVRR; H-L ؍ 2.75 (p ؍ 0.949) for AVR and 12.21 (p ؍ 0.142) for MVRR. Conclusions. The NNE models for aortic and mitral valve surgery were successfully validated using PHS patients. Using some different statistical approaches to modeling, we produced a new, unified model for both positions.
Comparison of 19 pre-operative risk stratification models in open-heart surgery
European Heart Journal, 2006
Aims To compare 19 risk score algorithms with regard to their validity to predict 30-day and 1-year mortality after cardiac surgery. Methods and results Risk factors for patients undergoing heart surgery between 1996 and 2001 at a single centre were prospectively collected. Receiver operating characteristics (ROC) curves were used to describe the performance and accuracy. Survival at 1 year and cause of death were obtained in all cases. The study included 6222 cardiac surgical procedures. Actual mortality was 2.9% at 30 days and 6.1% at 1 year. Discriminatory power for 30-day and 1-year mortality in cardiac surgery was highest for logistic (0.84 and 0.77) and additive (0.84 and 0.77) European System for Cardiac Operative Risk Evaluation (EuroSCORE) algorithms, followed by Cleveland Clinic (0.82 and 0.76) and Magovern (0.82 and 0.76) scoring systems. None of the other 15 risk algorithms had a significantly better discriminatory power than these four. In coronary artery bypass grafting (CABG)-only surgery, EuroSCORE followed by New York State (NYS) and Cleveland Clinic risk score showed the highest discriminatory power for 30-day and 1-year mortality. Conclusion EuroSCORE, Cleveland Clinic, and Magovern risk algorithms showed superior performance and accuracy in open-heart surgery, and EuroSCORE, NYS, and Cleveland Clinic in CABG-only surgery. Although the models were originally designed to predict early mortality, the 1-year mortality prediction was also reasonably accurate.
The Annals of Thoracic Surgery, 2004
Risk models play a vital role in monitoring health care performances. Despite extensive research and widespread use of risk models in cardiac surgery, there are methodologic problems. We reviewed the methodology used for risk models for short-term mortality. The findings suggest that many risk models are developed in an ad hoc manner. Important aspects such as selection of risk factors, handling of missing values, and size of the data used for model development are not dealt with adequately. Methodologic details presented in publications are often sparse and unclear. Model development and validation processes are not always linked to the clinical aim of the model, which may affect their clinical validity. We make some suggestions in this review for improvement in methodology and reporting.
JAMA Cardiology, 2016
IMPORTANCE Cardiovascular risk assessment is a fundamental component of prevention of cardiovascular disease (CVD). However, commonly used prediction models have been formulated in primarily or exclusively white populations. Whether risk assessment in black adults is dissimilar to that in white adults is uncertain. OBJECTIVES To develop and validate risk prediction models for CVD incidence in black adults, incorporating standard risk factors, biomarkers, and subclinical disease. DESIGN, SETTING, AND PARTICIPANTS The Jackson Heart Study (JHS), a longitudinal community-based study of 5301 black adults in Jackson, Mississippi. Inclusive study dates were the date of a participant's first visit (September 2000 to March 2004) to December 31, 2011. The median (75th percentile) follow-up was 9.1 (9.7) years. The dates of the analysis were August 2013 to May 2015. Measurements included standard risk factors, including age, sex, body mass index, systolic and diastolic blood pressure, ratio of fasting total cholesterol to high-density lipoprotein cholesterol, estimated glomerular filtration rate, antihypertensive therapy, diabetes mellitus, and smoking; blood biomarkers; and subclinical disease measures, including ankle-brachial index, carotid intimal-medial thickness, and echocardiographic left ventricular hypertrophy and systolic dysfunction. MAIN OUTCOMES AND MEASURES Incident CVD event was defined as the first occurrence of myocardial infarction, coronary heart disease death, congestive heart failure, stroke, incident angina, or intermittent claudication. Model performance was compared with the American College of Cardiology/American Heart Association (ACC/AHA) CVD risk algorithm and the Framingham Risk Score (FHS) refitted to the JHS data and evaluated in the Atherosclerosis Risk in Communities (ARIC) and Multi-Ethnic Study of Atherosclerosis cohorts. RESULTS The study cohort comprised 3689 participants with mean (SD) age at baseline was 53 (11) years, and 64.8% (n = 2390) were female. Over a median of 9.1 years, 270 participants (166 women) experienced a first CVD event. A simple combination of standard CVD risk factors, B-type natriuretic peptide, and ankle-brachial index (model 6) yielded modest improvement over a model without B-type natriuretic peptide and ankle-brachial index (C statistic, 0.79; 95% CI, 0.75-0.83 [relative integrated discrimination improvement, 0.22; 95% CI, 0.15-0.30]). However, the reclassification improvement was not substantially different between model 6 and the ACC/AHA CVD Pooled Cohort risk equations or between model 6 and the FHS. The models discriminated reasonably well in the ARIC and Multi-Ethnic Study of Atherosclerosis data (C statistic range, 0.70-0.77). CONCLUSIONS AND RELEVANCE Our findings using the JHS data in the present study are valuable because they confirm that current FHS and ACC/AHA risk algorithms work well in black individuals and are not easily improved on. A unique risk calculator for black adults may not be necessary.
The American Journal of Cardiology, 2014
on behalf of the OBSERVANT Research Group Risk stratification tools used in patients with severe aortic stenosis have been mostly derived from surgical series. Although specific predictors of early mortality with transcatheter aortic valve replacement (TAVR) have been identified, the prognostic impact of their combination is unexplored. We sought to develop a simple score, using preprocedural variables, for prediction of 30-day mortality after TAVR. A total of 1,878 patients from a national multicenter registry who underwent TAVR were randomly assigned in a 2:1 manner to development and validation data sets. Baseline characteristics of the 1,256 patients in the development data set were considered as candidate univariate predictors of 30-day mortality. A bootstrap multivariate logistic regression process was used to select correlates of 30-day mortality that were subsequently weighted and integrated into a scoring system. Seven variables were weighted proportionally to their respective odds ratios for 30-day mortality (glomerular filtration rate <45 ml/min [6 points], critical preoperative state [5 points], New York Heart Association class IV [4 points], pulmonary hypertension [4 points], diabetes mellitus [4 points], previous balloon aortic valvuloplasty [3 points], and left ventricular ejection fraction <40% [3 points]). The model showed good discrimination in both the development and validation data sets (C statistics 0.73 and 0.71, respectively). Compared with the logistic European System for Cardiac Operative Risk Evaluation in the validation data set, the model showed better discrimination (C statistic 0.71 vs 0.66), goodness of fit (Hosmer-Lemeshow p value 0.81 vs 0.00), and global accuracy (Brier score 0.054 vs 0.073). In conclusion, the risk of 30-day mortality after TAVR may be estimated by combining 7 baseline clinical variables into a simple risk scoring system.
Risk-prediction for postoperative major morbidity in coronary surgery
2009
Objective: Analysis of major perioperative morbidity has become an important factor in assessment of quality of patient care. We have conducted a prospective study of a large population of patients undergoing coronary artery bypass surgery (CABG), to identify preoperative risk factors and to develop and validate risk-prediction models for peri-and postoperative morbidity. Methods: Data on 4567 patients who underwent isolated CABG surgery over a 10-year period were extracted from our clinical database. Five postoperative major morbidity complications (cerebrovascular accident, mediastinitis, acute renal failure, cardiovascular failure and respiratory failure) were analysed. A composite morbidity outcome (presence of two or more major morbidities) was also analysed. For each one of these endpoints a risk model was developed and validated by logistic regression and bootstrap analysis. Discrimination and calibration were assessed using the under the receiver operating characteristic (ROC) curve area and the Hosmer-Lemeshow (H-L) test, respectively. Results: Hospital mortality and major composite morbidity were 1.0% and 9.0%, respectively. Specific major morbidity rates were: cerebrovascular accident (2.5%), mediastinitis (1.2%), acute renal failure (5.6%), cardiovascular failure (5.6%) and respiratory failure (0.9%). The risk models developed have acceptable discriminatory power (under the ROC curve area for cerebrovascular accident [0.715], mediastinitis [0.696], acute renal failure [0.778], cardiovascular failure [0.710], respiratory failure [0.787] and composite morbidity [0.701])
European Journal of Cardio-Thoracic Surgery, 2003
Objective: Risk stratification systems are used in cardiac surgery to estimate mortality risk for individual patients and to compare surgical performance between institutions or surgeons. This study investigates the suitability of six existing risk stratification systems for these purposes. Methods: Data on 5471 patients who underwent isolated coronary artery bypass grafting at two UK cardiac centres between 1993 and 1999 were extracted from a prospective computerised clinical data base. Of these patients, 184 (3.3%) died in hospital. In-hospital mortality risk scores were calculated for each patient using the Parsonnet score, the EuroSCORE, the ACC/AHA score and three UK Bayes models (old, new complex and new simple). The accuracy for predicting mortality at an institutional level was assessed by comparing total observed and predicted mortality. The accuracy of the risk scores for predicting mortality for a patient was assessed by the Hosmer-Lemeshow test. The receiver operating characteristic (ROC) curve was used to evaluate how well a system ranks the patient with respect to their risk of mortality and can be useful for patient management. Results: Both EuroSCORE and the simple Bayes model were reasonably accurate at predicting overall mortality. However predictive accuracy at the patient level was poor for all systems, although EuroSCORE was accurate for low to medium risk patients. Discrimination was fair with the following ROC areas: Parsonnet 0.73, EuroSCORE 0.76, ACC/AHA system 0.76, old Bayes 0.77, complex Bayes 0.76, simple Bayes 0.76. Conclusions: This study suggests that two of the scores may be useful in comparing institutions. None of the risk scores provide accurate risk estimates for individual patients in the two hospitals studied although EuroSCORE may have some utility for certain patients. All six systems perform moderately at ranking the patients and so may be useful for patient management. More results are needed from other institutions to confirm that the EuroSCORE and the simple Bayes model are suitable for institutional risk-adjusted comparisons.
European Journal of Cardio-thoracic Surgery, 2007
Objective: To develop a multivariate prediction model for in-hospital mortality following aortic valve replacement. Methods: Retrospective analysis of prospectively collected data on 4550 consecutive patients undergoing aortic valve replacement between 1 April 1997 and 31 March 2004 at four hospitals. A multivariate logistic regression analysis was undertaken, using the forward stepwise technique, to identify independent risk factors for in-hospital mortality. The area under the receiver operating characteristic (ROC) curve was calculated to assess the performance of the model. The statistical model was internally validated using the technique of bootstrap resampling, which involved creating 100 random samples, with replacement, of 70% of the entire dataset. The model was also validated on 816 consecutive patients undergoing aortic valve replacement between 1 April 2004 and 31 March 2005 from the same four hospitals. Results: Two hundred and seven (4.6%) in-hospital deaths occurred. Independent variables identified with in-hospital mortality are shown with relevant co-efficient values and p-values as follows: (1) age 70-75 years: 0.7046, p < 0.001; (2) age 75-85 years: 1.1714, p < 0.001; (3) age > 85 years: 2.0339, p < 0.001; (4) renal dysfunction: 1.2307, p < 0.001; (5) New York Heart Association class IV: 0.5782, p = 0.003; (6) hypertension: 0.4203, p = 0.006; (7) atrial fibrillation: 0.604, p = 0.002; (8) ejection fraction < 30%: 0.571, p = 0.012; (9) previous cardiac surgery: 0.9193, p < 0.001; (10) non-elective surgery: 0.5735, p < 0.001; (11) cardiogenic shock: 1.1291, p = 0.009; (12) concomitant CABG: 0.6436, p < 0.001. Intercept: À4.8092. A simplified additive scoring system was also developed. The ROC curve was 0.78, indicating a good discrimination power. Bootstrapping demonstrated that estimates were stable with an average ROC curve of 0.76, with a standard deviation of 0.025. Validation on 2004-2005 data revealed a ROC curve of 0.78 and an expected mortality of 4.7% compared to the observed rate of 4.1%. Conclusions: We developed a contemporaneous multivariate prediction model for inhospital mortality following aortic valve replacement. This tool can be used in day-to-day practice to calculate patient-specific risk by the logistic equation or a simple scoring system with an equivalent predicted risk. #
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TÓM TẮT Đặt vấn đề: Can thiệp mạch vành qua da là lựa chọn điều trị đối với bệnh lý động mạch vành trong những trường hợp hẹp một hoặc hai nhánh động mạch vành, hội chứng vành cấp. Số lượng các trường hợp can thiệp mạch gia tăng dẫn đến ngày càng có nhiều bệnh nhân nhập viện phẫu thuật bắc cầu chủ vành đã có tiền sử can thiệp mạch vành. Nghiên cứu này nhằm mục tiêu 1) nhận diện các yếu tố nguy cơ phẫu thuật của các bệnh nhân có chỉ định tái tưới máu vào viện với tiền sử can thiệp mạch vành trước đó và 2) đánh giá kết quả phẫu thuật bắc cầu chủ vành ở nhóm bệnh nhân này. Đối tượng, phương pháp: Bệnh nhân có tiền sử can thiệp mạch vành qua da được phẫu thuật chương trình bắc cầu chủ vành tại Bệnh viện Trung Ương Huế. Nghiên cứu hồi cứu, mô tả. Kết quả: Trong giai đoạn từ 1/2012 - 1/2017, có 16 bệnh nhân được phẫu thuật. Tuổi trung bình là 64,6 ± 8,2, trung bình BMI - 24,7 ± 1,8, thời gian phẫu thuật sau can thiệp qua da trung bình 2 năm. Các yếu tố nguy cơ bao gồm: tăng huyết áp 8...
Journal of Cardiovascular Development and Disease
Background: TAVR is a safe alternative to surgical aortic valve replacement (SAVR); however, sex-related differences are still debated. This research aimed to examine gender differences in a real-world transcatheter aortic valve replacement (TAVR) cohort. Methods: All-comer aortic stenosis (AS) patients undergoing TAVR with a Medtronic valve across 19 Italian sites were prospectively included in the Italian Clinical Service Project (NCT01007474) between 2007 and 2019. The primary endpoint was 1-year mortality. We also investigated 3-year mortality, and ischemic and hemorrhagic endpoints, and we performed a propensity score matching to assemble patients with similar baseline characteristics. Results: Out of 3821 patients, 2149 (56.2%) women were enrolled. Compared with men, women were older (83 ± 6 vs. 81 ± 6 years, p < 0.001), more likely to present severe renal impairment (GFR ≤ 30 mL/min, 26.3% vs. 16.3%, p < 0.001) but had less previous cardiovascular events (all p < 0.0...
Perioperative outcomes of coronary artery bypass graft surgery in Johannesburg, South Africa
Journal of Cardiothoracic Surgery
Background The perioperative complications in patients with coronary artery disease undergoing coronary artery bypass graft (CABG) surgery have been reported predominantly from developed countries, with a paucity of data from sub-Saharan Africa. We aim to report on the clinical characteristics and perioperative complications in patients with obstructive coronary artery disease, managed with CABG surgery at a tertiary academic hospital in Johannesburg, South Africa. Methods We retrospectively reviewed data from adult patients who underwent CABG surgery during a 17-year period (January 2000 – December 2017). Data was collected from the cardiothoracic surgery department’s pre- and postoperative reports, the cardiology department’s medical records, and anaesthesiology’s intra-operative reports. We collected demographic, biochemical, clinical, surgical, echocardiographic, and angiographic data. Outcomes data collected included perioperative complications and mortality. Results We analyse...
2021
Background: Calculated plasma volume status (PVS) reflects volume overload based on the deviation of the estimated plasma volume (ePV) from the ideal plasma volume (iPV). Calculated PVS is associated with prognosis in the context of heart failure. This single-center study investigated the prognostic impact of PVS in patients undergoing transcatheter aortic valve implantation (TAVI). Methods: A total of 859 TAVI patients had been prospectively enrolled in an observational study and were included in the analysis. An optimal cutoff for PVS of −5.4% was determined by receiver operating characteristic curve analysis. The primary endpoint was a composite of all-cause mortality or heart failure hospitalization within 1 year after TAVI. Results: A total of 324 patients had a PVS < −5.4% (no congestion), while 535 patients showed a PVS ≥ −5.4% (congestion). The primary endpoint occurred more frequently in patients with a PVS ≥ −5.4% compared to patients with PVS < −5.4% (22.6% vs. 13.0...
Perfusion Strategy for Minimally Invasive Cardiac Surgery
Ukrainian Journal of Cardiovascular Surgery
Minimally invasive cardiac surgery (MICS) has a number of proven advantages compared to median sternotomy. Safe cannulation and perfusion are some of the main components of the success of MICS. The aim. To present our perfusion strategy and describe the methods of cannulation, technical features, contraindications and potential complications. Materials and methods. We examined the results of 1088 adult patients who underwent primary cardiac surgery in our hospital (coronary artery bypass grafting, valve surgery, aortic surgery, left ventricle repair, congenital cardiac surgery and combined procedures) from July 2017 to May 2021. Of these, 851 patients were qualified for MICS. To select a safe cannulation strategy, we performed contrast enhanced computed tomography (CT) of the aorta and main branches for all the patients, also we calculated the body surface area according to the DuBois and DuBois formula. Results. We performed 838 minimally invasive on-pump procedures, which is 98.5%...
Routine preoperative CT: Ready to roll or a step too far?
Journal of Cardiac Surgery
The incidence of stroke after coronary artery bypass grafting (CABG) is around 1.3% in the Society of Thoracic Surgeons database but carries a mortality of almost 20% (1,2). The stroke rate is even higher with aortic valve replacements with the Determining Neurologic Outcomes from Valve Operations (DeNOVO) study reporting stroke rates as high as 17% (3). It is also likely that variations in definition of stroke leads to underreporting of this event. There is thus, no denying that stroke remains the Achilles heel of cardiac surgery and efforts must be made to mitigate its occurrence.
Journal of Cardiac Surgery, 2020
Background: Patients who refuse allogeneic blood transfusions (alloBT) on the basis of religious doctrine, such as Jehovah's Witnesses (JWs), can pose a challenge when undergoing surgical procedures. During cardiac surgery, special considerations regarding surgical techniques and blood loss minimization strategies can lead to improved outcomes. Limited literature exists to guide the use of four-factor prothrombin complex concentrate (4PCC) in this patient population undergoing cardiac surgery. Study Design and Methods: This retrospective, single-center study evaluated the impact of 4PCC on hemoglobin (Hgb) change from baseline to postoperative nadir within a 7-day period among patients who refused alloBT during cardiac surgery. This study identified patients who refused alloBT from January 2011 to June 2017. Multivariable linear regression was used to control for confounding variables to evaluate the effectiveness of 4PCC. Results: During the study timeframe, 79 patients met inclusion criteria, all of whom identified as JWs, and underwent cardiac surgery. Of these, 19 received intraoperative 4PCC. Multivariable linear regression found no difference in Hgb change in patients who received 4PCC vs those who did not. No significant differences were found in mortality, thromboembolic complications, or in-hospital postoperative events. Conclusions: In JWs undergoing cardiac surgery who refuse alloBT, intraoperative use of 4PCC was not associated with a difference in Hgb change within 7 days postoperatively when adjusting for confounding variables. In the event of excessive blood loss, the utilization of 4PCC may provide a viable option in JW patients who undergo cardiac surgery where few options exist to mitigate blood loss.
Journal of Cardiovascular Development and Disease
Background: Existing prediction models for post-transplant mortality in patients bridged to heart transplantation with temporary mechanical circulatory support (tMCS) perform poorly. A more reliable model would allow clinicians to provide better pre-operative risk assessment and develop more targeted therapies for high-risk patients. Methods: We identified adult patients in the United Network for Organ Sharing database undergoing isolated heart transplantation between 01/2009 and 12/2017 who were supported with tMCS at the time of transplant. We constructed a machine learning model using extreme gradient boosting (XGBoost) with a 70:30 train:test split to predict 1-year post-operative mortality. All pre-transplant variables available in the UNOS database were included to train the model. Shapley Additive Explanations was used to identify and interpret the most important features for XGBoost predictions. Results: A total of 1584 patients were included, with a median age of 56 (interq...
Frontiers in Cardiovascular Medicine, 2021
Background: The association between Body Mass Index (BMI) and clinical outcomes following coronary artery bypass grafting (CABG) remains controversial. Our objective was to investigate the real-world relationship between BMI and in-hospital clinical course and mortality, in patients who underwent CABG.Methods: A sampled cohort of patients who underwent CABG between October 2015 and December 2016 was identified in the National Inpatient Sample (NIS) database. Outcomes of interest included in-hospital mortality, peri-procedural complications and length of stay. Patients were divided into 6 BMI (kg/m2) subgroups; (1) under-weight ≤19, (2) normal-weight 20–25, (3) over-weight 26–30, (4) obese I 31–35, (5) obese II 36–39, and (6) extremely obese ≥40. Multivariable logistic regression model was used to identify predictors of in-hospital mortality. Linear regression model was used to identify predictors of length of stay (LOS).Results: An estimated total of 48,710 hospitalizations for CABG...
Clinical Factors and Outcomes When Real-World Heart Teams Overruled STS Risk Scores in TAVR Cases
Journal of Interventional Cardiology
Objectives. This study was conducted to determine why heart teams recommended transcatheter aortic valve replacement (TAVR) versus surgical AVR (SAVR) for patients at low predicted risk of mortality (PROM) and describe outcomes of these cases. Background. Historically, referral to TAVR was based predominately on the Society of Thoracic Surgeons (STS) risk model’s PROM >3%. In selected cases, heart teams had latitude to overrule these scores. The clinical reasons and outcomes for these cases are unclear. Methods. Retrospective data were gathered for all TAVR and SAVR cases conducted by 9 hospitals between 2013 and 2017. Results. Cases included TAVR patients with STS PROM >3% (n = 2,711) and ≤3% (n = 415) and SAVR with STS PROM ≤3% (n = 1,438). Leading reasons for recommending TAVR in the PROM ≤3% group were frailty (57%), hostile chest (22%), severe lung disease (16%), and morbid obesity (13%), and 44% of cases had multiple reasons. Most postoperative and 30-day outcomes were s...
CMAJ Open
It carries a higher burden of complications, requires intensive postoperative monitoring and involves an often long er hospital length of stay (LOS) as compared with noncardiac surgery. 1 With steady improvements in surgical technique and perioperative care, cardiac surgery is increasingly being offered to frail and complex patients with higher resource needs. 2,3 The drive by many organizations for operational efficiency and competing capacity needs during the COVID-19 pandemic makes evidence-based triaging and resource allocation, founded on real-world data, an urgent priority. Prediction of intensive care unit (ICU) LOS after cardiac surgery 4-6 is important but does not fully reflect the extent of resources needed. Nonetheless, although risk factors have been identified for prolonged postoperative hospital LOS, few models are available to predict this important metric, and none are able to estimate continuous postoperative LOS with accuracy. Further, though existing models include those from the Society of Thoracic Surgeons and the EuroSCORE data sets, 7-9 they were developed to predict perioperative death and end organ morbidity and were only later validated in single-centre data sets for the purpose of predicting prolonged LOS in a binary fashion instead of estimation of continuous LOS. To better inform health resource planning, we derived and externally validated clinical models using population-based data to identify top-tier resource users and to predict continuous hospital LOS after cardiac surgery.
JAMA network open, 2022
In 2020, the Centers for Medicare & Medicaid Services revised its national coverage determination, removing the requirement to obtain review from a Medicare-approved heart transplant center to implant a durable left ventricular assist device (LVAD) for bridge-to-transplant (BTT) intent at an LVAD-only center. The association between center-level transplant availability and access to heart transplant, the gold-standard therapy for advanced heart failure (HF), is unknown. To investigate the association of center transplant availability with LVAD implant strategies and subsequent heart transplant following LVAD implant before the Centers for Medicare & Medicaid Services policy change. Surgeons Intermacs multicenter US registry database was conducted from April 1, 2012, to June 30, 2020. The population included patients with HF receiving a primary durable LVAD. The primary outcomes were implant strategy as BTT and subsequent transplant by 2 years. Covariates that might affect listing strategy and outcomes were included (eg, patient demographic characteristics, comorbidities) in multivariable models. Parameters for BTT listing were estimated using logistic regression with center-level random effects and for receipt of a transplant using a Cox proportional hazards regression model with death as a competing event. The sample included 22 221 LVAD recipients with a median age of 59.0 (IQR, 50.0-67.0) years, of whom 17 420 (78.4%) were male and 3156 (14.2%) received implants at LVAD-only centers. Receiving an LVAD at an LVAD/transplant center was associated with a 79% increased adjusted odds of BTT LVAD designation (odds ratio, 1.79; 95% CI, 1.35-2.38; P < .001). The 2-year transplant rate following LVAD implant was 25.6% at LVAD/transplant centers and 11.9% at LVAD-only centers. There was an associated 33% increased rate of transplant at LVAD/transplant centers compared with LVAD-only centers (adjusted hazard ratio, 1.33; 95% CI, 1.17-1.51) with a similar hazard for death at 2 years (adjusted hazard ratio, 0.99; 95% CI, 0.90-1.08). Receiving an LVAD at an LVAD-transplant center was associated with increased odds of BTT intent at implant and subsequent transplant receipt for patients at 2 years. The findings of this study suggest that Centers for Medicare & Medicaid Services policy change (continued) Key Points Question Is the presence of a heart transplant program associated with differential evaluation for transplant or transplant among patients who receive a left ventricular assist device (LVAD)? Findings In this cohort study of 22 221 LVAD recipients from the Society of Thoracic Surgeons Intermacs database, patients receiving durable LVAD at centers that also performed heart transplants were significantly more likely to receive an LVAD as a bridge to transplant. In addition, patients treated at a combined LVAD/transplant center were more likely to receive a heart transplant in the subsequent 2 years. Meaning The findings of this study suggest that the increased use of LVAD at centers that do not perform transplants has the potential to contribute to inequities in access to heart transplant, the gold-standard therapy for advanced heart failure.
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Interactive CardioVascular and Thoracic Surgery, 2013
The aim of this study was to compare additive and logistic European System for Cardiac Operative Risk Evaluation (EuroSCORE), EuroSCORE II and the Society of Thoracic Surgeons (STS) models in calculating mortality risk in a Turkish cardiac surgical population. METHODS: The current patient population consisted of 428 patients who underwent isolated coronary artery bypass grafting (CABG) between 2004 and 2012, extracted from the TurkoSCORE database. Observed and predicted mortalities were compared for the additive/logistic EuroSCORE, EuroSCORE II and STS risk calculator. The area under the receiver operating characteristics curve (AUC) values were calculated for these models to compare predictive power. RESULTS: The mean patient age was 74.5 ± 3.9 years at the time of surgery, and 35.0% were female. For the entire cohort, actual hospital mortality was 7.9% (n = 34; 95% confidence interval [CI] 5.4-10.5). However, the additive EuroSCORE-predicted mortality was 6.4% (P = 0.23 vs observed; 95% CI 6.2-6.6), logistic EuroSCORE-predicted mortality was 7.9% (P = 0.98 vs observed; 95% CI 7.3-8.6), EuroSCORE II-predicted mortality was 1.7% (P = 0.00 vs observed; 95% CI 1.6-1.8) and STS predicted mortality was 5.8% (P = 0.10 vs observed; 95% CI 5.4-6.2). The mean predictive performance of the analysed models for the entire cohort was fair, with 0.7 (95% CI 0.60-0.79). AUC values for additive EuroSCORE, logistic EuroSCORE, EuroSCORE II and STS risk calculator were 0.70 (95% CI 0.60-0.79), 0.70 (95% CI 0.59-0.80), 0.72 (95% CI 0.62-0.81) and 0.62 (95% CI 0.51-0.73), respectively. CONCLUSIONS: EuroSCORE II significantly underestimated mortality risk for Turkish cardiac patients, whereas additive and logistic EuroSCORE and STS risk calculators were well calibrated.
Risk stratification in heart surgery: comparison of six score systems
European Journal of Cardio-Thoracic Surgery, 2000
Objective: Risk scores have become an important tool in patient assessment, as age, severity of heart disease, and comorbidity in patients undergoing heart surgery have considerably increased. Various risk scores have been developed to predict mortality after heart surgery. However, there are signi®cant differences between scores with regard to score design and the initial patient population on which score development was based. It was the purpose of our study to compare six commonly used risk scores with regard to their validity in our patient population. Methods: Between September 1, 1998 and February 28, 1999, all adult patients undergoing heart surgery with cardiopulmonary bypass in our institution were preoperatively scored using the initial Parsonnet, Cleveland Clinic, French, Euro, Pons, and Ontario Province Risk (OPR) scores. Postoperatively, we registered 30-day mortality, use of mechanical assist devices, renal failure requiring hemodialysis or hemo®ltration, stroke, myocardial infarction, and duration of ventilation and intensive care stay. Score validity was assessed by calculating the area under the ROC curve. Odds ratios were calculated to investigate the predictive relevance of risk factors. Results: Follow-up was able to be completed in 504 prospectively scored patients. Receiver operating characteristics (ROC) curve analysis for mortality showed the best predictive value for the Euro score. Predictive values for morbidity were considerably lower than predictive values for mortality in all of the investigated score systems. For most risk factors, odds ratios for mortality were substantially different from ratios for morbidity. Conclusions: Among the investigated scores, the Euro score yielded the highest predictive value in our patient population. For most risk factors, predictive values for morbidity were substantially different from predictive values for mortality. Therefore, development of speci®c morbidity risk scores may improve prediction of outcome and hospital cost. Due to the heterogeneity of morbidity events, future score systems may have to generate separate predictions for mortality and major morbidity events. q
The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Introduction
The Annals of Thoracic Surgery, 2009
Surgeons National Adult Cardiac Surgery Database (STS NCD) was developed nearly 2 decades ago. Since its inception, the number of participants has grown dramatically, patient acuity has increased, and overall outcomes have consistently improved. To adjust for these and other changes, all STS risk models have undergone periodic revisions. This report provides a detailed description of the 2008 STS risk model for coronary artery bypass grafting surgery (CABG).
Cardiac Surgery Risk Models: A Position Article
The Annals of Thoracic Surgery, 2004
Differences in medical outcomes may result from disease severity, treatment effectiveness, or chance. Because most outcome studies are observational rather than randomized, risk adjustment is necessary to account for case mix. This has usually been accomplished through the use of standard logistic regression models, although Bayesian models, hierarchical linear models, and machine-learning techniques such as neural networks have also been used. Many factors are essential to insuring the accuracy and usefulness of such models, including selection of an appropriate clinical database, inclusion of critical core variables, precise definitions for predictor variables and endpoints, proper model development, validation, and audit. Risk models may be used to assess the impact of specific predictors on outcome, to aid in patient counseling and treatment selection, to profile provider quality, and to serve as the basis of continuous quality improvement activities.
Objective: The Revised Cardiac Risk Index (RCRI) is a widely used model for predicting cardiac events after noncardiac surgery. We compared the accuracy of the RCRI with a new, vascular surgery-specific model developed from patients within the Vascular Study Group of New England (VSGNE). Methods: We studied 10,081 patients who underwent nonemergent carotid endarterectomy (CEA; n 5293), lower extremity bypass (LEB; n 2673), endovascular abdominal aortic aneurysm repair (EVAR; n 1005), and open infrarenal abdominal aortic aneurysm repair (OAAA; n 1,110) within the VSGNE from 2003 to 2008. First, we analyzed the ability of the RCRI to predict in-hospital major adverse cardiac events, including myocardial infarction (MI), arrhythmia, or congestive heart failure (CHF) in the VSGNE cohort. Second, we used a derivation cohort of 8208 to develop a new cardiac risk prediction model specifically for vascular surgery patients. Chi-square analysis identified univariate predictors, and multivariate logistic regression was used to develop an aggregate and four procedure-specific risk prediction models for cardiac complications. Calibration and model discrimination were assessed using Pearson correlation coefficient and receiver operating characteristic (ROC) curves. The ability of the model to predict cardiac complications was assessed within a validation cohort of 1873. Significant predictors were converted to an integer score to create a practical cardiac risk prediction formula. Results: The overall incidence of major cardiac events in the VSGNE cohort was 6.3% (2.5% MI, 3.9% arrhythmia, 1.8% CHF). The RCRI predicted risk after CEA reasonably well but substantially underestimated risk after LEB, EVAR, and OAAA for low-and higher-risk patients. Across all VSGNE patients, the RCRI underestimated cardiac complications by 1.7-to 7.4-fold based on actual event rates of 2.6%, 6.7%, 11.6%, and 18.4% for patients with 0, 1, 2, and >3 risk factors. In multivariate analysis of the VSGNE cohort, independent predictors of adverse cardiac events were (odds ratio [OR]) increasing age (1.7-2.8), smoking (1.3), insulin-dependent diabetes (1.4), coronary artery disease (1.4), CHF (1.9), abnormal cardiac stress test (1.2), long-term-blocker therapy (1.4), chronic obstructive pulmonary disease (1.6), and creatinine >1.8 mg/dL (1.7). Prior cardiac revascularization was protective (OR, 0.8). Our aggregate model was well calibrated (r 0.99, P < .001), demonstrating moderate discriminative ability (ROC curve 0.71), which differed only slightly from the procedure-specific models (ROC curves: CEA, 0.74; LEB, 0.72; EVAR, 0.74; OAAA, 0.68). Rates of cardiac complications for patients with 0 to 3, 4, 5, and >6 VSG risk factors were 3.1%, 5.0%, 6.8%, and 11.6% in the derivation cohort and 3.8%, 5.2%, 8.1%, and 10.1% in the validation cohort. The VSGNE cardiac risk model more accurately predicted the actual risk of cardiac complications across the four procedures for low-and higher-risk patients than the RCRI. When the VSG Cardiac Risk Index (VSG-CRI) was used to score patients, six categories of risk ranging from 2.6% to 14.3% (score of 0-3 to 8) were discernible. Conclusions: The RCRI substantially underestimates in-hospital cardiac events in patients undergoing elective or urgent vascular surgery, especially after LEB, EVAR, and OAAA. The VSG-CRI more accurately predicts in-hospital cardiac events after vascular surgery and represents an important tool for clinical decision making. (J Vasc Surg 2010;52:674-83.) Risk prediction models are widely used to estimate the likelihood of an adverse outcome for individual patients in order to select the best treatment option. These models have been applied successfully in a number of disease pro
Risk models for cardiac valve surgery
ACC Current Journal Review, 2005
Medical research often involves the comparison of different treatments, procedures, or providers. In each of these situations, it is necessary to account for differences in the baseline severity of illness and other clinical characteristics of patients prior to their treatment (case-mix), as these may substantially impact their outcomes. Because most medical and surgical research is conducted using nonrandomized observational data, some form of risk adjustment is typically used to retrospectively account for such differences in casemix. When the outcome of interest is binary, such as mortality, multivariable logistic regression is the most commonly used method to develop such risk models.
The Annals of Thoracic Surgery, 2013
Background. New York (NY) valve and valve/coronary artery bypass grafting (CABG) mortality risk models, developed from operations performed in 2007 to 2009, have just been published. These models were validated using NY data from 2004 to 2006. The authors stated that their models "should also be validated by testing them against non-New York populations." Thus, we validated the NY models with the Providence Health & Services-Swedish Health Services (PH&S-SHS) cardiac surgical data and also compared them with The Society of Thoracic Surgeons (STS) mortality risk models. Methods. The PH&S-SHS validation data set contained 4,021 isolated valve and 2,406 valve/CABG operations, performed from 2008 to 2012. The risk models (NY logistic and score models and the STS models) were recalibrated to equalize the expected and observed number of deaths. Discrimination was tested by C statistics and calibration by Hosmer-Lemeshow statistics. Results. PH&S-SHS operative mortality rates were 2.6% and 5.5% in the valve and valve/CABG operations, respectively, and were lower than the NY rates. The C statistics for the NY logistic valve and valve/CABG models were 0.777 and 0.727, respectively, and were very similar for the NY score models. Calibration was good for the NY valve model (p ؍ 0.85), but not for the NY valve/CABG model (p ؍ 0.01). The STS models had better discrimination than NY models and good calibration. Conclusions. The NY logistic and score models for valve operations fit the PH&S-SHS data well with acceptable discrimination and good calibration. The NY models for valve/CABG operations fit the PH&S-SHS data with acceptable discrimination and poor calibration. STS logistic regression models fit the PH&S-SHS data somewhat better.
Journal of the American College of Surgeons, 2009
BACKGROUND: The University HealthSystem Consortium (UHC) mortality risk adjustment models are increasingly being used as benchmarks for quality assessment. But these administrative database models may include postoperative complications in their adjustments for preoperative risk. The purpose of this study was to compare the performance of the UHC with the Society of Thoracic Surgeons (STS) risk-adjusted mortality models for adult cardiac surgery and evaluate the contribution of postoperative complications on model performance. STUDY DESIGN: We identified adult cardiac surgery patients with mortality risk estimates in both the UHC and Society of Thoracic Surgeons databases. We compared the predictive performance and calibration of estimates from both models. We then reestimated both models using only patients without any postoperative complications to determine the relative contribution of adjustments for postoperative events on model performance.
European Journal of Cardio-Thoracic Surgery, 2002
The aim of the present study was to evaluate the performance of three different preoperative risk models in the prediction of postoperative morbidity and mortality in coronary artery bypass (CAB) surgery. Methods: Data on 1132 consecutive CAB patients were prospectively collected, including preoperative risk factors and postoperative morbidity and in-hospital mortality. The preoperative risk models CABDEAL, EuroSCORE and Cleveland model were used to predict morbidity and mortality. A C statistic (receiver operating characteristic (ROC) curve) was used to test the discrimination of these models. Results: The area under the ROC curve for morbidity was 0.772 for the CABDEAL, 0.694 for the EuroSCORE and 0.686 for the Cleveland model. Major morbidity due to postoperative complications occurred in 268 patients (23.6%). The mortality rate was 3.4% (n ¼ 38 patients). The ROC curve areas for prediction of mortality were 0.711 for the CABDEAL, 0.826 for the EuroSCORE and 0.858 for the Cleveland model. Conclusions: The CABDEAL model was initially developed for the prediction of major morbidity. Thus, it is not surprising that this model evinced the highest predictive value for increased morbidity in this database. Both the Cleveland and the EuroSCORE models were better predictive of mortality. These results have implications for the selection of risk indices for different purposes. The simple additive CABDEAL model can be used as a hand-held model for preoperative estimation of patients' risk of postoperative morbidity, while the EuroSCORE and Cleveland models are to be preferred for the prediction of mortality in a large patient sample. q
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