Biomedical subjects

Sean M O'Brien

Publications and source records attributed to Sean M O'Brien.

9 recordsLinked to original sources

PubMed2006

Bedside tool for predicting the risk of postoperative dialysis in patients undergoing cardiac surgery.

BACKGROUND: Estimation of an individual patient's risk for postoperative dialysis can support informed clinical decision making and patient counseling. METHODS AND RESULTS: To develop a simple bedside risk algorithm for estimating patients' probability for dialysis after cardiac surgery, we evaluated data of 449,524 patients undergoing coronary artery bypass grafting (CABG) and/or valve surgery and enrolled in >600 hospitals participating in the Society of Thoracic Surgeons National Database (2002-2004). Logistic regression was used to identify major predictors of postoperative dialysis. Model coefficients were then converted into an additive risk score and internally validated. The model also was validated in a second sample of 86,009 patients undergoing cardiac surgery from January to June 2005. Postoperative dialysis was needed in 6451 patients after cardiac surgery (1.4%), ranging from 1.1% for isolated CABG procedures to 5.1% for CABG plus mitral valve surgery. Multivariable analysis identified preoperative serum creatinine, age, race, type of surgery (CABG plus valve or valve only versus CABG only), diabetes, shock, New York Heart Association class, lung disease, recent myocardial infarction, and prior cardiovascular surgery to be associated with need for postoperative dialysis (c statistic=0.83). The risk score accurately differentiated patients' need for postoperative dialysis across a broad risk spectrum and performed well in patients undergoing isolated CABG, off-pump CABG, isolated aortic valve surgery, aortic valve surgery plus CABG, isolated mitral valve surgery, and mitral valve surgery plus CABG (c statistic=0.83, 0.85, 0.81, 0.75, 0.80, and 0.75, respectively). CONCLUSIONS: Our study identifies the major patient risk factors for postoperative dialysis after cardiac surgery. These risk factors have been converted into a simple, accurate bedside risk tool. This tool should facilitate improved clinician-patient discussions about risks of postoperative dialysis.

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PubMed2006

Contemporary impact of state certificate-of-need regulations for cardiac surgery: an analysis using the Society of Thoracic Surgeons' National Cardiac Surgery Database.

BACKGROUND: Prior research using administrative data associated certificate-of-need (CON) regulation for open heart surgery with higher hospital coronary artery bypass grafting (CABG) volume and lower CABG operative mortality rates in elderly patients. It is unclear whether these findings apply in a general population and after controlling for detailed clinical characteristics and region. METHODS AND RESULTS: Using the Society of Thoracic Surgeons' (STS) National Cardiac Surgery Database, we examined isolated CABG surgery volume, operative mortality, and the composite end point of operative mortality or major morbidity for the years 2000 to 2003. The presence of CON regulations for open heart surgery was ascertained from the National Directory of the American Health Policy Association and by contacting CON administrators. Results were analyzed nationally, by state, and by region (West, Northeast, Midwest, South) and were adjusted for clinical factors and both population density and region with mixed-effects hierarchical logistic regression models. During 2000 to 2003, there were 314,710 isolated CABG surgeries performed at 294 STS hospitals in CON states (n=27, including Washington, DC) and 280 512 procedures at 343 STS hospitals in non-CON states (n=24). Patient clinical characteristics were similar among CON and non-CON hospitals. States with CON regulations tended to have higher population densities and had significantly higher median hospital annual CABG volumes in each of the years 2000 to 2003 (P<0.005). This difference remained significant after adjustment for region and population density. Operative mortality was 2.52% for CON versus 2.62% for non-CON states (P=0.32). There was a significant association between CON law and operative mortality in the South. After adjustment for patient risk factors and region, there was a marginally significant reduction of mortality risk in states with CON regulation (adjusted OR 0.92, 95% CI 0.86 to 1.00). However, this difference was not statistically significant when a revised model accounted for random state effects. Similar volume and outcomes results were seen when the analysis was repeated with data from the national Medicare database. CONCLUSIONS: CON states have significantly higher hospital CABG surgery volumes but similar mortality compared with non-CON states. CON regulation alone is not a sufficient mechanism to ensure quality of care for CABG surgery.

Certificate of Need↗

PubMed2006

Impact of renal dysfunction on outcomes of coronary artery bypass surgery: results from the Society of Thoracic Surgeons National Adult Cardiac Database.

BACKGROUND: Although patients with end-stage renal disease are known to be at high risk for mortality after coronary artery bypass graft (CABG) surgery, the impact of lesser degrees of renal impairment has not been well studied. The purpose of this study was to compare outcomes in patients undergoing CABG with a range from normal renal function to dependence on dialysis. METHODS AND RESULTS: We reviewed 483,914 patients receiving isolated CABG from July 2000 to December 2003, using the Society of Thoracic Surgeons National Adult Cardiac Database. Glomerular filtration rate (GFR) was estimated for patients with the use of the Modification of Diet in Renal Disease study formula. Multivariable logistic regression was used to determine the association of GFR with operative mortality and morbidities (stroke, reoperation, deep sternal infection, ventilation >48 hours, postoperative stay >2 weeks) after adjustment for 27 other known clinical risk factors. Preoperative renal dysfunction (RD) was common among CABG patients, with 51% having mild RD (GFR 60 to 90 mL/min per 1.73 m2, excludes dialysis), 24% moderate RD (GFR 30 to 59 mL/min per 1.73 m2, excludes dialysis), 2% severe RD (GFR <30 mL/min per 1.73 m2, excludes dialysis), and 1.5% requiring dialysis. Operative mortality rose inversely with declining renal function, from 1.3% for those with normal renal function to 9.3% for patients with severe RD not on dialysis and 9.0% for those who were dialysis dependent. After adjustment for other covariates, preoperative GFR was one of the most powerful predictors of operative mortality and morbidities. CONCLUSIONS: Preoperative RD is common in the CABG population and carries important prognostic importance. Assessment of preoperative renal function should be incorporated into clinical risk assessment and prediction models.

Coronary Artery Bypass↗

PubMed2006

Contemporary performance of surgical ventricular restoration procedures: data from the Society of Thoracic Surgeons' National Cardiac Database.

BACKGROUND: Surgical ventricular restoration (SVR) is an operation that demonstrates promise to improve outcomes for patients with left ventricular dysfunction. Current use and operative outcomes of SVR have come from centers of expertise, and operative risks of SVR in community practice are unknown. We sought to characterize the performance of SVR nationally and describe the acute risks of mortality and major morbidity plus predictors of adverse outcomes. METHODS: We identified patients undergoing an SVR procedure at US hospitals participating in the Society of Thoracic Surgeons (STS) National Cardiac Database from January 2002 to June 2004. Baseline characteristics, operative characteristics, clinical outcomes, and predictors of adverse procedural outcomes were analyzed. RESULTS: There were 731 patients who underwent SVR at 141 of STS's 576 hospitals, and 20 centers performed 10 SVR procedures or more. The operative mortality was 9.3%; reoperation in 14.1%, stroke in 3.3%, renal failure in 8.1%, and prolonged ventilation in 21.5%. Combined death or major complications occurred in 33.5%. Major predictors of this combined end point were age, female sex, creatinine > or = 2 mg/dL, insulin-dependent diabetes, myocardial infarction within 1 week, history of congestive heart failure, 3-vessel coronary disease, severe mitral insufficiency, and status of surgery. CONCLUSION: This study provides a first look at use and outcomes of SVR in a national sample. Although a quarter of STS sites are performing SVR, most have limited experience and perioperative events are somewhat higher than prior selected series. Further studies of SVR are needed to improve patient selection and procedural performance.

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PubMed2006

Determinants of operative mortality in valvular heart surgery.

OBJECTIVE: In some respects, outcome reporting in valvular surgery has been hampered by focusing on specific populations, reluctance to publish high-risk subgroups, and possibly skewed or inadequate samples. The goal of this study was to evaluate risk factors for operative mortality comprehensively across the entire spectrum of cardiac valvular procedures over the past decade. METHODS: All 409,904 valve procedures in the Society of Thoracic Surgeons database performed between 1994 and 2003 were assessed, and Society of Thoracic Surgeons preoperative and operative variables were related to operative mortality by using a multivariable logistic regression model. Data were greater than 95% complete, and the relative importance of relevant risk factors was determined by ranking odds ratios. The analysis had a high predictive power, with a C statistic of 0.735. RESULTS: In the model, 19 variables independently influenced operative mortality (all P < .01). The most significant was nonelective (acute) presentation (odds ratios, 2.11), followed by advanced age (odds ratios, 1.88), reoperation (odds ratios, 1.61), endocarditis (odds ratios, 1.59), and coronary disease (odds ratios, 1.58). Generally, valve replacement was associated with higher mortality than repair (odds ratios, 1.52). Overall, female gender was very important (odds ratios, 1.37), and earlier year of operation increased risk (odds ratios, 1.34), implying improving outcomes over time. Although any single comorbidity, on average, was only moderately contributory (odds ratios, 1.19), specific comorbidities, such as renal failure, or multiple comorbidities in a given patient could be very significant. Aortic root reconstruction carried the highest risk (odds ratios, 2.78), followed by tricuspid valve surgery (odds ratios, 2.26), multiple valve procedures (odds ratios, 2.06), and then isolated mitral (odds ratios, 1.47), pulmonic (odds ratios, 1.29), and aortic (reference procedure) operations. Reduced ejection fraction and severity of valve lesion were relatively less important (odds ratios, 1.34 and 0.83, respectively). CONCLUSIONS: These data illustrate the significance of acute presentation in determining operative risk, and earlier surgical intervention under elective conditions might be emphasized for all types of significant valve lesions. Because aortic root reconstruction doubles mortality compared with simple aortic valve procedures, root replacement should be reserved for specific root pathology. Finally, issues related to reoperation, endocarditis, valve repair, gender, and the various procedures deserve more detailed examination.

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PubMed2005

Clinical predictors of major infections after cardiac surgery.

BACKGROUND: Major infections are infrequent but important complications of cardiac surgery. Predicting their occurrence is essential for future prevention. The objective of the current investigation was to create and validate a bedside scoring system to estimate patient risk for major infection (mediastinitis, thoracotomy or vein harvest site infection, or septicemia) after coronary artery bypass grafting. METHODS AND RESULTS: Using the Society of Thoracic Surgeons National Cardiac Database, we analyzed 331 429 coronary artery bypass grafting cases from January 1, 2002, to December 31, 2003, to identify risk factors for major infection. Using logistic regression, 2 models were generated and validated using split-sample validation: (1) One limited to preoperative characteristics (preop model) and (2) one model including both preoperative and intraoperative characteristics (combined model). Major infection occurred in 11 636 patients (3.51%) (25.1% mediastinitis, 32.6% saphenous harvest site, 35.0% septicemia, 0.5% thoracotomy, 6.8% multiple sites). Patients with major infection had significantly higher mortality (17.3% versus 3.0%, P<0.0001) and postoperative length of stay >14 days (47.0% versus 5.9%, P<0.0001) than patients without major infection. Both the preop model (c-index 0.697) and combined model (c-index: 0.708) successfully discriminated between high- and low-risk patients. A simplified risk scoring system of 12 variables accurately predicted risk for major infection. CONCLUSIONS: We identified and validated a model that can identify patients undergoing cardiac surgery who are at high risk for major infection. These high-risk patients may be targeted for perioperative intervention strategies to reduce rates of major infection.

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PubMed2005

Surgical treatment of mitral valve endocarditis in North America.

BACKGROUND: Several single-institution series have suggested the feasibility and effectiveness of mitral valve repair for infective endocarditis (IE). METHODS: We examined 6627 patients with IE undergoing mitral valve surgery at 661 Society of Thoracic Surgeons-participating centers in 1994 to 2003. RESULTS: The diagnosis of IE was assigned to 5.8% (6,627 of 114,934) of patients having mitral valve surgery. The overall frequency of mitral valve repair for IE was 29.7% (1,965 of 6,627). Mitral valve repair was less frequently used for patients with active IE (423 of 2,654; 15.9%) than those with treated IE (1,459 of 3,570; 40.9%). Operative mortality was 3.7% (72 of 1,965) for mitral valve repair and 10.8% (502 of 4,662) for mitral valve replacement. Mortality rates were lower for patients with treated IE compared with active IE. After adjusting for multiple preoperative risk factors, mitral valve repair (odds ratio, 0.67; 95% confidence interval, 0.51 to 0.88) was associated with a significantly lower risk of death. Active (versus treated) IE (odds ratio, 2.12; 95% confidence interval, 1.68 to 2.68) and recent cerebrovascular accident (odds ratio, 1.71; 95% confidence interval, 1.28 to 2.31) were independent predictors of mortality. CONCLUSIONS: Mitral valve repair is less commonly applied for IE compared with other indications for mitral valve surgery. Patients with active IE were less likely to receive repair than those with treated IE. Mitral valve repair was associated with a lower risk of mortality. These results provide support for performing mitral valve repair when technically feasible in the setting of IE.

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PubMed2004

Cutpoint selection for categorizing a continuous predictor.

This article presents a new approach for choosing the number of categories and the location of category cutpoints when a continuous exposure variable needs to be categorized to obtain tabular summaries of the exposure effect. The optimum categorization is defined as the partition that minimizes a measure of distance between the true expected value of the outcome for each subject and the estimated average outcome among subjects in the same exposure category. To estimate the optimum partition, an efficient nonparametric estimate of the unknown regression function is substituted into a formula for the asymptotically optimum categorization. This new approach is easy to implement and it outperforms existing cutpoint selection methods.

Age Factors↗

PubMed2004

Bayesian multivariate logistic regression.

Bayesian analyses of multivariate binary or categorical outcomes typically rely on probit or mixed effects logistic regression models that do not have a marginal logistic structure for the individual outcomes. In addition, difficulties arise when simple noninformative priors are chosen for the covariance parameters. Motivated by these problems, we propose a new type of multivariate logistic distribution that can be used to construct a likelihood for multivariate logistic regression analysis of binary and categorical data. The model for individual outcomes has a marginal logistic structure, simplifying interpretation. We follow a Bayesian approach to estimation and inference, developing an efficient data augmentation algorithm for posterior computation. The method is illustrated with application to a neurotoxicology study.

Algorithms↗