Outcomes after bioprosthetic versus mechanical mitral valve replacement for infective endocarditis in the United States.

Objective: In patients who underwent mitral valve replacement for infectious endocarditis, we evaluated the association of prosthesis choice with readmission rates and causes (the primary outcomes), as well as with in-hospital mortality, cost, and length of stay (the secondary outcomes). Methods: Patients with infectious endocarditis who underwent isolated mitral valve replacement from January 2016 to December 2018 were identified in the United States Nationwide Readmissions Database and stratified by valve type. Propensity score matching was used to compare adjusted outcomes. Results: A weighted total of 4206 patients with infectious endocarditis underwent bioprosthetic mitral valve replacement (n = 3132) and mechanical mitral valve replacement (n = 1074) during the study period. Patients in the bioprosthetic mitral valve replacement group were older than those in the mechanical mitral valve replacement group (median 57 vs 46 y, P < .001). After propensity matching, the bioprosthetic mitral valve replacement group (n = 1068) had similar in-hospital mortality, length of stay, and costs compared with the mechanical mitral valve replacement group (n = 1056). Overall, 90-day readmission rates were high (28.9%) and comparable for bioprosthetic mitral valve replacement (30.5%) and mechanical mitral valve replacement (27.5%, P = .4). Likewise, there was no difference in readmissions over a calendar year by prosthesis type. Readmissions for infection and bleeding were common for both bioprosthetic mitral valve replacement and mechanical mitral valve replacement groups. Conclusions: Outcomes and readmission rates were similar for mechanical mitral valve replacement and bioprosthetic mitral valve replacement in infectious endocarditis, suggesting that valve choice should not be determined by endocarditis status. Additionally, strategies to mitigate readmission for infection and bleeding are needed for both groups.

Development of a Sensor Technology to Objectively Measure Dexterity for Cardiac Surgical Proficiency.

BACKGROUND: Technical skill is essential for good outcomes in cardiac surgery. However, no objective methods exist to measure dexterity while performing surgery. The purpose of this study was to validate sensor-based hand motion analysis (HMA) of technical dexterity while performing a graft anastomosis within a validated simulator. METHODS: Surgeons at various training levels performed an anastomosis while wearing flexible sensors (BioStamp nPoint, MC10 Inc) with integrated accelerometers and gyroscopes on each hand to quantify HMA kinematics. Groups were stratified as experts (n = 8) or novices (n = 18). The quality of the completed anastomosis was scored using the 10 Point Microsurgical Anastomosis Rating Scale (MARS10). HMA parameters were compared between groups and correlated with quality. Logistic regression was used to develop a predictive model from HMA parameters to distinguish experts from novices. RESULTS: Experts were faster (11 ± 6 minutes vs 21 ± 9 minutes; P = .012) and used fewer movements in both dominant (340 ± 166 moves vs 699 ± 284 moves; P = .003) and nondominant (359 ± 188 moves vs 567 ± 201 moves; P = .02) hands compared with novices. Experts' anastomoses were of higher quality compared with novices (9.0 ± 1.2 MARS10 vs 4.9 ± 3.2 MARS10; P = .002). Higher anastomosis quality correlated with 9 of 10 HMA parameters, including fewer and shorter movements of both hands (dominant, r = -0.65, r = -0.46; nondominant, r = -0.58, r = -0.39, respectively). CONCLUSIONS: Sensor-based HMA can distinguish technical dexterity differences between experts and novices, and correlates with quality. Objective quantification of hand dexterity may be a valuable adjunct to training and education in cardiac surgery training programs.

Penetrating cardiac injury: a narrative review.

Background and Objective: Penetrating cardiac trauma is rare but can cause life-threatening complications. Survival is dependent on prompt diagnosis and treatment. Given the low incidence and life-threatening implications, it is difficult to study in large prospective studies. The current literature regarding penetrating cardiac trauma comes primarily from large, experienced trauma centers and military sources. Understanding the history, current literature and even expert opinion can help with effectively treating injury promptly to maximize survival after penetrating cardiac trauma. We aimed to review the etiology and history of penetrating cardiac trauma. We review the prehospital treatment and initial diagnostic modalities. We review the incisional approaches to treatment including anterolateral thoracotomy, median sternotomy and subxiphoid window. The repair of atrial, ventricular and coronary injuries are also addressed in our review. The purpose of this paper is to perform a narrative review to better describe the history, etiology, presentation, and management of penetrating cardiac trauma. Methods: A narrative review was preformed synthesizing literature from MEDLINE and bibliographic review from identified publications. Studies were included based on relevance without exclusion to time of publication or original publication language. Key Content and Findings: Sonographic identification of pericardial fluid can aid in diagnosis of patients too unstable for CT. Anterolateral thoracotomy should be used for emergent repairs and initial stabilization. A median sternotomy can be used for more stable patients with known injuries. Carefully placed mattress sutures can be useful for repair of injuries surrounding coronary vessels to avoid devascularization. Conclusions: Penetrating cardiac trauma is life threatening and requires prompt workup and treatment. Trauma algorithms should continue to refine and be clear on which patients should undergo an emergency department (ED) thoracotomy, median sternotomy and further imaging.

Coronary artery bypass grafting at safety-net versus non-safety-net hospitals.

Objectives: Safety-net hospitals (SNHs) provide essential services to predominantly underserved patients regardless of their ability to pay. We hypothesized that patients who underwent coronary artery bypass grafting (CABG) would have inferior observed outcomes at SNHs compared with non-SNHs but that matched cohorts would have comparable outcomes. Methods: We queried the Nationwide Readmissions Database for patients who underwent isolated CABG from 2016 to 2018. We ranked hospitals by the percentage of all admissions in which the patient was uninsured or insured with Medicaid; hospitals in the top quartile were designated as SNHs. We used propensity-score matching to mitigate the effect of confounding factors and compare outcomes between SNHs and non-SNHs. Results: A total of 525,179 patients underwent CABG, including 96,133 (18.3%) at SNHs, who had a greater burden of baseline comorbidities (median Elixhauser score 8 vs 7; P = .04) and more frequently required urgent surgery (57.1% vs 52.8%; P < .001). Observed in-hospital mortality (2.1% vs 1.8%; P = .004) and major morbidity, length of stay (9 vs 8 days; P < .001), cost ($46,999 vs $38,417; P < .001), and readmission rate at 30 (12.4% vs 11.3%) and 90 days (19.0% vs 17.7%) were greater at SNHs (both P < .001). After matching, none of these differences persisted except length of stay (9 vs 8 days) and cost ($46,977 vs $39,343) (both P < .001). Conclusions: After matching, early outcomes after CABG were comparable at SNHs and non-SNHs. Improved discharge resources could reduce length of stay and curtail cost, improving the value of CABG at SNHs.

Combined effect of metabolites produced by a modified Lactobacillus casei and berry phenolic extract on Campylobacter and microbiome in chicken cecum contents.

Campylobacter is one of the most common foodborne bacterial pathogens causing illness, known as campylobacteriosis, in the United States. More than 70% of the campylobacteriosis cases have direct or indirect relation with poultry/poultry products. Currently, both conventional and organic/pasture poultry farmers are searching for sustainable alternative to antibiotics which can reduce colonization and cross-contamination of poultry products with Campylobacter and promote poultry health and growth. Probiotic and their nutritional supplement, known as prebiotic, have become consumers' preferences as alternatives to antibiotics/chemicals. In this study, we evaluated the combined effect of plant-derived prebiotic and probiotic-derived metabolites in reducing growth of Campylobacter in cecum contents, a simulated chicken gut condition. Cecum contents were collected from chickens pre-inoculated with kanamycin-resistant Campylobacter (CJRMKm), were incubated over 48 h time period, while being supplemented with either berry phenolic extract (BPE), cell free cultural supernatant from an engineered probiotic, Lactobacillus casei, or their combination. It was found that combine treatments were able to reduce both inoculated and naturally colonized Campylobacter more effectively. Microbiome analysis using 16S rRNA sequencing also revealed that combine treatments were capable to alter natural microflora positively within chicken cecum contents. Differences were observed in bacterial abundance at both phylum and genus level but did not show significant alteration in alpha diversity due to this treatment. PRACTICAL APPLICATION: The results of this study provide critical information for understanding the potential of synbiotic as an alternative in sustainable poultry farming. The outcomes of this study will lead future direction of using combination of probiotic-derived metabolites and BPE in poultry farming.

Readmissions After Surgical Aortic Valve Replacement: Influence of Prosthesis Type.

INTRODUCTION: Prosthesis choice during aortic valve replacement (AVR) weighs lifelong anticoagulation with mechanical valves (M-AVR) against structural valve degeneration in bioprosthetic valves (B-AVR). METHODS: The Nationwide Readmissions Database was queried to identify patients who underwent isolated surgical AVR between January 1, 2016 and December 31, 2018, stratifying by prothesis type. Propensity score matching was used to compare risk-adjusted outcomes. Readmission at 1 y was estimated with Kaplan-Meier (KM) analysis. RESULTS: Patients (n = 109,744) who underwent AVR (90,574 B-AVR and 19,170 M-AVR) were included. B-AVR patients were older (median 68 versus 57 y; P < 0.001) and had more comorbidities (mean Elixhauser score: 11.8 versus 10.7; P < 0.001) compared to M-AVR patients. After matching (n = 36,951), there was no difference in age (58 versus 57 y; P = 0.6) and Elixhauser score (11.0 versus 10.8; P = 0.3). B-AVR patients had similar in-hospital mortality (2.3% versus 2.3%; P = 0.9) and cost (mean: $50,958 versus $51,200; P = 0.4) compared with M-AVR patients. However, B-AVR patients had shorter length of stay (8.3 versus 8.7 d; P < 0.001) and fewer readmissions at 30 d (10.3% versus 12.6%; P < 0.001) and 90 d (14.8% versus 17.8%; P < 0.001), and 1 y (P < 0.001, KM analysis). Patients undergoing B-AVR were less likely to be readmitted for bleeding or coagulopathy (5.7% versus 9.9%; P < 0.001) and effusions (9.1% versus 11.9%; P < 0.001). CONCLUSIONS: B-AVR patients had similar early outcomes compared to M-AVR patients, but lower rates of readmission. Bleeding, coagulopathy, and effusions are drivers of excess readmissions in M-AVR patients. Readmission reduction strategies targeting bleeding and improved anticoagulation management are warranted in the first year following AVR.

Racial/ethnic differences persist in treatment choice and outcomes in isolated intervention for coronary artery disease.

OBJECTIVE: Studies have noted racial/ethnic disparities in coronary artery disease intervention strategies. We investigated trends and outcomes of coronary artery disease treatment choice (coronary artery bypass grafting or percutaneous coronary intervention) stratified by race/ethnicity. METHODS: We queried the National Inpatient Sample for patients who underwent isolated coronary artery bypass grafting or percutaneous coronary intervention (2002-2017). Outcomes were stratified by race/ethnicity (White, African American, Hispanic, Asian). Multivariable logistic regression evaluated associations between race/ethnicity and receiving coronary artery bypass grafting versus percutaneous coronary intervention, in-hospital mortality, and costs. RESULTS: Over the 15-year period, 2,426,917 isolated coronary artery bypass grafting surgeries and 7,184,515 percutaneous coronary interventions were performed. Compared with White patients, African American patients were younger (62 [interquartile range, 53-70] vs 66 [interquartile range, 57-75] years), were more likely to have Medicaid insurance (12.2% vs 4.4%), and had more comorbidities (Charlson-Deyo index, 1.9 ± 1.6 vs 1.7 ± 1.6) (all P < .01). After adjustment for patient comorbidities, presence of acute myocardial infarction, insurance status, and geography, African Americans were the least likely of all racial/ethnic groups to undergo coronary artery bypass grafting (odds ratio, 0.76; P < .01), a consistent trend throughout the study. African American patients had higher risk-adjusted mortality after coronary artery bypass grafting (odds ratio, 1.09; P < .01). Race/ethnicity was not associated with increased mortality after percutaneous coronary intervention. African American patients had higher hospitalization costs for coronary artery bypass grafting (+$5816; P < .01) and percutaneous coronary intervention (+$856; P < .01) after controlling for confounders. CONCLUSIONS: In this contemporary national analysis, risk-adjusted frequency of coronary artery bypass grafting versus percutaneous coronary intervention for coronary artery disease differed by race/ethnicity. African American patients had lower odds of undergoing coronary artery bypass grafting and worse outcomes. Reasons for these differences merit further investigation to identify opportunities to reduce potential disparities.

Machine learning for dynamic and early prediction of acute kidney injury after cardiac surgery.

OBJECTIVE: Acute kidney injury after cardiac surgery increases morbidity and mortality. Diagnosis relies on oliguria or increased serum creatinine, which develop 48 to 72 hours after injury. We hypothesized machine learning incorporating preoperative, operative, and intensive care unit data could dynamically predict acute kidney injury before conventional identification. METHODS: Cardiac surgery patients at a tertiary hospital (2008-2019) were identified using electronic medical records in the Medical Information Mart for Intensive Care IV database. Preoperative and intraoperative parameters included demographics, Charlson Comorbidity subcategories, and operative details. Intensive care unit data included hemodynamics, medications, fluid intake/output, and laboratory results. Kidney Disease: Improving Global Outcomes creatinine criteria were used for acute kidney injury diagnosis. An ensemble machine learning model was trained for hourly predictions of future acute kidney injury within 48 hours. Performance was evaluated by area under the receiver operating characteristic curve and balanced accuracy. RESULTS: Within the cohort (n = 4267), there were approximately 7 million data points. Median baseline creatinine was 1.0 g/dL (interquartile range, 0.8-1.2), with 17% (735/4267) of patients having chronic kidney disease. Postoperative stage 1 acute kidney injury occurred in 50% (2129/4267), stage 2 occurred in 8% (324/4267), and stage 3 occurred in 4% (183/4267). For hourly prediction of any acute kidney injury over the next 48 hours, area under the receiver operating characteristic curve was 0.82, and balanced accuracy was 75%. For hourly prediction of stage 2 or greater acute kidney injury over the next 48 hours, area under the receiver operating characteristic curve was 0.95 and balanced accuracy was 86%. The model predicted acute kidney injury before clinical detection in 89% of cases. CONCLUSIONS: Ensemble machine learning models using electronic medical records data can dynamically predict acute kidney injury risk after cardiac surgery. Continuous postoperative risk assessment could facilitate interventions to limit or prevent renal injury.

Development of a Machine Learning Model to Predict Outcomes and Cost After Cardiac Surgery.

BACKGROUND: Machine learning (ML) algorithms may enhance outcomes prediction and help guide clinical decision making. This study aimed to develop and validate a ML model that predicts postoperative outcomes and costs after cardiac surgery. METHODS: The Society of Thoracic Surgeons registry data from 4874 patients who underwent cardiac surgery (56% coronary artery bypass grafting, 42% valve surgery, 19% aortic surgery) at our institution were divided into training (80%) and testing (20%) datasets. The Extreme Gradient Boosting decision-tree ML algorithms were trained to predict three outcomes: operative mortality, major morbidity or mortality, and Medicare outlier high hospitalization cost. Algorithm performance was determined using accuracy, F1 score, and area under the precision-recall curve (AUC-PR). The ML algorithms were validated in index surgery cases with The Society of Thoracic Surgeons risk scores for mortality and major morbidities and with logistic regression and were then applied to nonindex cases. RESULTS: The ML algorithms with 25 input parameters predicted operative mortality (accuracy 95%; F1 0.31; AUC-PR 0.21), major morbidity or mortality (accuracy 71%, F1 0.47; AUC-PR 0.47), and high cost (accuracy 84%; F1 0.62; AUC-PR 0.65). Preoperative creatinine, complete blood count, patient height and weight, ventricular function, and liver dysfunction were important predictors for all outcomes. For patients undergoing nonindex cardiac operations, the ML model achieved an AUC-PR of 0.15 (95% CI, 0.05-0.32) for mortality and 0.59 (95% CI, 0.51-0.68) for major morbidity or mortality. CONCLUSIONS: The extreme gradient boosting ML algorithms can predict mortality, major morbidity, and high cost after cardiac surgery, including operations without established risk models. These ML algorithms may refine risk prediction after cardiac surgery for a wide range of procedures.

Nationwide database analysis of one-year readmission rates after open surgical or thoracic endovascular repair of Stanford Type B aortic dissection.

Objective: We examined readmissions and resource use during the first postoperative year in patients who underwent thoracic endovascular aortic repair or open surgical repair of Stanford type B aortic dissection. Methods: The Nationwide Readmissions Database (2016-2018) was queried for patients with type B aortic dissection who underwent thoracic endovascular aortic repair or open surgical repair. The primary outcome was readmission during the first postoperative year. Secondary outcomes included 30-day and 90-day readmission rates, in-hospital mortality, length of stay, and cost. A Cox proportional hazards model was used to determine risk factors for readmission. Results: During the study period, type B aortic dissection repair was performed in 6456 patients, of whom 3517 (54.5%) underwent thoracic endovascular aortic repair and 2939 (45.5%) underwent open surgical repair. Patients undergoing thoracic endovascular aortic repair were older (63 vs 59 years; P < .001) with fewer comorbidities (Elixhauser score of 11 vs 17; P < .001) than patients undergoing open surgical repair. Thoracic endovascular aortic repair was performed electively more often than open surgical repair (29% vs 20%; P < .001). In-hospital mortality was 9% overall and lower in the thoracic endovascular aortic repair cohort than in the open surgical repair cohort (5% vs 13%; P < .001). However, the 90-day readmission rate was comparable between the thoracic endovascular aortic repair and open surgical repair cohorts (28% vs 27%; P = .7). Freedom from readmission for up to 1 year was also similar between cohorts (P = .6). Independent predictors of 1-year readmission included length of stay more than 10 days (P = .005) and Elixhauser comorbidity risk index greater than 4 (P = .033). Conclusions: Approximately one-third of all patients with type B aortic dissection were readmitted within 90 days after aortic intervention. Surprisingly, readmission during the first postoperative year was similar in the open surgical repair and thoracic endovascular aortic repair cohorts, despite marked differences in preoperative patient characteristics and interventions.

Readmission After Bioprosthetic vs Mechanical Mitral Valve Replacement in the United States.

BACKGROUND: Choosing between a bioprosthetic and a mechanical mitral valve is an important decision for both patients and surgeons. We compared patient outcomes and readmission rates after bioprosthetic mitral valve replacement (Bio-MVR) vs mechanical mitral valve replacement (Mech-MVR). METHODS: The Nationwide Readmissions Database was queried to identify 31 474 patients who underwent isolated MVR (22 998 Bio-MVR, 8476 Mech-MVR) between January 1, 2016, and December 31, 2018. Propensity score matching by age, sex, elective status, and comorbidities was used to compare outcomes between matched cohorts by prosthesis type. Freedom from readmission within the first calendar year was estimated by Kaplan-Meier analysis and compared between matched cohorts. RESULTS: Bio-MVR patients were older (median age, 69 vs 57 years; P < .001) and had more comorbidities (median Elixhauser score, 14 vs 11; P < .001) compared with Mech-MVR patients. After propensity score matching (n = 15 549), Bio-MVR patients had similar operative mortality (3.5% vs 3.4%; P = .97) and costs ($50 958 vs $49 782; P = .16) but shorter lengths of stay (8 vs 9 days; P < .001) and fewer 30-day (16.0% vs 18.1%; P = .04) and 90-day (23.8% vs 26.8%; P = .01) readmissions compared with Mech-MVR patients. The difference in readmissions persisted at 1 year (P = .045). Readmission for bleeding or coagulopathy complications was less common with Bio-MVR (5.7% vs 10.1%; P < .001). CONCLUSIONS: Readmission was more common after Mech-MVR than after Bio-MVR. Identifying and closely observing patients at high risk for bleeding complications may bridge the readmissions gap between Bio-MVR and Mech-MVR.

Machine Learning to Predict Outcomes and Cost by Phase of Care After Coronary Artery Bypass Grafting.

BACKGROUND: Machine learning may enhance prediction of outcomes after coronary artery bypass grafting (CABG). We sought to develop and validate a dynamic machine learning model to predict CABG outcomes at clinically relevant pre- and postoperative time points. METHODS: The Society of Thoracic Surgeons (STS) registry data elements from 2086 isolated CABG patients were divided into training and testing datasets and input into Extreme Gradient Boosting decision-tree machine learning algorithms. Two prediction models were developed based on data from preoperative (80 parameters) and postoperative (125 parameters) phases of care. Outcomes included operative mortality, major morbidity or mortality, high cost, and 30-day readmission. Machine learning and STS model performance were assessed using accuracy and the area under the precision-recall curve (AUC-PR). RESULTS: Preoperative machine learning models predicted mortality (accuracy, 98%; AUC-PR = 0.16; F1 = 0.24), major morbidity or mortality (accuracy, 75%; AUC-PR = 0.33; F1 = 0.42), high cost (accuracy, 83%; AUC-PR = 0.51; F1 = 0.52), and 30-day readmission (accuracy, 70%; AUC-PR = 0.47; F1 = 0.49) with high accuracy. Preoperative machine learning models performed similarly to the STS for prediction of mortality (STS AUC-PR = 0.11; P = .409) and outperformed STS for prediction of mortality or major morbidity (STS AUC-PR = 0.28; P < .001). Addition of intraoperative parameters further improved machine learning model performance for major morbidity or mortality (AUC-PR = 0.39; P < .01) and high cost (AUC-PR = 0.64; P < .01), with cross-clamp and bypass times emerging as important additive predictive parameters. CONCLUSIONS: Machine learning can predict mortality, major morbidity, high cost, and readmission after isolated CABG. Prediction based on the phase of care allows for dynamic risk assessment through the hospital course, which may benefit quality assessment and clinical decision-making.

Development of a Risk Score to Predict 90-Day Readmission After Coronary Artery Bypass Graft.

BACKGROUND: Readmission after coronary artery bypass grafting (CABG) is used for quality metrics and may negatively affect hospital reimbursement. Our objective was to develop a risk score system from a national cohort that can predict 90-day readmission risk for CABG patients. METHODS: Using the National Readmission Database between 2013 and 2014, we identified 104,930 patients discharged after CABG, for a total of 234,483 patients after weighted analysis. Using structured random sampling, patients were divided into a training set (60%) and test data set (40%). In the training data set, we used multivariable analysis to identify risk factors. A point system risk score was developed based on the odds ratios. Variables with odds ratio less than 1.3 were excluded from the final model to reduce noise. Performance was assessed in the test data set using receiver operator characteristics and accuracy. RESULTS: In the United States, overall 90-day readmission rate after CABG was 19% (n = 44,559 of 234,483). Nine demographic and clinical variables were identified as important in the training data set. The final risk score ranged from 0 to 52; the 2 largest risks were associated with length of stay greater than 10 days (score = +10) and Medicaid insurance (score = +7). The final model's C-statistic was 0.67. Using an optimal cutoff of 18 points, the accuracy of the risk score was 77%. CONCLUSIONS: Ninety-day readmission after CABG surgery is frequent. A readmission risk score higher than 18 points predicts readmission in 77% of patients. Based on 9 demographic and clinical factors, this risk score can be used to target high-risk patients for additional postdischarge resources to reduce readmission.

Mid-Term Efficacy of Subxiphoid Versus Transpleural Pericardial Window for Pericardial Effusion.

BACKGROUND: The optimal surgical technique for drainage of pericardial effusions is frequently debated. Transpleural drainage via thoracotomy or thoracoscopy is hypothesized to provide more durable freedom from recurrent pericardial effusion than a subxiphoid pericardial window. We sought to compare operative outcomes and mid-term freedom from recurrent effusion between both approaches in patients with nontraumatic pericardial effusions. METHODS: All patients at our institution who underwent a pericardial window from 2001 to 2018 were identified. After excluding those who underwent recent cardiothoracic surgery or trauma, patients (n = 46) were stratified by surgical approach and presence of malignancy. Primary outcome was freedom from recurrent moderate or greater pericardial effusion. Secondary outcomes included operative mortality and morbidity and mid-term survival. Follow-up was determined by medical record review, with a follow-up of 67 patient-years. Fisher's exact test and Wilcoxon rank-sum test were used to compare groups. Mid-term survival and freedom from effusion recurrence were determined using Kaplan-Meier method. RESULTS: Subxiphoid windows (n = 31; 67%) were more frequently performed than transpleural windows (n = 15; 33%) and baseline characteristics were similar. Effusion etiologies included malignancy (n = 22; 48%), idiopathic (n = 12; 26%), uremia (n = 8; 17%), and collagen vascular disease (n = 4; 9%). Perioperative outcomes were comparable between the two surgical approaches, except for longer drain duration (7 versus 4 d, P = 0.029) in the subxiphoid group. Operative mortality was 19.6% overall and 36.4% in patients with malignancy. Mid-term survival and freedom from moderate or greater pericardial effusion recurrence was 37% (95% confidence interval [CI]: 19%-54%) and 69% (95% CI: 52%-86%) at 5 y, respectively. There was no difference in mid-term survival (P = 0.90) or freedom from pericardial effusion recurrence (P = 0.70) between surgical approaches. Although malignant etiology had worse late survival (P < 0.01), freedom from effusion recurrence was similar to nonmalignant etiology (P = 0.70). CONCLUSIONS: Pericardial window provides effective mid-term relief of pericardial effusion. Subxiphoid and transpleural windows are equivalent in mid-term efficacy and both surgical approaches can be considered. Patients with malignancy have acceptable operative mortality with low incidence of recurrent effusion, supporting palliative indications.

Incidence, Cost, and Risk Factors for Readmission After Coronary Artery Bypass Grafting.

BACKGROUND: Readmissions adversely affect hospital reimbursement and quality measures. We aimed to evaluate the incidence, cost, and risk factors for readmission following coronary artery bypass grafting (CABG). METHODS: We queried the National Readmissions Database and isolated patients who underwent CABG from 2013 to 2014. We determined the top reasons for readmission and compared demographics, comorbidities, in-hospital outcomes, and costs between readmitted and nonreadmitted patients. Generalized linear regression was performed to identify independent predictors for readmission. RESULTS: We identified 288,059 patients who underwent isolated CABG in the United States between 2013 and 2014. A total of 12.2% were readmitted within 30 days of discharge. Postoperative infection, heart failure, and arrhythmia were the most common reasons for readmission. The median time to readmit was 11 days, with a length of stay (LOS) of 6 days and a cost of $13,499 ± $201. Independent preoperative predictors for readmission were Medicaid status (odds ratio [OR], 1.33), female sex (OR, 1.32), chronic renal failure (OR, 1.26), greater than 4 Elixhauser comorbidities (OR, 1.20), chronic pulmonary disease (OR, 1.15), and nonelective operation (OR, 1.10) (all p < 0.05). In-hospital predictors included LOS greater than 10 days (OR, 1.52), acute kidney injury (OR, 1.30), atrial fibrillation (OR, 1.20), pneumonia (OR, 1.13), and discharge to skilled nursing facility (OR, 1.43) (all p < 0.05). CONCLUSIONS: Thirty-day readmissions after CABG are frequent and related to preoperative comorbidities and complex postoperative course. Medicaid status, prolonged LOS, and disposition to a skilled nursing facility are strong predictors for 30-day readmission following CABG. Readmission reduction efforts should consider improvements for patients in these cohorts.

Confusion Instead of Clarity: Publicly Reported Cardiac Surgery Ratings for Coronary Artery Bypass Grafting and Aortic Valve Replacement.

BACKGROUND: Public reporting of cardiac surgery ratings has been advocated to inform patient selection of hospitals. Although Society of Thoracic Surgeons (STS) ratings are based on audited risk-adjusted patient outcomes, other rating systems rely on administrative databases. In this study, we evaluate correlation among 4 widely used hospital rating systems for coronary artery bypass grafting (CABG) and aortic valve replacement (AVR). STUDY DESIGN: We identified an initial cohort of 602 hospitals from US News & World Report's (USN) listing of the 2016-2017 "Best Hospitals for Cardiology & Heart Surgery." From this cohort, current publicly available CABG and AVR ratings were collected from the STS, USN, Centers for Medicare & Medicaid Services, and Healthgrades. All 4 rating systems rated hospitals as high, average, or below average performers for each procedure. We then determined the match rate between rating systems for individual hospitals and assessed interrater reliability with Cohen's κ. RESULTS: Rating systems had different distributions of high and low performing ratings assigned. USN rated hospitals as high performing for both CABG and AVR more frequently compared with STS, Healthgrades, and Centers for Medicare & Medicaid Services. For CABG, the match rate between systems varied from 50% to 85%, with the best match between STS and Centers for Medicare & Medicaid Services. Similarly for AVR, the match rate varied from 50% to 73%, with the best match between STS and Healthgrades. Interrater reliability was poor among the 4 rating systems (κ < 0.2) and consistent with no agreement for CABG and AVR ratings. CONCLUSIONS: Publicly reported cardiac surgery ratings have significant discrepancy and poor correlation. This might confuse instead of clarify public perception of hospital quality for cardiac surgery.

Survival trends after inferior vena cava and aortic injuries in the United States.

OBJECTIVE: Recent studies have demonstrated an increase in trauma mortality relative to mortality from cancer and heart diseases in the United States. Major vascular injuries such as to the inferior vena cava (IVC) and aortic injuries remain responsible for a significant proportion of early trauma deaths in modern trauma care. The purpose of this study was to explore patterns in epidemiology and mortality after IVC and aortic injuries in the United States. METHODS: A 13-year analysis of the National Trauma Databank (2002-2014) was performed to extract all patients who sustained IVC, abdominal aortic, or thoracic aortic injuries. Demographics, clinical data, and outcomes were extracted. Patients were analyzed according to injury mechanism. RESULTS: A total of 25,428 patients were included in this analysis. Overall, the mean age was 39.8 ± 19.1 years, 70.3% were male, and 14.1% sustained a penetrating trauma. Although the incidence of all three injuries remained constant throughout the study period, for blunt trauma, mortality decreased over the study period (from 48.8% in 2002 to 28.7% in 2014; P < .001), in particular for thoracic aortic injuries (from 46.1% in 2002 to 23.7% in 2014; P < .001) and abdominal aortic injuries (from 58.3% in 2002 to 26.2% in 2014; P < .001). This decrease in mortality after blunt trauma was accompanied by an increase in endovascular procedures over the study period (from 1.0% in 2002 to 30.4% in 2014; P < .001), in particular for blunt thoracic aortic injuries (from 0.7% in 2002 to 41.4% in 2014; P < .001). When penetrating trauma patients were analyzed, overall there was an increase in mortality (from 43.8% in 2002 to 50.6% in 2014; P < .001), in particular after abdominal aortic injury (from 30.4% in 2002 to 66.0% in 2014; P < .001). Similar trends were observed for IVC injuries. No increase in endovascular use in penetrating trauma was identified (from 0.1% in 2002 to 3.4% in 2014; P < .001). CONCLUSIONS: The present study demonstrates an overall decrease in mortality after blunt aortic injuries in the United States. This decrease was accompanied by an increase in the use of endovascular procedures. After penetrating trauma, however, despite contemporary advances in trauma care, mortality has increased over the study period, in particular after abdominal aortic injury. No increase in endovascular use in penetrating trauma was demonstrated.