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.

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.

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.

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.

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.

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.

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.

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.

Intraoperative hypotensive resuscitation for patients undergoing laparotomy or thoracotomy for trauma: Early termination of a randomized prospective clinical trial.

BACKGROUND: Hemorrhagic shock is responsible for one third of trauma related deaths. We hypothesized that intraoperative hypotensive resuscitation would improve survival for patients undergoing operative control of hemorrhage following penetrating trauma. METHODS: Between July 1, 2007, and March 28, 2013, penetrating trauma patients aged 14 years to 45 years with a systolic blood pressure of 90 mm Hg or lower requiring laparotomy or thoracotomy for control of hemorrhage were randomized 1:1 based on a target minimum mean arterial pressure (MAP) of 50 mm Hg (experimental arm, LMAP) or 65 mm Hg (control arm, HMAP). Patients were followed up 30 days postoperatively. The primary outcome of mortality; secondary outcomes including stroke, myocardial infarction, renal failure, coagulopathy, and infection; and other clinical data were analyzed between study arms using univariate and Kaplan-Meier analyses. RESULTS: The trial enrolled 168 patients (86 LMAP, 82 HMAP patients) before early termination, in part because of clinical equipoise and futility. Injuries resulted from gunshot wounds (76%) and stab wounds (24%); 90% of the patients were male, and the median age was 31 years. Baseline vitals, laboratory results, and injury severity were similar between groups. Intraoperative MAP was 65.5 ± 11.6 mm Hg in the LMAP group and 69.1 ± 13.8 mm Hg in the HMAP group (p = 0.07). No significant survival advantage existed for the LMAP group at 30 days (p = 0.48) or 24 hours (p = 0.27). Secondary outcomes were similar for the LMAP and HMAP groups: acute myocardial infarction (1% vs. 2%), stroke (0% vs. 3%), any renal failure (15% vs. 12%), coagulopathy (28% vs. 29%), and infection (59% vs. 58%) (p > 0.05 for all). Acute renal injury occurred less often in the LMAP than in HMAP group (13% vs. 30%, p = 0.01). CONCLUSION: This study was unable to demonstrate that hypotensive resuscitation at a target MAP of 50 mm Hg could significantly improve 30-day mortality. Further study is necessary to fully realize the benefits of hypotensive resuscitation. LEVEL OF EVIDENCE: Therapeutic study, level II.

Intravascular ultrasound enhanced aortic sizing for endovascular treatment of blunt aortic injury.

BACKGROUND: Blunt aortic injury (BAI) in young patients with a compliant aorta and evolving hyperdynamic physiology may result in significant variation in aortic diameter during the cardiac cycle. Intravascular ultrasound (IVUS) may be useful to detect real-time variations in aortic diameters for more reliable sizing in patients undergoing thoracic endovascular aortic repair (TEVAR) of BAI. METHODS: This is a single-institution retrospective study of patients who underwent TEVAR for BAI in a Level 1 trauma center from January 2004 to January 2014. Patients underwent either trauma survey computed tomography (CT) alone (CT group) or IVUS and CT (IVUS group). We compared predeployment aortic measurements, implanted device size, landing zones, and repair outcomes between the groups. RESULTS: Forty-one patients underwent TEVAR for BAI: 28 were in the CT group and 13 in the IVUS group. Left subclavian artery (LSCA) coverage was performed in 50% (CT group) and 38% (IVUS group) of patients. CT-based median aortic diameter was similar in both groups (20.5 mm in the CT group vs. 19.0 mm in the IVUS group, p = 0.374). The median proximal diameter of the proximal device implanted was 26 mm in the CT group and 24 mm in the IVUS group (p = 0.329), which resulted in oversizing of 25.7% and 13.7% (p < 0.001), respectively. The implanted device was changed in 6 of 13 patients and in 4 of 5 patients in which the LSCA was covered because of IVUS measured-diameters. Graft extension proximal to the LSCA resulted in greater differences between the CT and IVUS measurements of the proximal aorta than if the graft was isolated to the descending aorta (18.8% vs. 5.57%, p = 0.005). Technical success of repair for both groups was 100%; no secondary interventions were required in either group. CONCLUSION: In combination with CT, IVUS provides important separate sizing information at the point of implantation for more accurate device selection, eliminating need for a repeat CT. LEVEL OF EVIDENCE: Therapeutic study, level IV.

Endovascular management of traumatic peripheral arterial injuries.

BACKGROUND: Traumatic injuries to peripheral arterial vessels are increasingly managed with endovascular techniques. Early small series have suggested that endovascular therapy is feasible and decreases operative blood loss, but these data are limited. The purpose of this study was to evaluate the feasibility and outcomes of endovascular management of nonaortic arterial trauma. MATERIALS AND METHODS: We reviewed records of traumatic nonaortic arterial injuries presenting at an urban level 1 trauma center from December 2009-July 2013. Patients undergoing treatment in interventional radiology and patients whose injuries occurred >72 h before presentation were excluded. Demographics, indicators of injury severity, operative blood loss, transfusion requirements, and clinical outcome were compared between patients undergoing endovascular and open management using appropriate inferential statistics. RESULTS: During the study period, 17 patients underwent endovascular interventions and 20 had open surgery. There were 19 upper extremity and/or thoracic outlet arterial injuries, 15 lower extremity injuries and 11 pelvic injuries. Endovascular cases were completed using a vascular imaging C-arm in a standard operating room. Estimated blood loss during the primary procedure was significantly lower with endovascular management (150 versus 825 cc, P < 0.001). No differences were observed between cohorts in age, injury severity score, intensive care unit length of stay, arterial pH, transfusion requirements, inpatient complication rate, or mortality. CONCLUSIONS: Our experience with endovascular management demonstrates its feasibility with commonly available tools. Operative blood loss may be significantly decreased using endovascular techniques. Further study is needed to refine patient selection criteria and to define long-term outcomes.

A case of biventricular failure after pericardial window for large pericardial effusion.

Pericardial tamponade resulting in hemodynamic compromise requiring either pericardiocentesis [Vandyke 1983] or subxiphoid pericardial window has been reported in literature [Armstrong 1984]. There are no large case series, only scattered case reports. Cardiac tamponade is known to affect the diastolic function of the heart but rare reports have documented systolic impairment of the left and right ventricle in the setting of tamponade [Vandyke 1983; Armstrong 1984]. We report a case of a transient biventricular systolic dysfunction in a patient with early cardiac tamponade after surgical drainage of pericardia1 effusion.