Evolving trends in aortic valve replacement: A statewide experience

BackgroundTranscatheter aortic valve replacement (TAVR) is an alternative to surgical aortic valve replacement (SAVR) for the treatment of aortic stenosis in patients at intermediate, high, and extreme risk for mortality from SAVR. We examined recent trends in aortic valve replacement (AVR) in Michigan.MethodsThe Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative (MSTCVS‐QC) database was used to determine the number of SAVR and TAVR cases performed from January 2012 through June 2017. Patients were divided into low, intermediate, high, and extreme risk groups based on STS predicted risk of mortality (PROM). TAVR patients in the MSTCVS‐QC database were also matched with those in the Transcatheter Valve Therapy Registry to determine their Heart Team‐designated risk category.ResultsDuring the study period 9517 SAVR and 4470 TAVR cases were performed. Total annual AVR volume increased by 40.0% (from 2086 to 2920), with a 13.3% decrease in number of SAVR cases (from 1892 to 1640) and a 560% increase in number of TAVR cases (from 194 to 1280). Greater than 90% of SAVR patients had PROM ≤8%. While >70% of TAVR patients had PROM ≤ 8%, they were mostly designated as high or extreme risk by a Heart Team.ConclusionsDuring the study period, SAVR volume gradually declined and TAVR volume dramatically increased. This was mostly due to a new group of patients with lower STS PROM who were designated as higher risk by a Heart Team due to characteristics not completely captured by the STS PROM score.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145246/1/jocs13740_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145246/2/jocs13740.pd

Determinants of hospital variability in perioperative red blood cell transfusions during coronary artery bypass graft surgery

OBJECTIVE: To identify to what extent distinguishing patient and procedural characteristics can explain center-level transfusion variation during coronary artery bypass grafting surgery. METHODS: Observational cohort study using the Perfusion Measures and Outcomes Registry from 43 adult cardiac surgical programs from July 1, 2011, to July 1, 2017. Iterative multilevel logistic regression models were constructed using patient demographic characteristics, preoperative risk factors, and intraoperative conservation strategies to progressively explain center-level transfusion variation. RESULTS: Of the 22,272 adult patients undergoing isolated coronary artery bypass surgery using cardiopulmonary bypass, 7241 (32.5%) received at least 1 U allogeneic red blood cells (range, 10.9%-59.9%). When compared with patients who were not transfused, patients who received at least 1 U red blood cells were older (68 vs 64 years; P \u3c .001), were women (41.5% vs 15.9%; P \u3c .001), and had a lower body surface area (1.93 m(2) vs 2.07 m(2); P \u3c .001), respectively. Among the models explaining center-level transfusion variability, the intraclass correlation coefficients were 0.07 for model 1 (random intercepts), 0.12 for model 2 (patient factors), 0.14 for model 3 (intraoperative factors), and 0.11 for model 4 (combined). The coefficient of variation for center-level transfusion rates were 0.31, 0.29, 0.40, and 0.30 for models 1 through 4, respectively. The majority of center-level variation could not be explained through models containing both patient and intraoperative factors. CONCLUSIONS: The results suggest that variation in center-level red blood cells transfusion cannot be explained by patient and procedural factors alone. Investigating organizational culture and programmatic infrastructure may be necessary to better understand variation in transfusion practices

Red Blood Cell Transfusions Impact Pneumonia Rates After Coronary Artery Bypass Grafting

BACKGROUND: Pneumonia, a known complication of coronary artery bypass grafting (CABG), significantly increases a patient\u27s risk of morbidity and mortality. Although not well characterized, red blood cell (RBC) transfusions may increase a patient\u27s risk of pneumonia. We describe the relationship between RBC transfusion and postoperative pneumonia after CABG. METHODS: A total of 16,182 consecutive patients underwent isolated CABG between 2011 and 2013 at 1 of 33 hospitals in the state of Michigan. We used multivariable logistic regression to estimate the relative odds of pneumonia associated with the use or number of RBC units (0, 1, 2, 3, 4, 5, and ≥ 6). We adjusted for predicted risk of mortality, preoperative hematocrit values, history of pneumonia, cardiopulmonary bypass duration, and medical center. We confirmed the strength and direction of these relationships among selected clinical subgroups in a secondary analysis. RESULTS: Five hundred seventy-six (3.6%) patients had pneumonia and 6,451 (39.9%) received RBC transfusions. There was a significant association between any RBC transfusion and pneumonia (adjusted odds ratio [ORadj], 3.4; p \u3c 0.001). There was a dose response between number of units and odds of pneumonia, with a ptrend less than 0.001. Patients receiving only 2 units of RBCs had a 2-fold (ORadj, 2.1; p \u3c 0.001) increased odds of developing pneumonia. These findings were consistent across clinical subgroups. CONCLUSIONS: We found a significant volume-dependent association between an increasing number of RBCs and the odds of pneumonia, which persisted after risk adjustment. Clinical teams should explore opportunities for preventing a patient\u27s risk of RBC transfusions, including reducing hemodilution or adopting a lower transfusion threshold in a stable patient

Determinants of Hospital Variation in Cardiac Rehabilitation Enrollment During Coronary Artery Disease Episodes of Care

BACKGROUND: Cardiac rehabilitation (CR) is associated with improved outcomes for patients with coronary artery disease (CAD). However, CR enrollment remains low and there is a dearth of real-world data on hospital-level variation in CR enrollment. We sought to explore determinants of hospital variability in CR enrollment during CAD episodes of care: medical management of acute myocardial infarction (AMI-MM), percutaneous coronary intervention (PCI), and coronary artery bypass grafting (CABG). METHODS: A cohort of 71 703 CAD episodes of care were identified from 33 hospitals in the Michigan Value Collaborative statewide multipayer registry (2015 to 2018). CR enrollment was defined using professional and facility claims and compared across treatment strategies: AMI-MM (n=18 678), PCI (n=41 986), and CABG (n=11 039). Hierarchical logistic regression was used to estimate effects of predictors and hospital risk-adjusted rates of CR enrollment. RESULTS: Overall, 20 613 (28.8%) patients enrolled in CR, with significant differences by treatment strategy: AMI-MM=13.4%, PCI=29.0%, CABG=53.8% (P\u3c0.001). There were significant differences in CR enrollment across age groups, comorbidity status, and payer status. At the hospital-level, there was over 5-fold variation in hospital risk-adjusted CR enrollment rates (9.8%-51.6%). Hospital-level CR enrollment rates were highly correlated across treatment strategy, with the strongest correlation between AMI-MM versus PCI (R(2)=0.72), followed by PCI versus CABG (R(2)=0.51) and AMI-MM versus CABG (R(2)=0.46, all P\u3c0.001). CONCLUSIONS: Substantial variation exists in CR enrollment during CAD episodes of care across hospitals. However, within-hospital CR enrollment rates were significantly correlated across all treatment strategies. These findings suggest that CR enrollment during CAD episodes of care is the product of hospital-specific rather than treatment-specific practice patterns

A Preoperative Risk Model for Postoperative Pneumonia After Coronary Artery Bypass Grafting

BACKGROUND: Postoperative pneumonia is the most prevalent of all hospital-acquired infections after isolated coronary artery bypass graft surgery (CABG). Accurate prediction of a patient\u27s risk of this morbid complication is hindered by its low relative incidence. In an effort to support clinical decision making and quality improvement, we developed a preoperative prediction model for postoperative pneumonia after CABG. METHODS: We undertook an observational study of 16,084 patients undergoing CABG between the third quarter of 2011 and the second quarter of 2014 across 33 institutions participating in the Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative. Variables related to patient demographics, medical history, admission status, comorbid disease, cardiac anatomy, and the institution performing the procedure were investigated. Logistic regression through forward stepwise selection (p \u3c 0.05 threshold) was utilized to develop a risk prediction model for estimating the occurrence of pneumonia. Traditional methods were used to assess the model\u27s performance. RESULTS: Postoperative pneumonia occurred in 3.30% of patients. Multivariable analysis identified 17 preoperative factors, including demographics, laboratory values, comorbid disease, pulmonary and cardiac function, and operative status. The final model significantly predicted the occurrence of pneumonia, and performed well (C-statistic: 0.74). These findings were confirmed through sensitivity analyses by center and clinically important subgroups. CONCLUSIONS: We identified 17 readily obtainable preoperative variables associated with postoperative pneumonia. This model may be used to provide individualized risk estimation and to identify opportunities to reduce a patient\u27s preoperative risk of pneumonia through prehabilitation

Impact of institutional culture on rates of transfusions during cardiovascular procedures: The Michigan experience

BACKGROUND: Red blood cell (RBC) transfusions have been associated with morbidity and mortality in both coronary artery bypass grafting (CABG) and percutaneous coronary interventions (PCI). As a mechanism for identifying determinants of RBC practice, we quantified the relationship between a center\u27s PCI and CABG transfusion rate. METHODS: We identified all patients undergoing CABG (n = 16,568) or PCI (n = 94,634) at each of 33 centers from 2010 through 2012 in the state of Michigan and compared perioperative RBC transfusion rates for CABG and PCI at each center. Crude and adjusted transfusion rates were modeled separately. We adjusted for common preprocedural risk factors (12 for CABG and 23 for PCI) and reported Pearson correlation coefficients based on the crude and risk-adjusted rates. RESULTS: As expected, RBC transfusion was more common after CABG (mean 46.5%) than PCI (mean 3.3%), with wide variation across centers for both (CABG min:max 26.5:71.3, PCI min:max 1.6:6.0). However, RBC transfusion rates were significantly correlated between CABG and PCI in both crude, 0.48 (P = .005), and adjusted, 0.53 (P = .001), analyses. These findings were consistent when restricting to nonemergent cases (radj = 0.44, P = .001). CONCLUSIONS: Red blood cell transfusion rates were significantly correlated between the CABG and PCI at individual hospitals in Michigan, independent of patient case mix. Future work should explore institutional practice patterns, philosophies, and guidelines for RBC transfusions

Quality Improvement: Arterial Grafting Redux, 2010:2019

BACKGROUND: The evidence base favoring utilization of multiple arterial conduits in coronary artery bypass grafting has strengthened in recent years. Nevertheless, utilization of arterial conduits in the US lags behind that of many European peers. We describe a statewide collaborative based approach to improving utilization. METHODS: Four metrics of arterial revascularization were devised. These were displayed and discussed at quarterly statewide quality collaborative meetings from January 2016 onwards, integrated with an educational program regarding attendant benefits. We undertook retrospective review of isolated coronary artery bypass grafting statewide from 2012-2019 to assess impact. RESULTS: A total of 38,523 cases met inclusion/exclusion criteria. Statewide incidence of multiple arterial grafting increased from 7.4% at baseline to 21.7% in 2019 (P < .001), implementation across hospitals varied widely, ranging from 67.6% to 0.0%. Utilization of total arterial revascularization increased 1.9% to 4.4% (P < .001) between time frames. Utilization of both radial artery and bilateral internal thoracic artery conduit increased significantly from 5.3% to 13.2% (P < .001) and 2.1% to 8.5% (P < .001), respectively; radial artery utilization was significantly higher than bilateral internal thoracic artery for each year (P < .001 for all comparisons). CONCLUSIONS: Our statewide quality improvement initiative improved rates of utilization of multiple arterial grafting by all metrics. Barriers to current utilization were identified to guide future quality improvement efforts. This reproducible approach is readily transferable to improve quality of care in other domains and geographical areas

Prediction of Transfusions After Isolated Coronary Artery Bypass Grafting Surgical Procedures

BACKGROUND: Although blood transfusions are common and have been associated with adverse sequelae after cardiac surgical procedures, few contemporaneous models exist to support clinical decision making. This study developed a preoperative clinical decision support tool to predict perioperative red blood cell transfusions in the setting of isolated coronary artery bypass grafting. METHODS: We performed a multicenter, observational study of 20,377 patients undergoing isolated coronary artery bypass grafting among patients at 39 hospitals participating in the Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative\u27s PERFusion measures and outcomes (PERForm) registry between 2011 and 2015. Candidates\u27 preoperative risk factors were identified based on previous work and clinical input. The study population was randomly divided into a 70% development sample and a 30% validation sample. A generalized linear mixed-effect model was developed to predict perioperative red blood cell transfusion. The model\u27s performance was assessed for calibration and discrimination. Sensitivity analysis was performed to assess the robustness of the model in different clinical subgroups. RESULTS: Transfusions occurred in 36.8% of patients. The final regression model included 16 preoperative variables. The correlation between the observed and expected transfusions was 1.0. The risk prediction model discriminated well (receiver operator characteristic [ROC] CONCLUSIONS: Our risk prediction model uses 16 readily obtainable preoperative variables. This model, which provides a patient-specific estimate of the need for transfusion, offers clinicians a guide for decision making and evaluating the effectiveness of blood management strategies

Prediction of Transfusions After Isolated Coronary Artery Bypass Grafting Surgical Procedures

BACKGROUND: Although blood transfusions are common and have been associated with adverse sequelae after cardiac surgical procedures, few contemporaneous models exist to support clinical decision making. This study developed a preoperative clinical decision support tool to predict perioperative red blood cell transfusions in the setting of isolated coronary artery bypass grafting. METHODS: We performed a multicenter, observational study of 20,377 patients undergoing isolated coronary artery bypass grafting among patients at 39 hospitals participating in the Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative\u27s PERFusion measures and outcomes (PERForm) registry between 2011 and 2015. Candidates\u27 preoperative risk factors were identified based on previous work and clinical input. The study population was randomly divided into a 70% development sample and a 30% validation sample. A generalized linear mixed-effect model was developed to predict perioperative red blood cell transfusion. The model\u27s performance was assessed for calibration and discrimination. Sensitivity analysis was performed to assess the robustness of the model in different clinical subgroups. RESULTS: Transfusions occurred in 36.8% of patients. The final regression model included 16 preoperative variables. The correlation between the observed and expected transfusions was 1.0. The risk prediction model discriminated well (receiver operator characteristic [ROC] CONCLUSIONS: Our risk prediction model uses 16 readily obtainable preoperative variables. This model, which provides a patient-specific estimate of the need for transfusion, offers clinicians a guide for decision making and evaluating the effectiveness of blood management strategies