Comparative study of same sitting hybrid coronary artery revascularization versus off-pump coronary artery bypass in multivessel coronary artery disease.

OBJECTIVE: We compared the outcomes of same sitting robotic-assisted hybrid coronary artery revascularization (HCR) with off-pump coronary artery bypass grafting (OPCABG) in similar patients with multivessel coronary artery disease. BACKGROUND: HCR is a novel procedure in selected patients with multivessel coronary artery disease (CAD). Although there are some data on staged HCR, the data on same sitting HCR are limited. METHODS: We conducted a prospective study comparing same sitting robotic-assisted HCR patients (n = 25) to a group of consecutive low to moderate risk OPCABG patients (n = 27) during the study period. HCR patients underwent robotic internal mammary artery takedown followed by OPCABG via minithoracotomy. After confirming graft patency, immediate percutaneous coronary intervention on the nonbypass arteries was performed. Comparative analyses were performed on in-hospital and 30 day outcomes. RESULTS: The baseline characteristics were similar for both groups including the severity of CAD (Syntax score 33.5+/-8.2 vs. 34.9+/-8.2, P = 0.556). Overall MACE was similar between both groups; however, the HCR group showed improved hospital outcomes with lower need for postoperative transfusions (12% vs. 67%, P < 0.001), and shorter length of hospital stay (5.1+/-2.8 vs. 8.2+/-5.4 days, P < 0.01). Despite lower postoperative costs, the HCR group had higher overall hospital costs due to higher procedural costs ($33,984 +/-$4,806 vs. $27,816+/-$11,172, P < 0.0001). Propensity model analysis showed similar findings. The HCR group showed improved quality of life measures with shorter time to return to work (5.3+/-3.0 vs. 8.2+/- 4.6 weeks, P = 0.01). CONCLUSIONS: Same sitting HCR appears to be feasible and may offer superior outcomes to standard OPCABG, further studies are warranted.

Cardiac troponin release following hybrid coronary revascularization versus off-pump coronary artery bypass surgery.

OBJECTIVES: Cardiac ischaemic marker release is associated with adverse clinical outcomes after cardiac surgery. We sought to compare the release of cardiac troponin I (cTnI) after hybrid coronary revascularization (HCR) with off-pump coronary artery bypass surgery (OPCAB). METHODS: Using data from a prospective single-centre registry, we compared cTnI measured at postoperative day 1 following one-stage HCR and OPCAB among patients with normal baseline cTnI. Multivariable linear regression analysis was used to adjust for variables that may have influenced cardiac marker release other than the used revascularization strategy. RESULTS: Sixty-five consecutive patients underwent elective HCR (n = 33) or OPCAB (n = 32). Overall, no differences were seen in comorbidities, CABG risk scores and the lesion-specific SYNTAX score. Procedural complications were lower (15.2 vs 34.4%, P = 0.072), but 30-day and 1-year clinical outcomes (death, myocardial infarction, and repeat revascularization) were similar between the two groups (3.0 vs 3.1% and 9.1 vs 6.2%, respectively). Post-procedural cTnI release measured at 24 h after surgery was significantly lower following HCR compared with OPCAB [ratio of upper reference level URL: median: 3.5, interquartile range (IQR): 0.8-9.1 vs 12.8, IQR: 6.9-21.8, P = 0.001]. After adjusting for potential confounders, HCR was associated, on average, with cTnI less than half (46%) compared with CABG (P <0.0001). CONCLUSIONS: HCR is associated with lower postoperative cTn release, compared with OPCAB. Further research into the clinical implications of this finding is warranted.

A prediction model for COPD readmissions: catching up, catching our breath, and improving a national problem.

Frequent COPD exacerbations have a large impact on morbidity, mortality and health-care expenditures. By 2020, the World Health Organization expects COPD and COPD exacerbations to be the third leading cause of death world-wide. Furthermore, In 2005 it was estimated that COPD exacerbations cost the U.S. health-care system 38 billion dollars. Studies attempting to determine factors related to COPD readmissions are still very limited. Moreover, few have used a organized machine-learning, sensitivity analysis approach, such as a Random Forest (RF) statistical model, to analyze this problem. This study utilized the RF machine learning algorithm to determine factors that predict risk for multiple COPD exacerbations in a single year. This was a retrospective study with a data set of 106 patients. These patients were divided randomly into training (80%) and validating (20%) data-sets, 100 times, using approximately sixty variables intially, which in prior studies had been found to be associated with patient readmission for COPD exacerbation. In an interactive manner, an RF model was created using the training set and validated on the testing dataset. Mean area-under-curve (AUC) statistics, sensitivity, specificity, and negative/positive predictive values (NPV, PPV) were calculated for the 100 runs. THE FOLLOWING VARIABLES WERE FOUND TO BE IMPORTANT PREDICTORS OF PATIENTS HAVING AT LEAST TWO COPD EXACERBATIONS WITHIN ONE YEAR: employment, body mass index, number of previous surgeries, administration of azithromycin/ceftriaxone/moxifloxacin, and admission albumin level. The mean AUC was 0.72, sensitivity of 0.75, specificity of 0.56, PPV of 0.7 and NPV of 0.63. Histograms were used to confirm consistent accuracy. The RF design has consistently demonstrated encouraging results. We expect to validate our results on new patient groups and improve accuracy by increasing our training dataset. We hope that identifying patients at risk for frequent readmissions will improve patient outcome and save valuable hospital resources.