Exclusive use of arterial grafts in coronary artery bypass operations for three-vessel disease: Use of both thoracic arteries and the gastroepiploic artery in 256 consecutive patients

Grandjean, Jan G.; Voors, Adriaan A.; Boonstra, Piet W.; Heyer, Peter den; Ebels, Tjark

doi:10.1016/s0022-5223(96)70093-4

Cited by 51 publications

(22 citation statements)

References 20 publications

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“…In this study, consistent with most studies, gender was not associated with higher AFIB prevalence rates (1,(15)(16)(27)(28)(29). Also consistent with our findings, most investigators have not identified a relationship between preexisting medical conditions and AFIB (1,13,14,18,24,25,27,28,(30)(31)(32). Two prior studies (4, 18) reported a relationship between AFIB and preexisting medical conditions.…”

Section: Discussion Preoperative Predictive Characteristicssupporting

confidence: 91%

“…The results of our regression analysis are similar to the results of others with respect to age (4,18,24,39). Almassi et al…”

Section: Regression Analysissupporting

confidence: 91%

“…The results of our regression analysis are similar to the results of others with respect to age (4,18,24,39). Almassi et al (1) reported a model that found age to be the strongest predictor for AFIB, followed by vein venting, chronic obstructive pulmonary disease, use of digoxin, and heart rate <80 beats per minute.…”

Section: Regression Analysissupporting

confidence: 88%

“…When the sample was limited to SCABG subjects only, the model did not change or improve appreciably. When the regression analysis was repeated using postoperative characteristics for the entire sample, no variables came forward for stepwise entry, and a combination of ECG dataevidence of infarct, ischemia, and right and left bundle branch block-only predicted AFIB correctly in 6.8% of cases.The results of our regression analysis are similar to the results of others with respect to age (4,18,24,39). Almassi et al…”

supporting

confidence: 91%

“…Age is the variable most consistently associated with post-CABG AFIB (1,4,9,11,13,16,(23)(24)(25)(26)(27). In this study, age provided the greatest contribution to the correct prediction of AFIB in the logistic regression model (14% of a total of 25% cumulative percent correct prediction).…”

Section: Discussion Preoperative Predictive Characteristicsmentioning

confidence: 50%

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Predictors and impact of atrial fibrillation after isolated coronary artery bypass grafting

Hravnak

Hoffman

Saul

et al. 2002

Critical Care Medicine

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Objective-Although an extensive number of studies have attempted to identify predictors of new-onset atrial fibrillation (AFIB) after coronary artery bypass grafting (CABG), a strong predictive model does not exist. Prior studies have included patients recruited from multiple centers with variant AFIB prevalence rates and those who underwent CABG in combination with other surgical procedures. Also, most studies have focused on pre-and perioperative characteristics, with less attention given to the initial postoperative period. The purpose of this study was to comprehensively examine pre-, peri-, and postoperative characteristics that might predict new-onset AFIB in a large sample of patients undergoing isolated CABG in a single medical center, utilizing data readily available to clinicians in electronic data repositories. In addition, length of stay and selected postoperative complications and disposition were compared in patients with AFIB and no AFIB. Design-Retrospective, comparative survey.Setting-University-affiliated tertiary care hospital.Patients-Patients with new-onset AFIB who underwent isolated standard CABG or minimally invasive direct vision coronary artery bypass were identified from an electronic clinical data repository. Interventions-None.Measurements and Main Results-The prevalence of AFIB in the total sample (n = 814) was 31.9%. Predictors of AFIB included age (p = .0004), number of vessels bypassed (p = .013), vessel location (diagonal [p < .003] or posterior descending artery [p < .001]), and net fluid balance on the operative day (p = .015). Forward stepwise regression analysis produced a model that correctly predicted AFIB in only 24% of cases, with age (14%) and body surface area (9%) providing the most prediction. The incidence of embolic stroke was higher in AFIB (n = 8) vs. no AFIB (n = 4) patients, but stroke preceded AFIB onset in seven of eight cases. Subjects with AFIB had a longer stay (p = .0004), more intensive care unit readmissions (p = .0004), and required more assistance at hospital discharge (p = .017).Conclusions-Despite attempts to examine comprehensively predictors of new-onset AFIB, we were unable to identify a robust predictive model. Our findings, in combination with prior work, imply that it may not be feasible to predict the development of new-onset AFIB after CABG using data readily available to the bedside clinician. In this sample, stroke was uncommon and, when it occurred, preceded AFIB in all but one case. As anticipated, AFIB increased length of stay, and patients with this complication required more assistance at discharge. Atrial fibrillation (AFIB) is the most common complication after coronary artery bypass grafting (CABG), with an incidence ranging from 5% to 40% (1-5). Although post-CABG AFIB is not associated with a significant increase in mortality (6), it has been noted to result in increased morbidity related to postoperative stroke (7,8), hemodynamic compromise (9), ventricular dysrhythmias (10), and iatrogenic complications associated with...

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