Abstract
Objective
To define predictors for prolonged ICU stay in order to improve patient outcome and reduce costs.
Patients and methods
Prospective data on 10,759 patients undergoing coronary artery bypass grafting with and without use of cardiopulmonary bypass (coronary artery bypass grafting, CABG; n =8,917; off-pump coronary artery bypass grafting, OPCAB; n =765; minimally invasive direct coronary artery bypass grafting, MIDCAB; n =1,077) between April 1996 and August 2001 were subjected to univariate and, consecutively, to multivariate logistic regression analysis. Prolonged ICU stay was defined as intensive care treatment for three postoperative days and longer.
Measurements and results
Mean duration of ICU stay was 3.8±6.9 days; overall prevalence of prolonged ICU stay was 37.1%. The hospital mortality was 3.5% (ICU ≥3 days: 5.9%; ICU <3 days: 2.0%). Out of 39 selected pre- and intraoperative patient- and treatment-related variables, by univariate analysis, 32 variables having a high association with prolonged ICU stay were identified. Using a stepwise logistic regression model, 20 variables were shown to be independent predictors for prolonged ICU stay. Both OPCAB and MIDCAB surgery were identified as having a significantly lower association with prolonged ICU stay.
Conclusion
As prolonged ICU stay is associated with poor patient outcome and increased costs it is of utmost importance to identify patients at a high risk for prolonged ICU stay. More frequent off-pump CABG may optimize patient outcome.
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Introduction
Despite refinements in perioperative management, prolonged intensive care unit (ICU) stay is still associated with poor patient outcome and increased costs [1, 2, 3]. Due to improvements in medical treatment, such as off-pump coronary artery bypass grafting (OPCAB) and recent trends in interventional cardiology, the profile of patients referred to cardiac surgery has altered substantially. There is a growing number of elderly patients carrying substantial additional risk factors as well as those requiring repeat cardiac surgery. This has led to an increased proportion of high-risk patients in recent years resulting in impaired patient outcome and increasingly expensive care [4, 5].
While several studies have used multivariate analysis to predict the risk of death after cardiac surgery and to develop scoring systems to identify patients at high risk for intra- and postoperative mortality, there is little data regarding predictors for postoperative morbidity and prolonged ICU stay especially after coronary artery bypass surgery with and without cardiopulmonary bypass (CPB). The value of mortality as the sole end-point in the evaluation of clinical trials has been questioned. Instead, morbidity has been suggested as a valid end-point [6]. In 1990, Hammermeister and associates conducted a study to identify risk factors predisposing towards major complications after cardiac surgery. They found older age, congestive heart failure, vascular disease, higher serum creatinine, and previous cardiac surgery to be risk factors for the development of renal failure, low cardiac output, and requirement for prolonged mechanical support [7].
However, new therapeutic strategies, such as off-pump CABG, may be beneficial with regard to postoperative morbidity and the need for intensive care treatment even in high-risk subgroups.
The aim of the present study was to systematically investigate the prevalence and possible predictors of prolonged ICU stay, as well as variables leading to a prolonged ICU stay, after coronary artery bypass grafting in the era of new, less invasive surgical techniques.
Material and methods
Study population
Ten thousand seven hundred and fifty-nine consecutive adult patients undergoing coronary artery bypass surgery between April 1996 and August 2001 were included in this study. As shown in Table 1, conventional CABG surgery with cardiopulmonary bypass was performed (Conv-CABG) in 8,917 patients, and 1,842 patients underwent CABG on the beating heart without cardiopulmonary bypass (CPB) either through a median sternotomy (off-pump coronary artery bypass grafting, OPCAB; n =765) or through a left lateral minithoracotomy (minimally invasive direct coronary artery bypass grafting, MIDCAB; n =1,077) (Table 1). Patients were assigned to one of the surgical techniques according to clinical indications (e.g., MIDCAB approach in patients with one-vessel disease). Throughout this study the choice of performing conventional or off-pump CABG was up to the individual surgeon. Initially, only selected patients were considered candidates for off-pump revascularization, whereas after an initial period of 6–12 months it was performed much more frequently. From the middle of 1997 onwards two out of nine staff surgeons used the off-pump technique whenever feasible; from 1998 onwards this increased to three staff surgeons; and from 2000 onwards four staff surgeons used this techique when feasible. Thirty-one patients, who initially had beating heart operations (either OPCAB or MIDCAB approach) had to be converted to a conventional strategy with cardiopulmonary bypass, intraoperatively. Intraoperative conversion was necessary in cases of hemodynamic instability, inability to expose the native coronary vessel with mechanical stabilizers on the beating heart, intramural course of the native coronary vessels or inability to anastomose the bypass vessel in cases in which the target coronary vessel was too small to perform a safe anastomosis on the beating heart. These patients were excluded from the beating heart groups and assigned to the Conv-CABG group.
Definition of prolonged ICU stay
Postoperative prolonged ICU stay was defined as intensive care treatment either at the intensive care unit or the intermediate care unit (without mechanical ventilation) lasting for 3 days and longer. Patients requiring intensive care treatment on at least three nonconsecutive days were also assigned to the group with prolonged ICU stay as they suffered from severe postoperative complications, possibly associated with one of the analyzed pre- and intraoperative variables. Patients only temporarily readmitted to the intermediate care unit for electrical cardioversion or pleurocentesis, for example, were not assigned to the group with prolonged ICU stay. In cases of readmitted patients staying on the ICU for 1 day and more, these days were added to the initial number of days on the ICU. If the total number reached or exceeded 3 days, those patients were included in the group of patients with prolonged ICU stay.
Data collection
Perioperative data were recorded prospectively using an online database system as described previously (Medwork database software, Lenz + Partner, Germany) [8]. All variables analyzed were entered prospectively to achieve a complete and valid data set for each patient. The validity of the data was routinely ensured by using this information for generating text documents, thus resulting in a meticulous confirmation of the data entered by the user. The pre- and intraoperative risk factors that were included in a univariate analysis and consecutively in a stepwise logistic regression model are listed in Table 2.
Statistical analysis
Continuous variables are expressed as mean±standard deviation, and categorical data as proportions. Continuous variables between patients with and without prolonged ICU stay were compared using the student's unpaired t-test or analysis of variance (ANOVA), with the appropriate correction for multiple comparisons. Categorical variables were compared by χ2 analysis. Univariate analysis of risk factors was performed calculating odds ratios (OR) with a 95% confidence interval. Variables with a P-value less than 0.05 were consecutively subjected to a multivariate logistic regression model to assess the independent impact of the risk factors on prolonged ICU stay. A stepwise procedure (backward Wald) was used. A P-value less than 0.05 was used to enter and eliminate variables [9]. All statistical analyses were performed using the SPSS statistical package 9.0 (SPSS, Birmingham, Ala., USA).
Results
Patient characteristics are shown in Table 1. The mean age of the study population was 65.0±9.5 years. Patients aged over 70 years constituted 34.8% of the study population (age 70–79 years 31.7% and age over 80 years 3.1%, respectively). Most of the patients in the study population were male (77.0%). Patients in the MIDCAB group were significantly younger than both the Conv-CABG and the OPCAB group, respectively (P <0.0001). The age within the OPCAB group was significantly lower than the Conv-CABG group (P =0.022). With regard to preoperative left ventricular ejection fraction (LVEF), patients in the MIDCAB group had a higher LVEF than patients both in the Conv-CABG and in the OPCAB group (P <0.0001 vs Conv-CABG and P =0.021 vs OPCAB, respectively). Prevalence of impaired NYHA-classification (≥3) was significantly higher in the Conv-CABG group than both the MIDCAB and the OPCAB group (P <0.0001 vs MIDCAB and P =0.003 vs OPCAB, respectively), whereas the prevalence in the OPCAB group was significantly higher compared to the MIDCAB group (P =0.039). However, the prevalence of impaired CCS-classification (≥3) was found to be highest in the OPCAB group, being significantly different in comparison to the Conv-CABG (P <0.0001) and the MIDCAB group (P =0.001). No differences with regard to the CCS-classification were found between the Conv-CABG and the MIDCAB group (P =n.s.). The number of coronary bypass grafts in the Conv-CABG group was significantly higher than the OPCAB and the MIDACB group (P <0.0001, respectively). Furthermore, patients undergoing MIDCAB surgery received a significantly lower number of bypass grafts than the OPCAB group (P <0.0001). Prevalence of previous coronary bypass grafting was significantly higher in the OPCAB than the Conv-CABG group (P =0.048). No significant differences have been found between the MIDCAB and the Conv-CABG group and between both beating heart groups (P =n.s.)
With regard to the postoperative need for rethoracotomy defined as chest reopening due, in almost all cases, to bleeding the prevalence was highest within the MIDCAB group (8.0%) reaching statistical significance as compared to the Conv-CABG group (6.8%; P =0.036), whereas there were no statistically significant differences between both beating heart groups (OPCAB: 7.2%; P =n.s.) and between the OPCAB and the Conv-CABG group (P =n.s.).
Patients with prolonged ICU stay were significantly older (66.6±9.3 years vs 64.0±9.4 years; P< 0.0001) and had a significantly lower preoperative left ventricular ejection fraction (50.7%±21.2 vs 55.2%±20.1; P <0.0001) as compared to patients with a normal ICU stay. The majority of patients both with and without prolonged ICU stay were male gender (76.2% vs 77.5%; P =n.s.). The mean duration of ICU stay in all patients was 3.8±6.9 days and the overall prevalence of prolonged ICU stay was 37.1%.
The prevalence of prolonged ICU stay varied among the different surgical procedures as shown in Fig. 1. The highest prevalence was found in the Conv-CABG group as compared to both the OPCAB and the MIDCAB group (P <0.0001 for both groups). Within the beating heart group the prevalence in the MIDCAB group was significantly lower than the OPCAB group [(P =0.004); Fig. 1]. The mean duration of postoperative ICU stay in patients with prolonged intensive care treatment was 7.7±10.2 days.
By using univariate analysis, 32 out of 39 variables were identified as having a high association with prolonged ICU stay (see table in Appendix).
By stepwise logistic regression analysis, 20 variables were identified as independent predictors of ICU stay for 3 postoperative days and longer, as well as two variables that were found to be associated with a significantly lower prevalence of prolonged ICU stay (Table 2). Prevalence and statistically significant differences of independent predictors as related to the different surgical procedures are shown in Table 3.
Perioperative (30 day) mortality was 3.5%. Mortality in the prolonged ICU group was significantly higher than patients with normal ICU stay [(5.9% vs 2.0%; P< 0.0001); Fig. 2]. The highest mortality rate was found in the Conv-CABG group for patients with prolonged ICU stay as well as for those with normal ICU stay, which was the lowest in the MIDCAB group for both subgroups (Fig. 2).
Discussion
Quantification of operative risk is a major problem in contemporary cardiac surgery especially with the background of an increasing number of high-risk patients. Although considerable information has been published on preoperative predictors of mortality after cardiac surgery, only a few studies have assessed such predictors of major complications resulting in prolonged ICU stay after cardiac surgery. A reliable yet simple global evaluation of the cardiac surgical patient's preoperative condition will improve assessment of the effects of surgical, anesthetic, and intensive care management. There is a clear relationship between the presence of co-morbidities and duration of ICU stay, suggesting that preoperative prediction of postoperative morbidity is important for assessment of expected length of stay, estimation of projected costs, and resource utilization [2].
Prolonged intensive care treatment in this series was intentionally defined as an ICU stay for 3 days and more. This relatively broad time-frame includes almost all patients suffering from postoperative complications after cardiac surgery leading to an increased requirement for intensive care treatment. Excluding those patients from the study would have biased the impact of the analyzed potential risk factors on patient outcome. It is probably due to this underlying definition of prolonged ICU stay that an unexpectedly large number of pre- and intraoperative predictors have been significantly associated with prolonged intensive care treatment in this series.
As reported in other series, a significant relationship was found between the presence of severe heart failure [NYHA ≥3 (OR: 1.12); LVEF ≤30% (OR: 1.38)] frequently resulting in the need for urgent operation (OR: 1.52), cardiogenic shock (OR: 1.39), preoperative myocardial infarction (OR: 1.21), and prolonged intensive care treatment in this series. In addition, advanced patient age [age ≥70 and <80 years (OR: 1.32) and age ≥80 years (OR: 1.78)] is a significant predictor of prolonged ICU stay as reported previously [2, 10]. Elderly patients constitute an increasing fraction of the cardiac surgical population and advanced age is known to be a significant risk factor, especially for non-cardiac morbidity such as renal and neurologic complications or multisystem organ failure after cardiac surgery [4, 5, 11, 12, 13, 14]. Furthermore, age-related losses of physiological reserves affect different organ systems to varying degrees and contribute to the increased morbidity observed in the elderly cardiac surgical patient.
Several concomitant diseases associated with vascular alterations such as atherosclerosis have been found to be significant predictors of prolonged ICU stay in this series. Not surprisingly, diabetes mellitus as one of the well-known risk factors of artherosclerotic disease has been found to be independently associated with prolonged intensive care treatment (OR: 1.29) [15, 16, 17]. In addition, peripheral vascular disease as a systemic disorder, was significantly associated with prolonged ICU stay as well (OR: 1.36). In this context, the association of a history of cerebrovascular disease (OR: 1.45), such as TIA, PRIND, or manifest stroke, and history of embolism (OR: 1.30) with a prolonged need for intensive care treatment was not an unexpected finding. The first denotes the existence of pathologic conditions within the cerebrovascular system and/or underlying stenoses of one or both carotid arteries. Other investigators have demonstrated a 7–13% incidence of postoperative stroke for patients with a history of previous neurologic events, leading to a prolonged requirement for mechanical ventilation and a delayed postoperative mobilization with a subsequent demand for intensive care treatment in most cases [18, 19]. The latter, as well as a history of atrial fibrillation as another significant risk factor (OR: 1.47), has a well-recognized association with the recurrent risk of thromboembolization and, subsequently, with a higher risk of intraoperative cerebral embolization during cardiac surgery, possibly leading to postoperative neurobehavioral deficits as described previously [20, 21].
Preoperative renal disease (OR: 2.1) has been shown to be significantly associated with postoperative renal failure leading to a prolonged intensive care treatment by some [22, 23]. Furthermore, Anderson and associates found renal failure as a predisposing factor for several adverse outcomes, including neurologic deficits, in patients undergoing coronary bypass surgery [24]. Several previous studies as well as our study revealed preoperative pulmonary disease (OR: 1.4) as an important predictor for postoperative morbidity and/or mortality [22, 23, 25].
Five intraoperative variables [operation time ≥3 h (OR: 1.35); perfusion time ≥2 h (OR: 1.59); intraoperative hemofiltration (OR: 1.26); intraoperative pacemaker stimulation (OR: 1.3); intraoperative IABP-support (OR: 1.69)] have been found to be independent predictors of prolonged ICU stay. All of them often denote technical difficulties in executing the planned operation due to unfavorable anatomy or intraoperative complications. Intraoperative hemofiltration possibly reflects a preoperatively existing renal insufficiency requiring additional treatment.
Both beating heart approaches, MIDCAB and OPCAB, have been shown to be significantly associated with a lower prevalence of prolonged ICU stay as confirmed by previous investigators [26, 27, 28, 29, 30]. However, preoperative patient characteristics in the beating heart group revealed a younger mean age and higher left ventricular ejection fraction both in the OPCAB and the MIDCAB group than in the Conv-CABG group. In addition, prevalence of severe clinical symptoms (NYHA and CCS classification ≥3) was significantly higher in the Conv-CABG group as compared to both beating heart groups. In contrast to these findings, prevalence of prior coronary artery bypass grafting was higher in both beating heart groups compared to the Conv-CABG group. These differences may reflect a selection bias, with lower-risk patients being referred for beating heart surgery, as we did not follow a randomized protocol. However, it is important to note that both beating heart groups did not have the lowest prevalence of all independent predictors for prolonged ICU stay (Table 3).
In summary, in this series of patients—after coronary artery bypass surgery either with cardiopulmonary bypass or on the beating heart—several pre- and intraoperative patient- or treatment variables have been shown to be significantly associated with prolonged ICU stay. Understanding the multivariate regressions presented in this study and their analysis should enable identification of a high-risk subset of patients undergoing coronary artery bypass surgery. The lower prevalence of prolonged ICU stay in both beating heart groups seems to argue for a benefit of eliminating CPB in patients undergoing coronary bypass surgery.
References
Ryan TA, Rady MY, Bashour A, Leventhal M, Lytle B, Starr NJ (1997) Predictors of outcome in cardiac surgical patients with prolonged intensive care stay. Chest 112:1035–1042
Tuman KJ, McCarthy RJ, March RJ, Najafi H, Ivankovich AD (1992) Morbidity and duration of ICU stay after cardiac surgery. A model for preoperative risk assessment. Chest 102:36–44
Rosenberg AL, Watts C (2000) Patients readmitted to ICUs. A systemic review of risk factors and outcomes. Chest 118:492–502
Warner CD, Weintraub WS, Craver JM, Jones EL, Gott JP, Guyton RA (1997) Effect of cardiac surgery patient characteristics on patient outcomes from 1981 through 1995. Circulation 96:1575–1579
Kalmár P, Irrgang E (2000) Cardiac surgery in Germany during 2000. A report by the German Society for Thoracic and Cardiovascular Surgery. Thorac Cardiovasc Surg 48:33–38
Petros AJ, Marshall JC, van Saene HKF (1995) Should morbidity replace mortality as an end-point for clinical trials in intensive care? Lancet 345:369–371
Hammermeister M, Burchfield C, Johnson R, Grover FL (1990) Identification of patients at greatest risk for developing major complications after cardiac surgery. Circulation 82[Suppl]):380–389
Gummert JF, Kluge M, Reissmann EM, Bung J, Mohr FW (1998) Einführung eines komplexen medizinischen Dokumentationssystems am Herzzentrum Leipzig. In: Krian A, Scheld HH (ed) Dokumentationsverfahren in der Herzchirurgie III. Steinkopff, Darmstadt, pp 99–103
Rosner BA (1995) Fundamentals of biostatistics, 4th edn. Duxbury-Press, Belmont, Calif., USA
Tu JV, Jaglal SB, Naylor CD, and the Steering Committee of the Provincial Adult Cardiac Care Network of Ontario (1995) Multicenter validation of a risk index for mortality, intensive care unit stay and overall hospital length of stay after cardiac surgery. Circulation 91:677–684
Lynn GM, Stefanko K, Reed JF III, Gee W, Nicholas G (1992) Risk factors for stroke after coronary artery bypass. J Thorac Cardiovasc Surg 104:1518–1523
Newman MF, Wolman R, Kanchuger M, Marschall K, Mora-Mangano C, Roach G, Smith LR, Aggarwal A, Nussmeier N, Herskowitz A, Mangano DT (1996) Multicenter preoperativestroke risk index for patients undergoing coronary artery bypass graft surgery. Circulation 94[Suppl 2]:74–80
Horneffer PJ, Gardner TJ, Manolio TA, Hoff SJ, Rykiel MF, Pearson PA, Gott VL, Baumgartner WA, Borkon AM, Watkins L (1987) The effects of age on outcome after coronary bypass surgery. Circulation 76:6–12
Avery II GJ, Ley SJ, Hill D, Hershon JJ, Dick SE (2001) Cardiac surgery in the octogenerian: evaluation of risk, cost, and outcome. Ann Thorac Surg 71:591–596
Roach GW, Kanchuger M, Mora Mangano C, Newman M, Nussmeier N, Wolman R, Aggarwal A, Marschall K, Graham SH, Ley C (1996) Adverse cerebral outcomes after coronary bypass surgery. Multicenter study of perioperative ischemia research group and the ischemia research and education foundation investigators. N Engl J Med 335:1857–1863
Stamou SC, Hill PC, Dangas G, Pfister AJ, Boyce SW, Dullum MK, Bafi AS, Corso PJ (2001) Stroke after coronary artery bypass: incidence, predictors, and clinical outcome. Stroke 32:1508–1513
Morricone L, Ranucci M, Denti S, Cazzaniga A, Isgro G, Enrini R, Caviezel F (1999) Diabetes and complications after cardiac surgery: comparison with a non-diabetic population. Acta Diabetol 36:77–84
Rorich MB, Furlan AJ (1990) Risk at cardiac surgery in patients with prior stroke. Neurology 40:835–837
Shaw PJ, Bates D, Cartlidge NEF, French JM, Heaviside D, Julian DG, Shaw DA (1989) An analysis of factors predisposing to neurological injury in patients undergoing coronary bypass operations. Q J Med 72:633–646
Hammon JW Jr, Stump DA, Kon ND, Cordell AR, Hudspeth AS, Oaks TE, Brooker RF, Rogers AT, Hilbawi R, Coker LH, Troost BT (1997) Risk factors and solutions for the development of neurobehavioral changes after coronary artery bypass grafting. Ann Thorac Surg 63:1613–1618
Clark RE, Brillman J, Davis DA, Lovell MR, Price TR, Magovern GJ (1995) Microemboli during coronary artery bypass grafting. Genesis and effect on outcome. J Thorac CardiovascSurg 109:249–257
Kurki TSO, Kataja M (1996) Preoperative prediction of postoperative morbidity in coronary artery bypass grafting. Ann Thorac Surg 61:1740–1745
Higgins TL, Estafanous FG, Loop FD, Beck GJ, Blum JM, Paranadi L (1992) Stratification of morbidity and mortality outcome by preoperative risk factors in coroanry artery bypass patients. JAMA 267:2344–2348
Anderson RJ, O' Brian M, MaWhinney S, Villa Nueva CB, Moritz TE, Sethi GK, Henderson WG, Hammermeister KE, Grover FL, Shroyer AL (1999) Renal failure predisposes patients to adverse outcome after coronary bypass surgery. Kidney Int 55:1057–1062
Hannan EL, Kilburn H, O'Donnell J, Lukacik G, Shields EP (1990) Adult open heart surgery in New York State. An analysis of risk factors and hospital mortality rates. JAMA 264:2768–2774
Murkin JM, Boyd WD, Ganapathy S, Adams SJ, Peterson RC (1999) Beating heart surgery: why expect less central nervous system morbidity? Ann Thorac Surg 68:1498–1501
Kshettry VE, Flavin TF, Emery RW, Nicoloff DM (2000) Does multi-vessel off-pump coronary artery bypass (OPCABG) reduce postoperative morbidity? Ann Thorac Surg 69:1725–1730
Mack MJ, Osborne JA, Shennib H (1998) Arterial graft patency in coronary artery bypass grafting: what do we really know? Ann Thorac Surg 66:1055–1059
Bull DA, Neumayer LA, Stringham JC, Meldrum P, Affleck DG, Karwande SV (2001) Coronary artery bypass grafting with cardiopulmonary bypass versus off-pump cardiopulmonary bypass grafting: does eliminating the pump reduce morbidity and cost? Ann Thorac Surg 71:170–175
Plomondon ME, Cleveland JC, Ludwig ST, Grunwald GK, Kiefe CI, Grover FL, Shroyer AL (2001) Off-pump coronary artery bypass is associated with improved risk-adjusted outcomes. Ann Thorac Surg 72:114–119
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Appendix
Appendix
The following table shows peroperative variables analyzed by univariate analysis (factors that had a statistically significant association with prolonged ICU-stay are printed in bold)
Patients with ICU−stay ≥3 days (n =3,988) | Patients with ICU−stay <3 days (n =6,771) | ||
---|---|---|---|
Preoperative variables | Prevalence % (n) | P−value | |
Age | |||
Age <60 years | 18.3% (730) | 29.1% (1,973) | <0.0001 |
Age ≥70 and <80 years | 37.2% (1,483) | 28.4% (1,926) | <0.0001 |
Age ≥80 years | 4.3% (171) | 2.4% (161) | <0.0001 |
History of syncope | 8.4% (336) | 7.3% (494) | 0.033 |
History of embolism | 3.5% (138) | 2.2% (148) | <0.0001 |
History of cardiogenic shock | 11.1% (442) | 5.2% (353) | <0.0001 |
Diabetes mellitus (glucose intolerance treated with diet, oral hypoglycemics or insulin) | 41.2% (1,645) | 33.1% (2,238) | <0.0001 |
Arterial hypertension (patient taking antihypertensive medication preoperatively) | 75.8% (3,021) | 72.3% (4,898) | <0.0001 |
History of renal disease (history of renal failure or pathological elevated serum creatinine treated medically without hemofiltration and/or dialysis) | 6.4% (256) | 2.3% (159) | <0.0001 |
Dialysis dependent renal insufficiency | 1.1% (42) | 0.3% (19) | <0.0001 |
Preoperative infection (infectious disease including endocarditis) | 1.5% (59) | 0.6% (42) | <0.0001 |
History of cerebrovascular disease (including stroke, TIA, and PRIND) | 4.7% (186) | 2.6% (178) | <0.0001 |
NYHA ≥3 | 81.8% (3,263) | 76.4% (5,175) | <0.0001 |
LVEF ≤30% (assessed by angiography or 2D echocardiography) | 11.1% (441) | 6.1% (413) | <0.0001 |
History of peripheral vascular disease | 26.2% (1,046) | 17.2% (1,164) | <0.0001 |
Atrial fibrillation (history of preoperative atrial fibrillation) | 5.9% (235) | 3.0% (202) | <0.0001 |
Urgent operation | 27.5% (1,097) | 16.4% (1,100) | <0.0001 |
Emergency surgery (emergent surgery due to complications during coronary angiography and/or PTCA) | 1.1% (42) | 0.6% (39) | 0.008 |
History of pulmonary disease (chronic pathologic pulmonary function test) | 8.0% (320) | 4.8% (325) | <0.0001 |
Prior myocardial infarction | 58.5% (2,331) | 51.4% (3,479) | <0.0001 |
CCS ≥3 | 37.8% (1,509) | 35.9% (2,435) | 0.05 |
Sex (male) | 76.2% (3,039) | 77.5% (5,250) | 0.117 |
Hyperlipidemia | 52.7% (2,100) | 54.3% (3,679) | 0.155 |
Prior cardiac surgery | 4.4% (174) | 3.7% (252) | 0.102 |
Prior CABG | 3.8% (150) | 3.1% (213) | 0.097 |
Prior aortic valve surgery | 0.2% (9) | 0.4% (26) | 0.219 |
Prior mitral valve surgery | 0.1% (6) | 0.2% (16) | 0.386 |
Intraoperative variables | |||
Duration of surgery ≥3 h | 24.1% (961) | 16.4% (1,113) | <0.0001 |
Total CPB time ≥2 h | 10.9% (435) | 4.3% (293) | <0.0001 |
Ischemic time ≥1 h | 11.6% (462) | 8.9% (607) | <0.0001 |
Intraoperative hemofiltration | 9.2% (367) | 4.7% (321) | <0.0001 |
Intraoperative hypothermia ≤32 °C | 29.2% (1,166) | 21.3% (1,439) | <0.0001 |
Intraoperative RBC transfusion ≥1,000 ml | 2.9% (115) | 1.0% (67) | <0.0001 |
Intraoperative low cardiac output | 3.9% (154) | 1.1% (75) | <0.0001 |
Intraoperative IABP−support | 4.2% (168) | 1.2% (78) | <0.0001 |
Intraoperative assist device (ECMO, Berlin heart) | 1.4% (54) | 0.4% (24) | <0.0001 |
Intraoperative need for pacemaker stimulation | 19.5% (776) | 11.3% (766) | <0.0001 |
Use of cardioplegia | 76.3% (3,043) | 69.6% (4,711) | <0.0001 |
Beating heart surgery | 10.4% (415) | 21.1% (1,427) | <0.0001 |
OPCAB | 4.9% (194) | 8.0% (544) | <0.0001 |
MIDCAB | 5.3% (210) | 12.8% (867) | <0.0001 |
Coronary bypass grafts ≥2 | 82.5% (3,290) | 75.7% (5,127) | <0.0001 |
Intraoperative blood loss ≥500 ml | 0.7% (26) | 0.4% (26) | 0.061 |
CABG coronary artery bypass grafting, OPCAB off-pump coronary artery bypass grafting, MIDCAB minimally invasive direct coronary artery bypass grafting, RBC red blood cells, LVEF left ventricular ejection fraction, PTCA percutaneous transluminal coronary angioplasty, CPB cardiopulmonary bypass, IABP intra-aortic ballon pump, ECMO extracorporal membrane oxygenation
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Bucerius, J., Gummert, J.F., Walther, T. et al. Predictors of prolonged ICU stay after on-pump versus off-pump coronary artery bypass grafting. Intensive Care Med 30, 88–95 (2004). https://doi.org/10.1007/s00134-003-1950-5
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DOI: https://doi.org/10.1007/s00134-003-1950-5