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Departments of
*Anesthesiology and
Biomathematical Sciences, The Mount Sinai School of Medicine; and
Department of Anesthesiology, St. Luke’s-Roosevelt Hospital Center, Columbia University, New York, New York
Address correspondence and reprint requests to David L. Reich, MD, Department of Anesthesiology, Box 1010, The Mount Sinai School of Medicine, One Gustave L. Levy Place, New York, NY 10029-6574. Address e-mail to dreich{at}smtplink.mssm.edu
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Abstract |
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Implications: Intraoperative hemodynamic abnormalities, including pulmonary hypertension, hypotension during cardiopulmonary bypass, and postcardiopulmonary bypass pulmonary diastolic hypertension, were independently associated with mortality, stroke, and perioperative myocardial infarction over and above the effects of other preoperative risk factors.
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Introduction |
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The results of previous studies (1–3 have been difficult to interpret because statistical analyses were limited to univariate tests. Multivariate analytical methods are required to assess the independent effects of the intraoperative hemodynamic aberrations on the risk of morbidity and mortality after adjusting for the effects of underlying medical conditions. For example, intraoperative hypertension may be a marker for essential hypertension, such that intraoperative blood pressure deviations may or may not add risk beyond that of the underlying condition of essential hypertension.
The advent of computerized intraoperative data acquisition systems provides the opportunity to record and store intraoperative hemodynamic data with great accuracy (5–7. Using such a system, the associations between intraoperative electrocardiographic (ECG) ST-segment changes and intraoperative hemodynamics with PMI have been published (8. The purpose of the current investigation was to determine whether intraoperative hemodynamic aberrations were independent predictors of perioperative mortality, stroke, or PMI using data derived from computerized anesthesia records and state-mandated cardiac surgical outcomes records at two hospitals in New York, NY.
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Methods |
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The outcomes analyzed were mortality (during same hospitalization after CABG), stroke, and PMI (transmural or nontransmural). Stroke was defined as a transient or permanent new focal neurologic deficit occurring intraoperatively through 24 h postoperatively. Transmural PMI was defined as new Q waves on the ECG, and an increase in creatine phosphokinase MB isoenzyme above the hospital laboratory’s myocardial infarction threshold occurring within 48 h after surgery. Nontransmural PMI was defined as an increase in creatine phosphokinase MB isoenzyme above the hospital laboratory’s myocardial infarction threshold occurring within 48 h after surgery with no new Q waves on the ECG. All patients underwent creatine phosphokinase MB testing.
Review by the New York State Bureau of Hospitals assured the accuracy of the data in the CSRS in the following fashion. Independent auditors reviewed 50 cases at each hospital at least every 3 yr and verified the database entries against the medical record. The New York State Bureau of Hospital Services performed regular frequency distributions of all risk factors to ascertain whether marked changes were occurring in the reporting frequency of various risk factors. Additionally, hospitals with outlying incidences of risk factors were required to provide supporting documentation from the medical record. Finally, the CSRS database was cross-correlated with the New York Statewide Planning and Research Cooperative System (SPARCS) database. Discrepancies in outcomes or length of hospital stay were reconciled by consultation with the reporting hospital (New York State Bureau of Hospital Services database administration staff, personal communication, 1999).
Intraoperative hemodynamic data were derived from computerized anesthesia records that automatically stored hemodynamic values every 15 s and were used in every CABG procedure at both hospitals (CompuRecordTM; Anesthesia Recording, Inc., Pittsburgh, PA). All patients undergoing CABG at these two centers had pulmonary artery catheters inserted at the beginning of the procedure, usually after the induction of anesthesia. Heart rate (HR), mean arterial pressure (MAP), systolic arterial pressure (SAP), diastolic arterial pressure (DAP), mean pulmonary arterial pressure (MPAP), systolic pulmonary arterial pressure (SPAP), diastolic pulmonary arterial pressure (DPAP), and right atrial pressure (RAP) were extracted from the computerized anesthesia records. The raw data obtained every 15 s contain artifactual values due to intermittent electrocautery interference and transducer flushing, among other causes. Therefore, the data were filtered for such artifacts by using the median value in consecutive 2-min epochs. Each CABG procedure was divided into three periods: precardiopulmonary bypass (pre-CPB), during cardiopulmonary bypass (CPB), and postcardiopulmonary bypass (post-CPB).
A Visual Basic (Microsoft, Inc., Redmond, WA) application was written to quantify the extent and duration of abnormal hemodynamic states in each of the three periods of the operation. For each period of the operation, the program classified the median value of every 2-min epoch into very low, low, normal, high, and very high categories according to defined limits (Table 1). For example, a SAP of <75 mm Hg was classified as low, 100 mm Hg as normal, and 180 mm Hg as high. The categorization of the extremes was exclusive, such that a SAP of 210 mm Hg was classified as very high, but not as high. Low and very low categories were not assigned for MPAP, SPAP, DPAP, and RAP. Additionally, each 2-min epoch was classified as labile or nonlabile according to a previously validated algorithm that quantified the rate of change between epochs (10. The only hemodynamic variable analyzed during the period of nonpulsatile CPB was MAP.
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Data for the preoperative risk factors in the CSRS database and for the derived hemodynamic abnormalities were summarized for each hospital to identify outliers and to characterize the distributions of these variables. For each hospital, bivariate contingency tables were created to examine the association between an outcome and a CSRS variable or hemodynamic measure. For this part of the analysis, continuous variables were categorized according to appropriate cutoff values. Significance levels were determined by 
2 tests of association, tests for trend, or Fisher’s exact test, as appropriate. Each CSRS or derived hemodynamic variable with a P value <0.20 at either hospital and with no marked discordance between the two hospitals was entered in the multivariate models. By using the univariate tests, 42 potential predictors from the CSRS database and the derived hemodynamic data were identified for mortality, 38 were identified for stroke, and 27 were identified for PMI. However, several variables that had been suggested as risk factors from a previous risk stratification scheme (e.g., aortic cross-clamp time and intraaortic balloon pump use) (11 and several of the derived hemodynamic abnormalities that are important clinically (e.g., MAP lability) were entered into the multivariate models despite their failure to meet the above criteria.
The independent influence of factors as they occur sequentially during CABG, while adjusting for previously established factors, was modeled using multivariate logistic regression analyses. Each outcome was modeled separately. To control for differences in some baseline rates between the two hospitals, a variable indicating hospital site was included in all the multivariate models. The analyses were conducted in three stages—variables representing patient characteristics and preoperative factors were tested first by using a forward stepwise procedure. Stepwise procedures were then used to identify additional independent factors measured in the pre-CPB period and the CPB phase of the procedure. These were added to the variables retained in the initial model, and the procedure was repeated with post-CPB variables. Thus, independent predictors that were identified during the initial stages of the stepwise multivariate regression may not have retained statistical significance as independent predictors in the final model. P < 0.05 was required for retention of a predictor in the multivariate model.
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Results |
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Discussion |
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After adjustment for relevant preoperative risk factors reported to the CSRS, several hemodynamic aberrations were predictors of adverse outcomes. Other hemodynamic abnormalities of clinical concern in the intraoperative period were examined—specifically, hemodynamic changes associated with tracheal intubation and hemodynamic lability (rapid changes in variables) throughout the operation (10. These hemodynamic aberrations were not independent predictors of mortality, stroke, or PMI in this patient sample.
A randomized, prospective trial of high versus low perfusion pressure during CPB found that the overall (combined) incidence of mortality or cardiac or neurologic complications was lower in the high perfusion pressure group (12. However, mortality and cardiac and neurologic complications did not differ between the perfusion groups in that study when considered separately. The independent association of low MAP during CPB with mortality in the current study lends further support to the hypothesis that low perfusion pressure during CPB may be deleterious.
There are very few reports of independent (multivariate) associations of intraoperative hemodynamic aberrations with complications. Jain et al. (8 reported that systolic blood pressure <90 mm Hg after CPB was an independent predictor of PMI, but this finding was not confirmed by the current study. Although the study populations were relatively similar, the incidence of PMI was markedly higher in the population studied by Jain et al. (8. No other hemodynamic predictors of PMI were found in that study (8. Although they observed that ST-segment abnormalities were independent predictors of PMI, the absence of ECG ST-segment data in our study prevents direct comparison with their data.
The CSRS database has been criticized by Green and Wintfeld (13 as an unreliable instrument based on dramatic changes in the reported incidence of preoperative risk factors that occurred after the publication of surgeon-specific mortality rates. Specifically, from 1989 through 1991, they noted a tripling in the reported incidence of chronic obstructive pulmonary disease. We have less concern regarding the validity of the CSRS data as it relates to this study for the following reasons. New York State subsequently created a rigorous system of data validation (previously discussed) that was in force during our study (1993–1995). In addition, in our initial examination of the CSRS data for outliers, we observed that the incidence of risk factors and outcomes was almost always consistent between hospitals and realistic in magnitude. PMI rates were an exception (see below).
Moreover, the premise of the critiques of the CSRS database is that surgeons underreport complications and overestimate preoperative risk factors to minimize their individual risk-adjusted mortality rates. The complications of in-hospital mortality and postoperative stroke are well defined and difficult to overlook. Overestimation of preoperative risk factors would have attenuated the independent predictive value of intraoperative hemodynamic aberrations in a multivariate approach. Despite putative problems with the CSRS data, we believe that potentially important hemodynamic predictors have been identified in this study.
Another limitation of the study is the necessity of categorizing hemodynamic variables into normal and abnormal groups based on defined, but arbitrary, limits (Table 1). The choice of absolute limits, rather than relative changes from baseline, was based on our concern that we could not establish the true baseline values in these patients with severe coronary artery disease on complex medical regimens.
The differences in risk factors and outcomes between hospitals is a problem that is encountered frequently in studies conducted at more than one site. It would be unreasonable to expect complete concordance between sites given the large number of variables analyzed in the univariate analyses. Hospital site was always included in the multivariate models in the current study. The only important difference between sites in the current study was in PMI rates.
The diagnosis of PMI is problematic and controversial. Badner et al. (14 noted that the PMI rate varied from 5.3% to 20.7% as four different sets of diagnostic criteria were applied to a cohort of 323 patients with increased cardiac risk undergoing noncardiac surgery. The CSRS database criteria vary somewhat due to interhospital laboratory differences in creatine phosphokinase MB isoenzyme myocardial infarction thresholds. The marked differences in nontransmural PMI rates between the sites in the current study highlights this difficulty. The use of more sensitive methods of PMI detection, such as troponin I and T assays, could have influenced our findings on the hemodynamic predictors of PMI. The lack of uniform laboratory criteria for PMI illustrates the importance of stratifying data by sites, as was done in this study. The hemodynamic predictors of PMI identified in the current study should be considered less robust findings than those for mortality and stroke based on these limitations.
The independent association of MAP <40 mm Hg with decreased PMI risk is probably related to two factors: the markedly lower PMI rate at Site A and the surgical practice of using brief periods of low-flow CPB during coronary artery anastomoses at that site. This technical difference in surgical approach between the hospitals may or may not account for the observed difference in PMI. We are therefore hesitant to conclude that very low MAP confers protection against PMI based on our data.
This was an observational study that considered a large number of variables and allowed us to identify hemodynamic abnormalities associated with adverse outcomes in patients undergoing treatment by specialized teams of cardiac anesthesiologists and surgeons. The hemodynamic changes observed in these patients occurred despite attempts to maintain normal hemodynamics intraoperatively. It does not necessarily follow, however, that more aggressive therapy aimed at normalizing hemodynamics would improve outcome. Determination of an outcome effect of such therapy would require a randomized clinical trial.
It is possible that the hemodynamic predictors of adverse outcome identified in this study were not the primary causes, but rather the markers, of pathophysiological states that caused the complications but are not recorded in the CSRS database or the anesthesia record. Three of the four predictors of mortality (high MPAP pre-CPB, high HR post-CPB, and high DPAP post-CPB) are consistent with left ventricular dysfunction. The remaining hemodynamic predictor of mortality (low MAP during CPB) could represent inadequate extracorporeal perfusion due to causes such as endotoxemia or exaggerated inflammatory responses to CPB (15. Alternatively, it could be an artifactual finding in patients who experienced exaggerated aortic-to-radial artery pressure gradients during CPB (16. Stroke is associated with hypertension, and increased DAP post-CPB may be a sign of previously undiagnosed hypertension. The high SPAP and DPAP post-CPB that were predictors of PMI may have been due to left ventricular dysfunction associated with PMI. Low HR pre-CPB may have been indicative of large doses of ß-adrenergic blocking drugs in patients with more severe underlying coronary artery disease or sinus node dysfunction. If the preceding scenarios are plausible, aggressive medical therapy to control hemodynamics might have no effect on the ultimate outcome.
Pulmonary artery catheters were the source of many of the independent intraoperative hemodynamic predictors of adverse outcome. Although our findings do not directly contribute to the debate regarding the effects of pulmonary artery catheters on patient outcomes (17, they do show that intraoperatively derived pulmonary artery catheter data have prognostic value in the cardiac surgical setting.
In conclusion, specific intraoperative hemodynamic aberrations were independently associated with mortality, stroke, and PMI. These findings demonstrate the prognostic relevance of intraoperative hemodynamics over and above the effects of certain preoperative risk factors. The question of whether outcomes could be improved by greater control of intraoperative hemodynamic variables awaits prospectively designed studies.
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Acknowledgments |
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Footnotes |
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References |
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