We found no differences between the SICU outcomes by univariable analysis while dividing the patients based on their emergent surgery status and SRCI. There was no significant association between the preoperative clinical variables (ASA physical status class, SRCI, and surgery risk) and mortality outcomes.
The information obtained by univariable analysis was used to perform regression analysis. In the multivariable regression analysis, we considered sex, age, emergent surgery, SRCI, and surgery risk as possible confounders. After adjusting for confounders, the multivariable regression analysis revealed that ASA physical status class is significantly associated with SICU length of stay (IRR = 1.79, 95% CI, 1.35–2.39, P < 0.001), mechanical ventilation duration (IRR = 2.57, 95% CI, 1.69–3.92, P < 0.001), vasopressor treatment duration (IRR = 3.57, 95% CI, 1.84–6.94, P < 0.001), number of acquired organ dysfunction (IRR=1.71, 95% CI, 1.46–1.99, P < 0.001), and readmission to SICU within 7 days (odds ratio = 3.39, 95% CI, 1.04–11.09, P = 0.02). The interpretation of the multivariable analysis (Table 4) reveals that for each unit increase in ASA physical status class, there was a 79% increase in the rate of SICU length of stay, 157% increase in the rate of mechanical ventilation duration, 257% increase in the rate of vasopressor treatment duration, and 71% increase in the rate of number of acquired organ dysfunction. The univariable and multivariable regression analyses revealed significant association between surgery risk and number of organ dysfunction (IRR = 1.56, 95% CI, 1.29–1.89, P < 0.001, and adjusted IRR = 1.31, 95% CI, 1.05–1.64, P = 0.02).
We used univariable analysis information to guide the regression analysis. Our study revealed an association between ASA physical status class and important SICU outcomes: SICU length of stay, duration of mechanical ventilation, duration of vasopressor treatment, number of acquired organ dysfunctions, and readmission to the SICU. There was a significant difference between sex, emergency surgery status, ASA physical status class, SICU length of stay, mechanical ventilation duration, and number of acquired organ dysfunctions based on surgical risk. SRCI was not significantly associated with SICU outcomes. The emergent nature of the procedure was not associated with worse SICU outcomes in our population, by univariable and regression analysis. There was no association of any preoperative clinical data with mortality.
ASA physical status class is an assessment measure based on physical status and has been associated with increased postoperative mortality6,7 and postoperative complications18,19 including increased ICU length of stay.11 ASA physical status class accuracy was challenged by a historical survey that tested the consistency of ASA physical status classification by different anesthesia providers based on hypothetical scenarios.20 ASA physical status class is a very simple assessment measure based on physical status that has been associated with postoperative mortality and postoperative complications despite the question of inconsistency across different anesthesia providers. Our present study was adequately powered to show a difference of 3 days between the mean in SICU length of stay based on ASA physical status class by univariable analysis, which supports good association between ASA physical status class and SICU length of stay. In addition, our study also demonstrated association between ASA physical status class and most of the other assessed SICU outcomes, such as duration of mechanical ventilation, duration of vasopressor treatment, number of acquired organ dysfunctions, and readmission to the SICU. The readmission to SICU was found to be associated with increased hospital mortality in a prospective observational study.21 In our study, readmission to the ICU is not associated with increased mortality, perhaps because of the lower readmission rate (5%) and SICU mortality (3.2%) in our patient population.
Our study did not find a significant association of SRCI with SICU outcomes, probably because most of our patients (79.5%) had 0 or 1 criteria which correlated with <1% cardiac complications in the study by Lee et al.13 When patients were stratified by these criteria, the risk of major cardiac complications with 0, 1, 2, and 3+ criteria was 0.4% to 0.5%, 0.9% to 1.3%, 4% to 7%, and 9% to 11%, respectively.13 The RCI validated by Lee et al.13 in 1999 is considered the “gold standard” for prediction of perioperative cardiovascular major events, and 5 of its criteria are used in the ACC/AHA guidelines.15 Other studies contested the RCI prediction accuracy for cardiovascular complications and/or mortality perioperatively.22,23
We used a simple grading system for surgery based on ACC/AHA guidelines15 and found that surgical risk is associated with the SICU outcomes in univariable analysis. Most of our patients (81%) were stratified as intermediate risk. According to 1 large prospective study, the rate of serious adverse events postoperatively was 16.9%, and mortality was 7.1%.24 Efforts for surgery stratification and assessment of risks were studied by various teams, and scores such as POSSUM and IRIS use complex models to predict surgical outcomes.25,26 By dividing the patients based on surgical risk, we demonstrated significant differences not only between SICU outcomes but also between sex and emergency surgery status distribution. The patients who had vascular surgery were predominantly men and had emergent procedures. Furthermore, abdominal aortic aneurysms are more common in men.27 The likelihood of emergent surgery in patients with surgical risk 3 in our institution may be related to higher frequency of organ transplantation.
We did not find an association between emergent surgery (32% of our patients) and ICU outcomes. Due to the small sample size, the regression analysis for emergent surgery revealed large 95% 2-sided CI for vasopressor treatment duration and readmission to SICU within 7 days, but narrow 95% CI for other variables, most likely due to the variance difference (Table 4). Emergent surgery status was associated with worse postoperative outcomes in numerous studies.7,19,26 One study found emergency status association with shorter hospital stay, with most of the patients having emergent surgery being ASA physical status I.28 We extrapolate that ASA physical status class is a more powerful risk factor than the emergency status alone.
There was no association between preoperative clinical variables and mortality in our study. ICU mortality rates vary widely among studies from 7% to 15%.29–31 SICU mortality is lower in our institution than in most of the published studies; therefore, we might not see a significant influence of the preoperative clinical data on mortality rates.
Our study has several limitations. The retrospective design of our study could have generated confounders that are not assessed in the study. We did not assess for comorbidities, such as respiratory disease or malignancy, but ASA physical status class is increased based on comorbidities severity. Nineteen of the 239 patients screened were excluded based on missing consent before ICU admission. The reason for autoexclusion might have been the severity of the illness, which impeded the patients’ ability to sign consent for research on admission. Our sample size was relatively small but adequately powered to show a clinically significant difference between the SICU lengths of stay based on ASA physical status class by univariable analysis. We acknowledge the limitation due to smaller sample size that did not allow us to perform a thorough investigation of the interaction effects by multivariable regression analysis. Neurosurgery patients were excluded, since they were treated by a different team, similar to the study by Lee et al.13 Other studies found that neurosurgery patients have a lower risk for serious adverse events preoperatively than thoracic or general surgery patients.21,24 Cardiac surgery patients were excluded as well considering the specifics of physiologic changes after cardiopulmonary bypass and its effects on ICU stay.
In conclusion, we evaluated a limited number of relatively easy-to-use risk assessment tools used frequently in everyday practice of an anesthesiologist. Our study results confirm the importance of ASA physical status class for the appreciation of postoperative complications and SICU outcomes. Our study further supports the use of ASA physical status class and surgical risk as important assessment tools for SICU risk stratification and association with serious nonfatal morbidity and resource utilization.
Name: Monica I. Lupei, MD.
Contribution: This author contributed to the design and the conduct of the study, data collection, data interpretation and analysis, and the manuscript preparation.
Attestation: Monica I. Lupei approved the final manuscript and attests to the integrity of the original data and the analysis reported in the manuscript. This author is the archival author who is responsible for maintaining the study records.
Name: Jeffrey G. Chipman, MD.
Contribution: This author helped design the study and prepare the manuscript.
Attestation: Jeffrey G. Chipman approved the final manuscript.
Name: Gregory J. Beilman, MD.
Contribution: This author helped design the study and prepare the manuscript.
Attestation: Gregory J. Beilman approved the final manuscript.
Name: S. Cristina Oancea, PhD.
Contribution: This author contributed to the data interpretation and analysis and the manuscript preparation.
Attestation: S. Cristina Oancea approved the final manuscript.
Name: Mojca R. Konia, MD, PhD.
Contribution: This author contributed to the study design, data collection, interpretation and analysis, and the manuscript preparation.
Attestation: Mojca R. Konia attests to the integrity of the original data and the analysis reported in the manuscript. This author approved the final manuscript.
This manuscript was handled by: Steven L. Shafer, MD.
The authors thank Dr. Ioanna Apostolidou, MD, PhD, Associate Professor of Anesthesiology, University of Minnesota, for providing advice and recommendations for the manuscript preparation.
a Available at: http://www.asahq.org/Home/For-Members/Clinical-Information/ASA-Physical-Status-Classification-System. Accessed January 17 2014. Cited Here...
1. Gruenberg DA, Shelton W, Rose SL, Rutter AE, Socaris S, McGee G. Factors influencing length of stay in the intensive care unit. Am J Crit Care. 2006;15:502–9
2. Ryan TA, Rady MY, Bashour CA, Leventhal M, Lytle B, Starr NJ. Predictors of outcome in cardiac surgical patients with prolonged intensive care stay. Chest. 1997;112:1035–42
3. Fakhry SM, Kercher KW, Rutledge R. Survival, quality of life, and charges in critically ill surgical patients requiring prolonged ICU stays. J Trauma. 1996;41:999–1007
4. Halpern NA, Pastores SM, Greenstein RJ. Critical care medicine in the United States 1985-2000: an analysis of bed numbers, use, and costs. Crit Care Med. 2004;32:1254–9
5. Saklad M. Grading of patients for surgical procedures. Anesthesiology. 1941;2:281–4
6. Dripps RD, Lamont A, Eckenhoff JE. The role of anesthesia in surgical mortality. JAMA. 1961;178:261–6
7. Vacanti CJ, VanHouten RJ, Hill RC. A statistical analysis of the relationship of physical status to postoperative mortality in 68,388 cases. Anesth Analg. 1970;49:564–6
8. Marx GF, Mateo CV, Orkin LR. Computer analysis of postanesthetic death. Anesthesiology. 1973;39:54–8
9. Aronson WL, McAuliffe MS, Miller K. Variability in the American Society of Anesthesiologists Physical Status Classification Scale. AANA J. 2003;71:265–74
10. Menke H, Klein A, John KD, Junginger T. Predictive value of ASA classification for the assessment of the perioperative risk. Int Surg. 1993;78:266–70
11. Wolters U, Wolf T, Stützer H, Schröder T. ASA classification and perioperative variables as predictors of postoperative outcome. Br J Anaesth. 1996;77:217–22
12. Prause G, Ratzenhofer-Comenda B, Pierer G, Smolle-Jüttner F, Glanzer H, Smolle J. Can ASA grade or Goldman’s cardiac risk index predict peri-operative mortality? A study of 16,227 patients. Anaesthesia. 1997;52:203–6
13. Lee TH, Marcantonio ER, Mangione CM, Thomas EJ, Polanczyk CA, Cook EF, Sugarbaker DJ, Donaldson MC, Poss R, Ho KK, Ludwig LE, Pedan A, Goldman L. Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation. 1999;100:1043–9
14. Moitra VK, Flynn BC, Mazzeffi M, Bodian C, Bronheim D, Ellis JE. Indication for surgery, the revised cardiac risk index, and 1-year mortality. Ann Vasc Surg. 2011;25:902–8
15. Fleischmann KE, Beckman JA, Buller CE, Calkins H, Fleisher LA, Freeman WK, Froehlich JB, Kasper EK, Kersten JR, Robb JF, Valentine RJ. 2009 ACCF/AHA focused update on perioperative beta blockade: a report of the American college of cardiology foundation/American heart association task force on practice guidelines. Circulation. 2009;120:2123–51
16. Marshall JC, Cook DJ, Christou NV, Bernard GR, Sprung CL, Sibbald WJ. Multiple organ dysfunction score: a reliable descriptor of a complex clinical outcome. Crit Care Med. 1995;23:1638–52
17. Vincent JL, de Mendonça A, Cantraine F, Moreno R, Takala J, Suter PM, Sprung CL, Colardyn F, Blecher S. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on “sepsis-related problems” of the European Society of Intensive Care Medicine. Crit Care Med. 1998;26:1793–800
18. Tiret L, Hatton F, Desmonts JM, Vourc’h G. Prediction of outcome of anaesthesia in patients over 40 years: a multifactorial risk index. Stat Med. 1988;7:947–54
19. Cohen MM, Duncan PG. Physical status score and trends in anesthetic complications. J Clin Epidemiol. 1988;41:83–90
20. Owens WD, Felts JA, Spitznagel EL Jr. ASA physical status classifications: a study of consistency of ratings. Anesthesiology. 1978;49:239–43
21. Kaben A, Corrêa F, Reinhart K, Settmacher U, Gummert J, Kalff R, Sakr Y. Readmission to a surgical intensive care unit: incidence, outcome and risk factors. Crit Care. 2008;12:R123
22. Röhrig R, Junger A, Hartmann B, Klasen J, Quinzio L, Jost A, Benson M, Hempelmann G. The incidence and prediction of automatically detected intraoperative cardiovascular events in noncardiac surgery. Anesth Analg. 2004;98:569–77
23. Boersma E, Kertai MD, Schouten O, Bax JJ, Noordzij P, Steyerberg EW, Schinkel AF, van Santen M, Simoons ML, Thomson IR, Klein J, van Urk H, Poldermans D. Perioperative cardiovascular mortality in noncardiac surgery: validation of the Lee cardiac risk index. Am J Med. 2005;118:1134–41
24. Bellomo R, Goldsmith D, Russell S, Uchino S. Postoperative serious adverse events in a teaching hospital: a prospective study. Med J Aust. 2002;176:216–8
25. Copeland GP. The POSSUM system of surgical audit. Arch Surg. 2002;137:15–9
26. Mangano DT. Perioperative cardiac morbidity. Anesthesiology. 1990;72:153–84
27. Harthun NL. Current issues in the treatment of women with abdominal aortic aneurysm. Gend Med. 2008;5:36–43
28. Voney G, Biro P, Roos M, Frielingsdorf B, Shafighi M, Wyss P. Interrelation of peri-operative morbidity and ASA class assignment in patients undergoing gynaecological surgery. Eur J Obstet Gynecol Reprod Biol. 2007;132:220–5
29. Rhodes A, Moreno RP, Metnitz B, Hochrieser H, Bauer P, Metnitz P. Epidemiology and outcome following post-surgical admission to critical care. Intensive Care Med. 2011;37:1466–72
30. Resche-Rigon M, Azoulay E, Chevret S. Evaluating mortality in intensive care units: contribution of competing risks analyses. Crit Care. 2006;10:R5
© 2014 International Anesthesia Research Society
31. Uusaro A, Kari A, Ruokonen E. The effects of ICU admission and discharge times on mortality in Finland. Intensive Care Med. 2003;29:2144–8