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Serum creatinine and perioperative outcome – a matched-pairs approach using computerised anaesthesia records

Published online by Cambridge University Press:  13 April 2005

M. G. Dehne ,
A. Junger ,
B. Hartmann ,
L. Quinzio ,
R. Röhrig ,
M. Benson  and
G. Hempelmann
M. G. Dehne
Affiliation:
University Hospital Giessen, Department of Anesthesiology, Intensive Care Medicine, and Pain Therapy, Giessen, Germany
A. Junger
Affiliation:
University Hospital Giessen, Department of Anesthesiology, Intensive Care Medicine, and Pain Therapy, Giessen, Germany
B. Hartmann
Affiliation:
University Hospital Giessen, Department of Anesthesiology, Intensive Care Medicine, and Pain Therapy, Giessen, Germany
L. Quinzio
Affiliation:
University Hospital Giessen, Department of Anesthesiology, Intensive Care Medicine, and Pain Therapy, Giessen, Germany
R. Röhrig
Affiliation:
University Hospital Giessen, Department of Anesthesiology, Intensive Care Medicine, and Pain Therapy, Giessen, Germany
M. Benson
Affiliation:
University Hospital Giessen, Department of Anesthesiology, Intensive Care Medicine, and Pain Therapy, Giessen, Germany
G. Hempelmann
Affiliation:
University Hospital Giessen, Department of Anesthesiology, Intensive Care Medicine, and Pain Therapy, Giessen, Germany
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Abstract

Summary

Background and objective: A study was designed to utilise the resources of our computerised anaesthesia record keeping system to assess the attributable effects of increased preoperative creatinine (>1.3 mg dL−1) on outcome in patients undergoing non-cardiac surgery.

Methods: This retrospective study was based on data sets of 58 458 patients recorded with a computerised anaesthesia record keeping system over a period of 4 yr at a tertiary care university hospital. Cases were defined as patients with a preoperative creatinine >1.3 mg dL−1; controls (creatinine ≤1.3 mg dL−1) were selected and automatically matched according to several parameters (ASA physical status, high risk and urgency of surgery, age and gender) in a stepwise fashion. Main outcome measures were hospital mortality and the incidence of intraoperative cardiovascular events.

Results: Three-thousand-and-twenty-eight patients (5.2%) had preoperative creatinine values >1.3 mg dL−1. Matching was successful for 54.5% of the cases, leading to 1649 cases (mean creatinine 3.3 ± 2.2 mg dL−1) and 1649 controls (1.0 ± 0.2 mg dL−1). The crude mortality rates for the cases and matched controls were 2.2% (n = 36) and 0.9% (n = 15), respectively (P = 0.003). Intraoperative cardiovascular events were found in 30.1% of the patients (n = 496) and in 28.3% of the matched controls (n = 466; P = 0.25, power = 0.46). Using logistic regression analyses a significant association between preoperative increased creatinine and hospital mortality was found (odds ratio 2.62; 95% confidence interval [1.39; 4.93]).

Conclusions: An increased preoperative serum creatinine in patients undergoing non-cardiac surgery is associated with an increased perioperative risk, but not with a higher incidence of intraoperative cardiovascular events.

Keywords

ANAESTHESIAINFORMATION SYSTEMSMEDICAL RECORD SYSTEMS, computerisedCREATININEKIDNEY FAILUREOUTCOME ASSESSMENT (HEALTHCARE)RISK ASSESSMENT, cardiovascular, morbidity, mortality
Type
Original Article
Information
European Journal of Anaesthesiology , Volume 22 , Issue 2 , February 2005 , pp. 89 - 95
Copyright
2005 European Society of Anaesthesiology

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References

Mann JF, Gerstein HC, Pogue J, Bosch J, Yusuf S. Renal insufficiency as a predictor of cardiovascular outcomes and the impact of ramipril: the HOPE randomized trial. Ann Intern Med 2001; 134: 629–636.Google Scholar
Gerstein HC, Bosch J, Pogue J, Taylor DW, Zinman B, Yusuf S. Rationale and design of a large study to evaluate the renal and cardiovascular effects of an ACE inhibitor and vitamin E in high-risk patients with diabetes. The MICRO-HOPE Study. Microalbuminuria, cardiovascular, and renal outcomes. Heart Outcomes Prevention Evaluation. Diabetes Care 1996; 19: 1225–1228.Google Scholar
Szczech LA, Best PJ, Crowley E, et al. Outcomes of patients with chronic renal insufficiency in the bypass angioplasty revascularization investigation. Circulation 2002; 105: 2253–2258.Google Scholar
Brady AR, Fowkes FG, Greenhalgh RM, Powell JT, Ruckley CV, Thompson SG. Risk factors for postoperative death following elective surgical repair of abdominal aortic aneurysm: results from the UK Small Aneurysm Trial. On behalf of the UK Small Aneurysm Trial participants. Br J Surg 2000; 87: 742–749.Google Scholar
Anderson RJ, O'Brien M, MaWhinney S, et al. Mild renal failure is associated with adverse outcome after cardiac valve surgery. Am J Kidney Dis 2000; 35: 1127–1134.Google Scholar
Mangano CM, Diamondstone LS, Ramsay JG, Aggarwal A, Herskowitz A, Mangano DT. Renal dysfunction after myocardial revascularization: risk factors, adverse outcomes, and hospital resource utilization. The Multicenter Study of Perioperative Ischemia Research Group. Ann Intern Med 1998; 128: 194–203.Google Scholar
Benson M, Junger A, Quinzio L, et al. Clinical and practical requirements of online software for anesthesia documentation: an experience report. Int J Med Inf 2000; 57: 155–164.Google Scholar
Benson M, Junger A, Quinzio L, et al. Data processing at the anesthesia workstation: from data entry to data presentation. Meth Inf Med 2000; 39: 319–324.Google Scholar
DGAI-Kommission ‘Qualitätssicherung und Datenverarbeitung in der Anästhesie'. Kerndatensatz Qualitätssicherung in der Anästhesie. Anästh Intensivmed 1993; 34: 331–335.
American Society of Anesthesiologists (ASA). New classification of physical status. Anesthesiology 1963; 24: 111.
Lee TH, Marcantonio ER, Mangione CM, et al. Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation 1999; 100: 1043–1049.Google Scholar
Erdfelder E, Faul F, Buchner A. GPOWER: a general power analysis program. Behavior Res Meth, Instr Comput 1996; 28: 1–11.Google Scholar
Eichhorn JH. Anesthesia record keeping. Int J Clin Monit Comput 1993; 10: 109–115.Google Scholar
Edsall DW, Deshane P, Giles C, Dick D, Sloan B, Farrow J. Computerized patient anesthesia records: less time and better quality than manually produced anesthesia records. J Clin Anesth 1993; 5: 275–283.Google Scholar
Benson M, Junger A, Fuchs C, et al. Using an anesthesia information management system to prove a deficit in voluntary reporting of adverse events in a quality assurance program. J Clin Monit 2000; 16: 211–217.Google Scholar
Benson M, Junger A, Quinzio L, et al. Influence of the method of data collection on the documentation of blood pressure readings with an Anesthesia Information Management System (AIMS). Meth Inf Med 2001; 40: 190–195.Google Scholar
Reich DL, Wood RK, Mattar R, et al. Arterial blood pressure and heart rate discrepancies between handwritten and computerized anesthesia records. Anesth Analg 2000; 91: 612–616.Google Scholar
Reich DL, Timcenko A, Bodian CA, et al. Predictors of pulse oximetry data failure. Anesthesiology 1996; 84: 859–864.Google Scholar
Jones CA, McQuillan GM, Kusek JW, et al. Serum creatinine levels in the US population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis 1998; 32: 992–999.Google Scholar
Röhrig R, Junger A, Hartmann B, et al. The incidence and prediction of automatically detected intraoperative cardiovascular events in noncardiac surgery. Anesth Analg 2004; 98: 569–577.Google Scholar
Perrone RD, Madias NE, Levey AS. Serum creatinine as an index of renal function: new insights into old concepts. Clin Chem 1992; 38: 1933–1953.Google Scholar
Swedko PJ, Clark HD, Paramsothy K, Akbari A. Serum creatinine is an inadequate screening test for renal failure in elderly patients. Arch Int Med 2003; 163: 356–360.Google Scholar
Anderson RJ, O'Brien M, MaWhinney S, et al. Renal failure predisposes patients to adverse outcome after coronary artery bypass surgery. VA Cooperative Study #5. Kidney Int 1999; 55: 1057–1062.Google Scholar
Szczech LA, Reddan DN, Owen WF, et al. Differential survival after coronary revascularization procedures among patients with renal insufficiency. Kidney Int 2001; 60: 292–299.Google Scholar
Culleton BF, Larson MG, Wilson PW, Evans JC, Parfrey PS, Levy D. Cardiovascular disease and mortality in a community-based cohort with mild renal insufficiency. Kidney Int 1999; 56: 2214–2219.Google Scholar
Detsky AS, Abrams HB, Forbath N, Scott JG, Hilliard JR. Cardiac assessment for patients undergoing noncardiac surgery. A multifactorial clinical risk index. Arch Intern Med 1986; 146: 2131–2134.Google Scholar
Wolters U, Wolf T, Stutzer H, Schröder T. ASA classification and perioperative variables as predictors of postoperative outcome. Br J Anaesth 1996; 77: 217–222.Google Scholar
Lagasse RS. Anesthesia safety: model or myth? A review of the published literature and analysis of current original data. Anesthesiology 2002; 97: 1609–1617.Google Scholar
Levey AS, Perrone RD, Madias NE. Serum creatinine and renal function. Annu Rev Med 1988; 39: 465–490.Google Scholar
Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976; 16: 31–41.Google Scholar