Etomidate use and postoperative outcomes among cardiac surgery patients

Abstract

Background: Although a single dose of etomidate can cause relative adrenal insufficiency, the impact of etomidate exposure on postoperative outcomes is unknown. The objective of this study was to examine the association between a single induction dose of etomidate and clinically important postoperative outcomes after cardiac surgery.

Methods: The authors retrospectively examined the association between etomidate exposure during induction of anesthesia and postoperative outcomes in patients undergoing cardiac surgery from January 2007 to December 2009 by using multivariate logistic regression analyses and Cox proportional hazards regression analyses. Postoperative outcomes of interest were severe hypotension, mechanical ventilation hours, hospital length of stay, and in-hospital mortality.

Results: Sixty-two percent of 3,127 patients received etomidate. Etomidate recipients had a higher incidence of preoperative congestive heart failure (23.0 vs. 18.3%; P = 0.002) and a lower incidence of preoperative cardiogenic shock (1.3 vs. 4.0%; P < 0.001). The adjusted odds ratio for severe hypotension and in-hospital mortality associated with receiving etomidate was 0.80 (95% CI, 0.58-1.09) and 0.75 (95% CI, 0.45-1.24), respectively, and the adjusted hazard ratio for time to mechanical ventilation removal and time to hospital discharge was 1.10 (95% CI, 1.00-1.21) and 1.07 (95% CI, 0.97-1.18), respectively. Propensity score analysis did not change the association between etomidate use and postoperative outcomes.

Conclusions: In this study, there was no evidence to suggest that etomidate exposure was associated with severe hypotension, longer mechanical ventilation hours, longer length of hospital stay, or in-hospital mortality. Etomidate should remain an option for induction of anesthesia in cardiac surgery patients.

Fig. 1

Severe Hypotension Regression Analysis: Results are based on a multivariable logistic regression model, and odds ratios (OR) and 95% confidence intervals summarize the relative odds of severe hypotension. Calendar month, body mass index (BMI) and creatinine concentration were entered into the regression model flexibly using restricted cubic splines with four knots. To display effects sizes for the nonlinear effects, we chose a single reference value for each variable (calendar month = July 2008, BMI = 30 kg/m2, creatinine concentration = 1 mg/dl) and compared all other values to it. Due to lack of evidence suggesting a nonlinear relationship with any of the outcomes, the other continuous variables (age and ejection fraction) were modeled with linear terms and are included on the right with categorical variables. Categorical variables effects characterize the adjusted association between the outcome and the presence (vs. absence) of the risk factor. ACE = angiotensin-converting enzyme; CABG = coronary artery bypass graft; CHF = congestive heart failure.

Fig. 2

Time to Mechanical Ventilation (MV) Removal Regression Analysis: Results are based on a multivariable Cox proportional hazards model, and hazard ratios (HR) and 95% confidence intervals summarize the relative rates at which MV was removed. Calendar month, body mass index (BMI) and creatinine concentration were entered into the regression model flexibly using restricted cubic splines with four knots. To display effects sizes for the nonlinear effects, we chose a single reference value for each variable (calendar month = July 2008, BMI = 30 kg/m2, creatinine concentration = 1 mg/dl) and compared all other values to it. Due to lack of evidence suggesting a nonlinear relationship with any of the outcomes, the other continuous variables (age and ejection fraction) were modeled with linear terms and are included on the right with categorical variables. Categorical variable effects characterize the adjusted association between the outcome and the presence (vs. absence) of the risk factor. Note that HR greater than (less than) one implies shorter (longer) time on MV. ACE = angiotensin-converting enzyme; CABG = coronary artery bypass graft; CHF = congestive heart failure.

Fig. 3

Time to Hospital Discharge Regression Analysis: Results are based on a multivariable Cox proportional hazards model, and hazard ratios (HR) and 95% confidence intervals summarize the relative rates at which patients were discharged from the hospital. Calendar month, body mass index (BMI) and creatinine concentration were entered into the regression model flexibly using restricted cubic splines with four knots. To display effects sizes for the non-linear effects, we chose a single reference value for each variable (calendar month = July 2008, BMI = 30 kg/m2, creatinine concentration = 1 mg/dl) and compared all other values to it. Due to lack of evidence suggesting a nonlinear relationship with any of the outcomes, the other continuous variables (age and ejection fraction) were modeled with linear terms and are included on the right with categorical variables. Categorical variable effects characterize the adjusted association between the outcome and the presence (vs. absence) of the risk factor. Note that HR greater than (less than) one implies shorter (longer) length of stay. ACE = angiotensin-converting enzyme; CABG = coronary artery bypass graft; CHF = congestive heart failure.

Fig. 4

In Hospital Mortality Regression Analysis: Results are based on a multivariable logistic regression model, and odds ratios (OR) and 95% confidence intervals summarize the relative odds of mortality during the hospitalization. Calendar month, body mass index (BMI) and creatinine concentration were entered into the regression model flexibly using restricted cubic splines with four knots. To display effects sizes for the nonlinear effects, we chose a single reference value for each variable (calendar month = July 2008, BMI = 30 kg/m2, creatinine concentration = 1 mg/dl) and compared all other values to it. Due to lack of evidence suggesting a nonlinear relationship with any of the outcomes, the other continuous variables (age and ejection fraction) were modeled with linear terms and are included on the right with categorical variables. Categorical variables effects characterize the adjusted association between the outcome and the presence (vs. absence) of the risk factor. ACE = angiotensin-converting enzyme; CABG = coronary artery bypass graft; CHF = congestive heart failure.