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Quantifying risk of transfusion in children undergoing spine surgery
Michael G Vitale1, Douglas E Levy, Maxwell C Park
1International Center for Health Outcomes and Innovation Research, College of Physicians and Surgeons, Columbia University, 600 West 168th Street, 7th Floor, New York, NY 10032, USA. mgv16@yahoo.com
Background Context:
The risks and costs of transfusion are a great concern in the area of pediatric spine surgery, because it is a blood-intensive procedure with a high risk for transfusion. Therefore, determining the predictors of transfusion in this patient population is an important first step and has the potential to improve upon the current approaches to reducing transfusion rates. In this study, we reveal several predictors of transfusion in a pediatric patient population undergoing spine surgery. In turn, we present a general rule of thumb ("rule of two's") for gauging transfusion risk, thus enhancing the surgeon's approach to avoiding transfusion in certain clinical scenarios.
Purpose:
This study was conducted to determine the main factors of transfusion in a population of pediatric patients undergoing scoliosis surgery. The goal was to present an algorithm for quantifying the true risk of transfusion for various patient groups that would highlight patients "at high risk" for transfusion. This is especially important in light of the various risks associated with undergoing a transfusion, as well as the costs involved in maintaining and disposing of exogenous blood materials.
Study Design/Setting:
This is a retrospective review of a group of children who underwent scoliosis surgery between 1988 and 1995 at an academic institution.
Patient Sample:
A total of 290 patients were analyzed in this study, of which 63 were transfused and 227 were not.
Outcome Measures:
No outcomes measures were used in this study.
Methods:
A retrospective review of 290 patients presenting to our institution for scoliosis surgery was conducted, with a focus on socioclinical data related to transfusion risk. Univariate analysis and logistic regression were used to quantify the determinants of transfusion risk.
Results:
Univariate analysis identified many factors that were associated with the risk of transfusion. However, it is clear that several of these factors are dependent on each other, obscuring the true issues driving transfusion need. We used multivariate analysis to control for the various univariate predictors of transfusion. Our logistic regression model suggested that the type of scoliosis (odds ratio [OR], 2.02; 95% confidence interval [CI], 1.07 to 3.82), degree of curvature (OR, 1.012/degree curve; 95% CI, 1.01 to 1.03), and use of erythropoietin (OR, 0.29; 95% CI, 0.14 to 0.62) were the main determinants of transfusion risk for our population.
Conclusions:
The main risk factors of transfusion were used to formulate a simple algorithm, which can be used to quantify transfusion risk and to guide efforts to avoid transfusion in children undergoing spinal surgery. Given a 10% baseline risk for transfusion, our "rule of two's" indicates that each risk factor approximately doubles the chance of transfusion, whereas the administration of recombinant human erythropoietin roughly halves the risk of transfusion.