Association between elevated pre-operative glycosylated hemoglobin and post-operative infections after non-emergent surgery

Abstract

Background: A chronic state of impaired glucose metabolism affects multiple components of the immune system, possibly leading to an increased incidence of post-operative infections. Such infections increase morbidity, length of stay, and overall cost. This study evaluates the correlation between elevated pre-operative glycosylated hemoglobin (HbA1c) and post-operative infections.

Study design: Adult patients undergoing non-emergent procedures across all surgical subspecialties from January 2010 to July 2014 had a preoperative HbA1c measured as part of their routine pre-surgical assessment. 2200 patient charts (1100 < 6.5% HbA1c and1100 ≥ 6.5% HbA1c) were reviewed for evidence of post-operative infection (superficial surgical site infection, deep wound/surgical space abscess, pneumonia, and/or urinary tract infection as defined by Centers for Disease Control criteria) within 30 days of surgery.

Results: Patients with HbA1c < 6.5% and those with HbA1c ≥ 6.5% showed no statistically significant difference in overall infection rate (3.8% in the HbA1c < 6.5% group vs. 4.5% in the HbA1c ≥ 6.5% group, p = 0.39). Both linear regression and multivariate analysis did not identify HbA1c as an individual predictor of infection. Elevated HbA1c was, however, predictive of significantly increased risk of post-operative infection when associated with increased age (≥81 years of age) or dirty wounds.

Conclusions: The risk factors of post-operative infection are multiple and likely synergistic. While pre-operative HbA1c level is not independently associated with risk of post-operative infection, there are scenarios and patient subgroups where pre-operative HbA1c is useful in predicting an increased risk of infectious complications in the post-operative period.

Keywords: Complication; Glycosylated hemoglobin; Hyperglycemia; Infections; Surgery.

Fig. 1

Recursive partitioning decision tree. Parent node represents all 2200 patients included in the study. All cut points in the figure represent a level of a given predictor that portends a statistically significant (p < 0.05) difference in the rate of post-operative infection at that specified cut point.