Assessing effect of perioperative glycemic control on adverse outcomes after emergency general surgery
In a retrospective cohort study by Jehan and colleagues1 assessing the effect of perioperative glycemic control on postoperative adverse outcomes in patients undergoing emergency general surgery, multivariate linear regression analysis showed that plasma hemoglobin A1c (HbA1c) of 6.0% or greater and a postoperative random blood sugar of 200 mg/dL or greater were independent predictors of major complications. Patients with both HbA1c of 6.0% or greater and a postoperative random blood sugar of 200 mg/dL or greater have a four times higher risk of developing postoperative major complications. Given that optimal glycemic control is important for postoperative outcomes of emergency surgical patients, their findings have potential implications. However, this is a retrospective study, which can introduce a number of potential confounders. Other than the limitations described in the discussion section of Jehan et al's article, we have noticed other issues from this study that were not well addressed.
First, this study included patients with HbA1c levels measured within 3 months before surgery. Given that HbA1c is a marker of glycemic control over the previous 3 months before the measurement, we are concerned that preoperative HbA1c levels used in this study cannot exactly represent the perioperative glycemic control of all patients. Moreover, this study aimed to assess the association of perioperative glycemic control with postoperative adverse outcomes. However, the readers were not provided the details of perioperative glycemic control strategies and targets. Actually, in surgical patients with and without diabetes mellitus, a single postoperative elevated blood sugar level has been significantly associated with morbidity and mortality; this risk is related to the degree of glucose elevation.2
Second, as a routinely measured variable, preoperative hemoglobin level was not provided in patients' data. The available evidence shows that preoperative anemia is a significant predictor of overall morbidity, serious morbidity, and increased length of stay after emergency surgery.3 Furthermore, this study provided overall and procedure-specific in-hospital mortality, complications and 30-day readmission rates, but surgical factors associated with the occurrence of postoperative adverse outcomes were not included in the multivariate model for risk adjustment. It has been shown that surgery type, timing of surgery, operation longer than 2 hours, visceral organ resection, intraoperative large blood loss, and blood transfusion are significantly associated with increased risks of morbidity and mortality after emergency surgery.4,5 Given that the above preoperative and intraoperative risk factors are not included in the multivariate model, we argue that association between preoperative HbA1c levels and postoperative adverse outcomes would have been biased.
Finally, this study performed the receiver operator characteristic (ROC) curve analysis and showed a 6% cutoff value of HbA1c for postoperative adverse outcomes, with a sensitivity and specificity of 85% and 79%. However, the readers were not provided the area under the ROC curve, which indicates the predictive performance of HbA1c of 6.0% or greater for postoperative adverse outcomes. For example, an area under the ROC curve of 0.90 to 1.0 indicated excellent (0.75–0.89), good (0.60–0.74), fair (0.50–0.59), or no predictive value.6 By the ROC curve analysis, the authors should provide the positive and negative predictive values of HbA1c of 6.0% or greater for postoperative adverse outcomes based on the cutoff value of HbA1c. In this way, the readers can estimate whether there is a good overall agreement between observed frequencies and predicted probabilities in the development and the validation sets.
We believe that addressing the above issues would further clarify the transparency of this study and improve interpretation of their results.