Author: Michael Vlessides
A study has found that intraoperative fluid management data can have an important role in risk prediction models for postoperative acute kidney injury.
The study, from Columbia University Irving Medical Center, in New York City, concluded that adding these data to baseline risk prediction models improves their accuracy, giving anesthesiologists another tool in preventing the often devastating complication.
Numerous Intra-op Factors Reviewed
To help answer this question, Dr. Kim and his colleagues used a cohort of patients presenting for general intraabdominal surgery at the medical center between 2005 and 2015. Preoperative data for each patient was obtained from the American College of Surgeons National Surgical Quality Improvement Program database, and intraoperative data were taken from the hospital’s Anesthesia Information Management System.
Variables were added to the baseline model that reflected intraoperative factors, including anesthetics, beta-blockers, blood pressure, fluid management, opioids and vasopressors. Variable selection for the additional intraoperative variables also used stepwise forward selection, with each intraoperative factor being evaluated separately. Improvement of the model was assessed by increases in the area under the curve of the receiver operator characteristic curve, as well as net reclassification improvement.
“In most previous studies, researchers have looked at the effect of a single exposure on the risk of postoperative AKI,” Dr. Kim said in an interview with Anesthesiology News. “I wanted to approach it in a different way; I wanted to look at what we do in the operating room and what that tells us about AKI risk beyond what we already know. I see the patient before surgery, and I know their baseline characteristics, demographics, comorbidities, and the type of surgery they’re about to have,” he explained. “What does intraoperative management data add to that?”
As Dr. Kim reported at the 2019 annual meeting of the International Anesthesia Research Society (abstract E136), 201 of the 2,691 patients in the cohort developed AKI, for a rate of 7.5%. The baseline predictive model classified 49% of the patients (n=1,321) as low risk (0-5% predicted risk); 39% (n=1,037) as medium risk (5%-15% predicted risk); and 12% (n=333) as high risk (>15% predicted risk). The area under the curve (AUC) for the baseline model was 0.769.
The study also found that only the addition of fluid management variables significantly increased the AUC of the baseline model (0.791; 95% CI, 0.762-0.821; P=0.005) and made a significantly positive net reclassification improvement (0.125; 95% CI, 0.053-0.197; P=0.001), compared with the baseline model.
“The results suggest that perhaps blood pressure [AUC, 0.788; P=0.01] and anesthetic variables [AUC, 0.783; P=0.02] may also be important,” Dr. Kim said. “But in my framework of multiple comparisons, I couldn’t say that they were significantly important.”
Anesthetic variables resulted in a net reclassification improvement of AUC 0.074 (95% CI, 0.016-0.131; P=0.01), while blood pressure contributed to an improvement of AUC 0.067 (95% CI, –0.007 to 0.141; P=0.08).
“So at least in this model, fluid management variables were the single factor we can say added more information about AKI risk compared to the baseline model,” Dr. Kim explained.
Specifically, three fluid management variables were added to the baseline model: albumin administration, hydroxyethyl starch solution administration and estimated blood loss. Other candidate variables not selected were the administration of lactated Ringer’s solution, red blood cells, plasma and normal saline, and urine output.
The study found that any administration of hydroxyethyl starch solution increased the odds of postoperative AKI by 80% (odds ratio [OR], 1.80; 95% CI, 0.97-3.34; P=0.04). Similarly, administration of more than 250 mL of albumin increased the risk for postoperative AKI by 118% (OR, 2.18; 95% CI, 1.45-3.30; P=0.001).
Despite the strength of the findings, Dr. Kim noted that the study has limitations, including the fact that interaction effects were not assessed, as there may be relationships between variables that were not evaluated.
“Perhaps adding variables from different intraoperative factors might produce a better model,” Dr. Kim noted. “A good anesthesiologist considers fluids, anesthetics, blood pressure and vasopressors together, and not in isolation, so this may be too clean of a framework.”
Nevertheless, the study may help improve intraoperative management and reduce the risk for AKI in patients undergoing general surgical procedures. “I think this shows that in one framework, fluid management is important,” Dr. Kim concluded. “But I think this is part of a larger body of work that can tease out which factors matter the most for individual patients, and hopefully we’ll pay more attention to these factors.”
As Frederic T. Billings IV, MD, MSc, commented, the authors are addressing an important question. “Historically, clinicians have focused on preoperative factors to predict postoperative AKI,” noted Dr. Billings, an associate professor of anesthesiology and medicine at Vanderbilt University School of Medicine, in Nashville, Tenn. “This may be in part due to limited ability to collect repeatedly measured hemodynamic data in anesthesia information systems that allow for the type of analysis performed in this study.
“As an anesthesiologist, we assume that a lot of the risk for AKI may be due to the intraoperative hemodynamic perturbations and management our patients receive,” Dr. Billings continued. “In addition, many of these intraoperative factors are modifiable, providing opportunities to affect AKI. For these reasons, it is of high interest to anesthesiologists and the field to understand the impact of intraoperative factors on prediction of AKI.”
As Dr. Billings went on to explain, it was no surprise to see that intraoperative fluid management was associated with AKI. “Fluid management is a mainstay of anesthetic practice, and these data reassert the importance of considering the type of fluid and the volume of fluid in the mitigation of AKI,” he said. “It is unclear, however, if the increased risk for AKI associated with hydroxyethyl starch and albumin administration is due to these fluids or confounding factors.”