For critically ill patients with respiratory failure, none of the available risk indexes is particularly robust in terms of distinguishing survivors from nonsurvivors within the perioperative period. To address this, a University of California, Los Angeles (UCLA) research team has proposed a novel index that may prove to be more relevant to critically ill patients in the perioperative environment.
“We had an ICU patient come in for surgery who was so sick that it prompted a discussion among the anesthesiologists about his chances for survival after surgery,” said Vadim Gudzenko, MD, assistant clinical professor of anesthesiology in the Division of Critical Care at UCLA. “As a result, we looked at the literature and saw that not very much research has been performed in this specific subset of patients.”
Although preoperative risk stratification indexes have traditionally emphasized cardiac-related morbidity and mortality in patients undergoing elective, noncardiac surgery, medical advances have led to an increasing number of critically ill patients presenting for diagnostic or therapeutic interventions. Given this changing landscape, the researchers investigated the ability of three indexes to predict hospital survival in critically ill patients with underlying respiratory failure.
“We wanted to find the index that would best predict mortality in these patients,” Dr. Gudzenko commented. “Anesthesiologists usually use the ASA [American Society of Anesthesiologists] class—which correlates well with many outcomes—to assign the level of complexity to a particular patient. It’s a great tool, but how good is it for patients who are coming to the ICU?”
Predictive Indexes
To help answer this question, Dr. Gudzenko and his colleagues reviewed the medical records of ICU patients presenting at UCLA between July 1, 2013, and July 31, 2014. Patients were deemed eligible for inclusion if they were in respiratory failure in the ICU before a surgical or interventional procedure. Of 1,251 cases screened, 301 were included in the final analysis; the study’s primary outcome was survival to discharge. The three indexes studied were ASA physical status, the Revised Cardiac Risk Index (RCRI) and the Sequential Organ Failure Assessment (SOFA) score.
As reported at the 2015 annual meeting of the ASA (abstract A4042), 200 critically ill patients with respiratory failure underwent the 301 procedures. Of these, 48 (24%) did not survive to discharge. Perhaps not surprisingly, significant differences were found between survivors and nonsurvivors with respect to ASA class (3.7 vs. 3.9; P=0.03), RCRI (1.7 vs. 2.5; P=0.001) and SOFA score (8.8 vs. 11.2; P=0.005).
What proved more intriguing was that the three indexes only provided modest discrimination on the basis of the area under the curve (AUC) for these relationships. The RCRI proved the most useful (0.66), followed by SOFA (0.64) and then ASA physical status (0.59). “When we looked at the predictive indices, we realized that none of them are really very good, at least as applies to our cohort,” Dr. Gudzenko said.
Of note, the ASA physical status scale was the worst in terms of predicting mortality. “The beauty of the ASA scale is that it’s subjective, but this is also its limitation: It’s based on the gestalt of anesthesiology practice,” Dr. Gudzenko told Anesthesiology News. “It performs well in experienced hands, but its subjectivity leaves it open to interpretation.”
Preoperative variables that were significantly associated (P<0.05) with mortality included age, history of coronary artery disease, heart failure, diabetes and renal dysfunction, as well as vasopressor requirements, platelet count and serum creatinine.
The investigators also performed a multifactorial analysis, which revealed that emergent nature, heart failure, diabetes and vasopressor requirements were the most useful factors in predicting survival to discharge. With that in mind, they created an index of these four components—dubbed the UCLA Score—which was found to outperform other scores and indexes (AUC=0.75). “We feel our model is the best of them all,” Dr. Gudzenko noted. “It not only has very good correlation with overall mortality, but every additional point actually correlates with decreased survival by about 15%.”
Although the novel index is currently being validated at other institutions, the investigators hope it may help improve both patient care and the utilization of hospital resources in the future.
“The question is, can we use this information to tailor treatment for our patients and provide better care?” he asked. “Not only that, but can we use this information to help us choose the best management approach for critically ill patients?
“I think as a first step, it will help clinicians make decisions about the overall feasibility of their interventions. We can keep almost anybody alive in the OR [operating room], but what happens in the next couple of weeks is the most important question. And is it really worth it to go through invasive and aggressive interventions when poor outcome was predicted even before we started?”
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