SLIP-2 tops original model for identifying ARDS risk
Compared with the original surgical lung injury prediction model, SLIP-2 may be a better tool for uncovering high-risk patients.
SLIP-2 better identifies ARDS risk
HealthDay News – The updated surgical lung injury prediction (SLIP-2) model outperforms the original SLIP model for identifying patients at risk for postoperative acute respiratory distress syndrome (ARDS), according to researchers.
“Although ARDS prevention is a priority, the inability to identify patients at risk for ARDS remains a barrier to progress,” wrote Daryl J. Kor, MD, from the Mayo Clinic in Rochester, Minn., and colleagues in findings published in Anesthesiology.
The researchers conducted a secondary analysis of a multicenter, prospective cohort study that evaluated 1,562 high-risk patients undergoing surgery to determine which SLIP model predicted risk more effectively.
In the heterogeneous cohort with baseline risk factors for ARDS, the original SLIP score performed poorly (area under the receiver operating characteristic curve, 0.56), whereas the SLIP-2 score performed well (area under the receiver operating characteristic curve, 0.84). Similar discrimination was observed in internal validation, with an area under the receiver operating curve of 0.84.
The researchers found that 7.5% developed ARDS. Independent predictors of ARDS included sepsis, high-risk aortic vascular surgery, high-risk cardiac surgery, emergency surgery, cirrhosis, admission location other than home, increased respiratory rate (20 to 29 and ≥30 breaths/minute), fraction of inspired oxygen >35%, and oxygen saturation <95%.
"If validated in an independent sample, this tool may help identify surgical patients at high risk for ARDS," concluded the researchers.