Surgical lung injury prediction model can help identify patients at high risk of ALI

A new study in the July issue of Anesthesiology helped developed a model that could determine which patients are at high risk of developing acute lung injury (ALI). Postoperative ALI is a life-threatening respiratory complication, with an estimated mortality exceeding 45 percent in certain surgical populations. Since ALI has limited treatment options, prevention may be more effective than treating the syndrome.

Researchers from Mayo Clinic in Rochester, MN, performed a secondary analysis of a prospective database and compared patients who developed ALI versus those who did not. From the analysis, preoperative risk factors for postoperative ALI were identified and evaluated for inclusion in the surgical lung injury prediction (SLIP) model.

"The SLIP model will help physicians study targeted prevention strategies in patients who are at moderate or high risk of ALI, while avoiding potential harm in patient's who are at low risk," said lead study author Daryl J. Kor, M.D.

Findings revealed that out of 4,366 patients, 2.6 percent developed early postoperative ALI. Patients who developed ALI were older and more likely to undergo high-risk cardiac, vascular, and thoracic surgery. Patients with diabetes mellitus, chronic obstructive pulmonary disease, gastroesophageal reflux disease, and alcohol abuse also were discovered to be at risk for ALI.

The model categorized all SLIP scores into three groups of patients: low risk (SLIP score ≤9), moderate risk (SLIP score 10 to 26), and high risk (SLIP score ≥27). "Future research will go one step further and test strategies to prevent postoperative ALI in patients who are determined to be at high risk using the SLIP score," continued Dr. Kor.


American Society of Anesthesiologists


The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
You might also like...
Novel predictors of severe respiratory syncytial virus infections among infants below the age of one