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Observational Study
. 2014 May;120(5):1168-81.
doi: 10.1097/ALN.0000000000000216.

Predicting risk of postoperative lung injury in high-risk surgical patients: a multicenter cohort study

Affiliations
Observational Study

Predicting risk of postoperative lung injury in high-risk surgical patients: a multicenter cohort study

Daryl J Kor et al. Anesthesiology. 2014 May.

Abstract

Background: Acute respiratory distress syndrome (ARDS) remains a serious postoperative complication. Although ARDS prevention is a priority, the inability to identify patients at risk for ARDS remains a barrier to progress. The authors tested and refined the previously reported surgical lung injury prediction (SLIP) model in a multicenter cohort of at-risk surgical patients.

Methods: This is a secondary analysis of a multicenter, prospective cohort investigation evaluating high-risk patients undergoing surgery. Preoperative ARDS risk factors and risk modifiers were evaluated for inclusion in a parsimonious risk-prediction model. Multiple imputation and domain analysis were used to facilitate development of a refined model, designated SLIP-2. Area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test were used to assess model performance.

Results: Among 1,562 at-risk patients, ARDS developed in 117 (7.5%). Nine independent predictors of ARDS were identified: 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/min), FIO2 greater than 35%, and SpO2 less than 95%. The original SLIP score performed poorly in this heterogeneous cohort with baseline risk factors for ARDS (area under the receiver operating characteristic curve [95% CI], 0.56 [0.50 to 0.62]). In contrast, SLIP-2 score performed well (area under the receiver operating characteristic curve [95% CI], 0.84 [0.81 to 0.88]). Internal validation indicated similar discrimination, with an area under the receiver operating characteristic curve of 0.84.

Conclusions: In this multicenter cohort of patients at risk for ARDS, the SLIP-2 score outperformed the original SLIP score. If validated in an independent sample, this tool may help identify surgical patients at high risk for ARDS.

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Figures

Figure 1
Figure 1
Study participant flow diagram. ALI indicates acute lung injury; ARDS, acute respiratory distress syndrome; ED, emergency department; LIPS, Lung Injury Prediction Score.
Figure 2
Figure 2
Receiver operating characteristic curves comparing the original surgical lung injury prediction (SLIP) model with the revised SLIP-2 predictive algorithm. AUC indicates area under the receiver operating characteristic curve.
Figure 3
Figure 3
Incidence of acute respiratory distress syndrome (ARDS) by risk group. Frequency of ARDS increased with increasing associated risk, as determined by the surgical lung injury prediction model 2 (SLIP-2) score: low-risk group (n=623), moderate-risk group (n=503), and high-risk group (n=120).

Comment in

  • Transforming high risk to high yield.
    Bartels K, Grenz A, Eltzschig HK. Bartels K, et al. Anesthesiology. 2014 May;120(5):1072-4. doi: 10.1097/ALN.0000000000000217. Anesthesiology. 2014. PMID: 24755782 Free PMC article. No abstract available.

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