Development and Validation of Procedure-Specific Risk Score for Predicting Postoperative Pulmonary Complication: A NSQIP Analysis

Carrie A. Foster, Eric J. Charles, Florence E. Turrentine, Min Woong Sohn, Irving L. Kron, R. Scott Jones

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


Background: Postoperative pulmonary complications (PPCs; unplanned reintubation, postoperative pneumonia, and failure to liberate from mechanical ventilation within 48 hours), contribute significantly to increased rates of morbidity and mortality. Procedure type is an important factor that contributes risk in generalized PPC prediction models. The objective of this study was to develop and validate procedure-specific risk scores for the 6 procedures with the highest rates of PPCs. Study Design: American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Participant Use File data (2005 to 2015) for patients undergoing pancreatectomy, hepatectomy, esophagectomy, abdominal aortic aneurysm repair, open aortoiliac repair, and lung resection were used for analysis. Multivariable logistic regression was used to develop pulmonary complications risk scores (PCRS) for each procedure. Youden indices were used to identify cutoff points within each PCRS and were further validated using a random selection of the original NSQIP dataset collected. Results: Twenty-one variables were included in the initial analysis, which yielded unique relative risk score models for each procedure. Within all the risk score models, long operative time (within the last quartile) was a strong predictor of PPCs. An increased rate of PPCs was associated with increasing PCRS values in both the training and validation samples for all procedures. Conclusions: Important variables were identified for 6 common procedures that yield an increased risk of PPCs. These variables differed by procedure type, outlining the importance of procedure-specific risk scores. Each procedure-specific PCRS developed in this study can be used by health care professionals to better predict the risk of PPCs and to optimize patient outcomes.

Original languageEnglish
Pages (from-to)355-365.e3
JournalJournal of the American College of Surgeons
Issue number4
StatePublished - Oct 2019

Bibliographical note

Funding Information:
Support: This work was supported by the National Heart, Lung, and Blood Institute (grant numbers UM1 HL088925 and T32 HL007849 ). Original scientific article

Publisher Copyright:
© 2019 American College of Surgeons

ASJC Scopus subject areas

  • Surgery


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