Korean J Adult Nurs.  2023 May;35(2):85-96. 10.7475/kjan.2023.35.2.85.

Validation of Prediction Models for Postoperative Pulmonary Complications after Lung Resection: A Retrospective Study

• Jung S
• Hwang SK

• KMID: 2543041
• DOI: http://doi.org/10.7475/kjan.2023.35.2.85

Abstract

Purpose
This study aimed to verify the potential use of postoperative pulmonary complications prediction models in patients with lung resection.
Methods
In this retrospective study, 1,160 patients were selected among the admitted patients who underwent lung resection surgery. The predictive validity of the Assess Respiratory Risk in Surgical Patients in Catalonia Tool (ARISCAT) and the Pulmonary Complications Risk Score (PCRS)-lung resection model were assessed based on the sensitivity, specificity, positive and negative predictive values, and Area Under the receiver operating characteristic Curve (AUC).
Results
Of the patients, 420 (36.2%) developed postoperative pulmonary complications after lung resection surgery within 30 days. The sensitivity, specificity, positive predictive values, and negative predictive values were 52.2%, 70.6%, 49.0%, and 74.0%, respectively, for the ARISCAT (cut-off point of 47), and 53.8%, 78.5%, 15.3%, and 95.9%, respectively, for the PCRS-lung resection model (cut-off point of 147). The AUCs were 0.65 (ARISCAT) and 0.70 (PCRS-lung resection model).
Conclusion
The findings indicate that the predictive validity values of the ARISCAT was sufficient, and the PCRS-lung resection model was good. However, the clinical usefulness of the models should be verified in future studies.

Keyword

Postoperative complications; Pneumonectomy; Predictive value of tests