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Related Experiment Video

Updated: Mar 6, 2026

An R-Based Landscape Validation of a Competing Risk Model

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Comparative Evaluation of Risk Scores for Predicting Postoperative Pulmonary Complications.

Wenting Zhang¹, Yingying Gao¹, Shengfang Li¹

¹Drs. Zhang, Gao, Li, Huang, Guo, Wu, Yang, Mo, Huang, and Mr. Xu are affiliated with Department of intensive care unit, Peking University Shenzhen Hospital, Shenzhen, China.

Respiratory Care

|March 5, 2026

Summary

Postoperative pulmonary complications (PPCs) in critically ill surgical patients are poorly predicted by current models. The LAS VEGAS score showed the best performance but still had limited accuracy, highlighting the need for better risk prediction tools.

Keywords:

critically ill patients postoperative pulmonary complications predictive accuracy risk prediction models

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Area of Science:

Critical Care Medicine
Surgical Outcomes
Respiratory Physiology

Background:

Postoperative pulmonary complications (PPCs) significantly increase morbidity and mortality in surgical patients, especially the critically ill.
Existing risk prediction models for PPCs lack comparative data in critically ill populations.

Purpose of the Study:

To evaluate and compare the predictive performance of three established risk models for PPCs in critically ill surgical patients.
To identify the most effective model for stratifying PPC risk in this specific patient group.

Main Methods:

A retrospective cohort study of 495 critically ill surgical patients admitted to a tertiary ICU in China.
Assessment of PPCs using the LAS VEGAS, ARISCAT, and CHI-BPRI risk models.
Receiver operating characteristic (ROC) analysis to evaluate predictive performance, including AUC, sensitivity, and specificity.

Main Results:

20.4% of patients developed PPCs.
The LAS VEGAS score demonstrated the highest Area Under the Curve (AUC) at 0.63, with 74% sensitivity and 47% specificity.
None of the models achieved statistically superior discrimination or AUCs above 0.70, indicating suboptimal predictive accuracy.

Conclusions:

Established risk models (LAS VEGAS, ARISCAT, CHI-BPRI) exhibit limited predictive performance for PPCs in critically ill Chinese surgical patients.
The LAS VEGAS score offered the best, albeit modest, utility for early risk identification.
There is a critical need for developing improved, population-specific prediction tools for PPCs in this vulnerable patient cohort.