A clinically useful nomogram integrating bedside lung ultrasound and clinical parameters for pulmonary complications after non-thoracic surgery in blunt chest trauma patients.

OBJECTIVES

Lung ultrasonography can be used to effectively evaluate the severity of pulmonary injury. This study aimed to develop a nomogram that incorporated the results of lung ultrasonography and traditional clinical parameters to predict postoperative pulmonary complications (PPCs) in patients with blunt chest trauma who underwent non-thoracic surgery.

DESIGN

Prospective, observational study.

SETTING

The study was performed in a first 3A-grade hospitals in China.

PARTICIPANTS

This study included 374 patients with blunt chest trauma who underwent extremity or pelvic fracture surgery.

INTERVENTIONS: All patients underwent lung ultrasonography before surgery and received general anesthesia combined with a regional block, goal-directed fluid therapy, and lung-protective ventilation. 30-days postoperatively, all participants were followed up to assess PPCs. Logistic regression was used to identify the key predictors of PPCs, and a nomogram was constructed. The predictive efficacy of the model was evaluated using receiver operating characteristic (ROC) and calibration curves, and the clinical application value was evaluated using decision curve analysis (DCA).

RESULTS

PPC incidence was 26.73%. American Society of Anesthesiologists physical status class, chronic obstructive pulmonary disease, recent respiratory infection, pneumothorax, lung ultrasonography score, and number of rib fractures were incorporated into the nomogram. The nomogram exhibited an excellent discriminative ability, with an area under the ROC curve of 0.932. The DCA demonstrated significant clinical utility of this nomogram in predicting PPCs.

CONCLUSION

We developed a nomogram that combined the results of lung ultrasonography and traditional clinical parameters to predict the risk of PPCs in patients with blunt chest trauma who underwent non-thoracic surgery. This validation revealed satisfactory discrimination, indicating its potential clinical utility. This may assist in clinical decision-making.