Risk factors analysis and prediction model construction of LRTI in head and neck cancer patients with tracheostomy based on subglottic sputum aspiration volume.

OBJECTIVE

Most head and neck cancer (HNC) patients had postoperative aspiration and even lower respiratory tract infections (LRTI). This study aimed to investigate the association between subglottic sputum aspiration volume (SSAV) and the onset of LRTI in HNC patients with tracheostomy. We further sought to identify independent risk factors and construct a predictive model for postoperative LRTI in this patient population.

METHODS

This study retrospectively enrolled 235 HNC patients with intraoperative tracheotomy from June 2018 to November 2022. Subglottic sputum aspiration volume (SSAV) and other clinical data were collected. Univariate and multivariable analyses were performed to construct a logistic regression model. According to the model, a Nomogram was created to visualize the risk of LRTI, and another 66 patients from March 2023 to May 2023 were recruited to validate the prediction model.

RESULTS

The univariate analysis showed that preoperative head and neck surgery history, WBC, PCT, CRP, tumor T stage, tumor N stage, and the SSAV changes had significantly positive relationships with postoperative LRTI. PCT, CRP, tumor T stage, SSAV Range, SSAV Max, and SSAV Min were demonstrated to be independent risk factors. Pathogen analysis revealed that the microbiota of the lower respiratory tract infection was Pseudomonas aeruginosa, Staphylococcus aureus, and Acinetobacter baumannii complex group. Model validation analysis showed that the model fit well with the actual situation (AUC = 87.9%, 95%CI:0.767-0.992).

CONCLUSION

SSAV is an unneglectable and meaningful clinical parameter, and the changes in SSAV can predict the risk of LRTI in patients with intraoperative tracheotomy. A new prediction model is satisfactory in predicting LRTI after intraoperative tracheotomy.