Association Between Red Blood Cell Distribution Width and Outcomes of Open Airway Reconstruction Surgery in Adults

Airway reconstruction for adults with laryngotracheal stenosis (LTS) is directed toward improving airway caliber to mitigate the patient's dyspnea and achieve prosthesis-free breathing (ie, without tracheostomy, intraluminal stent, or T-tube). Despite the importance of preoperative risk stratification to minimize postoperative complications, consensus on an objective predictive algorithm for open airway reconstruction is lacking.

To determine whether the ability to achieve a prosthesis-free airway in adults after open airway reconstruction is associated with red blood cell distribution width (RDW) at the time of surgery.

Case series study investigating 92 consecutive patients 18 years and older with laryngotracheal stenosis who underwent open airway reconstruction at a US tertiary care hospital from January 1, 2006, to January 1, 2017.

The main outcome was a prosthesis-free airway (absence of tracheostomy, intraluminal stent, or T-tubes) at last follow-up. Multivariate logistic regression modeling was used to identify independent factors associated with this outcome.

Of the 92 patients who met inclusion criteria, the median (interquartile range) age was 44 (33.0-60.3) years; 50 (53%) were female, and 82 (89%) were white. In all, 74 patients (80%) were prosthesis free at the last follow-up (mean, 833 days; 95% CI, 10-4229 days). In multivariate analyses, airway decannulation was significantly correlated with reduced RDW (odds ratio [OR], 0.40; 95% CI, 0.19-0.84) and the absence of posterior glottic stenosis (OR, 0.12; 95% CI, 0.04-0.37).

These data suggest that surgical success in open airway reconstruction is significantly associated with RDW and whether the patient had posterior glottic stenosis. The RDW is a routine laboratory parameter that may provide some insight to the preoperative probability of prosthesis removal, facilitate risk stratification, promote informed patient decision making, and optimize health care resource management.