Importance: 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.
Objective: 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.
Design, setting, and participants: 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.
Main outcomes and measures: 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.
Results: 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).
Conclusions and relevance: 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.