Acoustic rhinometry and rhinomanometry in the preoperative screening of septal surgery patients

Autor: Jukka Tikanto, Tapio Pirilä
Rok vydání: 2009
Předmět:
Zdroj: American journal of rhinologyallergy. 23(6)
ISSN: 1945-8932
Popis: Background The preoperative assessment of septal surgery patients with acoustic rhinometry (AR) or rhinomanometry (RMM) is still a controversial subject. This study was designed to apply AR and RMM in preoperative screening of septal surgery patients. Methods The gold standard is postoperative satisfaction expressed by patients as “very high,” “high,” “moderate,” or “low” subjective total benefit from the operation to the nasal obstruction 1 year after surgery. One hundred fifty-seven consecutive patients presenting for septal surgery because of an obstructing septum deviation in anterior rhinoscopy, sufficient pre- and postoperative data were available in 110 patients. Anterior rhinoscopy, AR, and RMM were performed before and 1 year after surgery. Results The preoperative AR and RMM had a statistically significant impact (p < 0.01) in predicting the postoperative satisfaction. The best single preoperative parameter for predicting postoperative satisfaction was the postdecongestion overall minimum cross-sectional area on the deviation side in AR; the estimated optimal cutoff value was 0.40 cm2. The most predictive preoperative RMM parameter was the postdecongestion intercavital flow ratio (the flow on the deviation side divided by the flow on the wide side); the estimated optimal cutoff value was 1:2. For both parameters the sensitivity/specificity for the cutoff values was around 65/60% in finding patients with high or very high postoperative satisfaction. For anterior rhinoscopy the optimal cutoff was a deviation between severe and moderate with sensitivity/specificity around 55/55%. Conclusion In patients with a very severe deviation, anterior rhinoscopy was sufficient for preoperative screening but in milder deviations AR and RMM significantly predicted postoperative success.
Databáze: OpenAIRE