z-logo
open-access-imgOpen Access
Predictive models of objective oropharyngeal OSA surgery outcomes: Success rate and AHI reduction ratio
Author(s) -
Ji Ho Choi,
Jae Yong Lee,
Jaehyung Cha,
Kangwoo Kim,
Seung No Hong,
Jun Young Lee
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0185201
Subject(s) - medicine , stepwise regression , obstructive sleep apnea , logistic regression , tonsil , polysomnography , confidence interval , surgery , retrospective cohort study , apnea
Objective The aim of this study was to develop a predictive model of objective oropharyngeal obstructive sleep apnea (OSA) surgery outcomes including success rate and apnea-hypopnea index (AHI) reduction ratio in adult OSA patients. Study design Retrospective outcome research. Methods All subjects with OSA who underwent oropharyngeal and/or nasal surgery and were followed for at least 3 months were enrolled in this study. Demographic, anatomical [tonsil size (TS) and palate-tongue position (PTP) grade (Gr)], and polysomnographic parameters were analyzed. The AHI reduction ratio (%) was defined as [(postoperative AHI—preoperative AHI) x 100 / postoperative AHI], and surgical success was defined as a ≥ 50% reduction in preoperative AHI with a postoperative AHI < 20. Results A total of 156 consecutive OSAS adult patients (mean age ± SD = 38.9 ± 9.6, M / F = 149 / 7) were included in this study. The best predictive equation by Forward Selection likelihood ratio (LR) logistic regression analysis was:ln (P x1 − P x) = 1 . 518 − 0 . 039 × Age + 1 . 392 × TS Gr − 0 . 803 × PTP GrThe best predictive equation according to stepwise multiple linear regression analysis was:AHI reduction ratio = − 39 . 464 + ( 32 . 752 × TS Gr ) + ( 2 . 623 × AHI ) − ( 2 . 542 × Arousal index )+ [ 1 . 245 × Minimum Sa O 2 ( % ) ] − [ 0 . 599 × Snoring ( % ) ](TS/PTP Gr = 1 if TS/PTP Gr 3 or 4, TS/PTP Gr = 0 if TS/PTP Gr 1 or 2) Conclusion The predictive models for oropharyngeal surgery described in this study may be useful for planning surgical treatments and improving objective outcomes in adult OSA patients.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here