Professor and Chair Kaohsiung Chang Gung Memorial Hospital Kaohsiung, Taiwan (Republic of China)
Disclosure(s):
Hsin-Ching Lin, MD, FACS: No relevant relationships to disclose.
Introduction: To identify the possible predictors for OSA (obstructive sleep apnea) patients’ willingness/final treatment via objective anthropometric/anatomic data and/or subjective shared decision-making (SDM) response.
Methods: A retrospective cohort study enrolled 300 consecutive OSA patients (31 females/269 males; mean age, 41.7 years; mean AHI, 45.6/hr.). All of the patients completed a full-night polysomnography and anthropometric measurements including modified Mallampati grade (also known as updated Friedman’s tongue position), body mass index, etc. The OSA patients also completed a qualified 10-item SDM questionnaire and experienced the auto-CPAP. Spearman's correlation was used to determine correlations between covariates. Simple/univariable and multiple logistic regressions with stepwise selection were evaluated the effect of covariates for predicting the final selection with OSA surgery. The performances of logistic regression models were used by the area under the receiver operating characteristic (ROC) curves. P < 0.05 was considered statistical significance.
Results: This analysis was that SDM could use to predict the clinical decision making for patients with OSA (AUC = 62.2%.). If we added the GPA (global patient’s assessment) score (-5 ~ +5) after auto-CPAP trail before the OSA patients made the final decision for selecting OSA surgery as the treatment or not, it did increase the predicting rate. The predicting power can be improved by adding the GPA score after receiving CPAP trail (AUC = 83.0%.).
Conclusions: The study demonstrated that SDM is not only for helping decision making clinically, but also could assist to predict the OSA patients’ final treatment selection.
