Upper airway angle and glottic height: a prospective cohort to evaluate two new features for airway prediction

Abstract Background: Predicting difficult direct laryngoscopies remains challenging and improvements are needed in preoperative airway assessment. We conceived two new tests (the upper airway angle and the glottic height) and assessed their association with difficult direct laryngoscopies as well as their predictive performance. Methods: A prospective cohort was conducted with 211 patients undergoing general anesthesia for surgical procedures. We assessed the association between difficult laryngoscopies and modified Mallampati Test (MMT), Upper Lip Bite Test (ULBT), Mandibular Length (ML), Neck Circumference (NC), Mouth Opening (MO), Sternomental Distance (SMD), Thyromental Distance (TMD), Upper Airway Angle (UAA), and Glottic Height (GH). We also estimated their predictive values. Results: Difficult laryngoscopy was presented by 12 patients (5.7%). Six tests were significantly associated with difficult laryngoscopies and their area under the ROC curve, and 95% CIs were as follows: UAA = 88.82 (81.86-95.78); GH = 86.43 (72.67-100); ML = 83.75 (72.77-94.74); NC = 79.17 (64.98-93.36); MO = 65.58 (45.13-86.02); and MMT = 77.89 (68.37-87.41). Conclusion: We have found two new features (the UAA and the GH) to be significantly associated with the occurrence of difficult direct laryngoscopies. They also presented the best predictive performance amongst the nine evaluated tests in our cohort of patients. We cannot ensure, however, these tests to be superior to other regularly used bedside tests based on our estimated 95% CIs.

Development of Decision Support Formulas for the Prediction of Bladder Outlet Obstruction and Prostatic Surgery in Patients With Lower Urinary Tract Symptom/Benign Prostatic Hyperplasia: Part II, External Validation and Usability Testing of a Smartphone A / 대한배뇨장애요실금학회지

PURPOSE: We aimed to externally validate the prediction model we developed for having bladder outlet obstruction (BOO) and requiring prostatic surgery using 2 independent data sets from tertiary referral centers, and also aimed to validate a mobile app for using this model through usability testing. METHODS: Formulas and nomograms predicting whether a subject has BOO and needs prostatic surgery were validated with an external validation cohort from Seoul National University Bundang Hospital and Seoul Metropolitan Government-Seoul National University Boramae Medical Center between January 2004 and April 2015. A smartphone-based app was developed, and 8 young urologists were enrolled for usability testing to identify any human factor issues of the app. RESULTS: A total of 642 patients were included in the external validation cohort. No significant differences were found in the baseline characteristics of major parameters between the original (n=1,179) and the external validation cohort, except for the maximal flow rate. Predictions of requiring prostatic surgery in the validation cohort showed a sensitivity of 80.6%, a specificity of 73.2%, a positive predictive value of 49.7%, and a negative predictive value of 92.0%, and area under receiver operating curve of 0.84. The calibration plot indicated that the predictions have good correspondence. The decision curve showed also a high net benefit. Similar evaluation results using the external validation cohort were seen in the predictions of having BOO. Overall results of the usability test demonstrated that the app was user-friendly with no major human factor issues. CONCLUSIONS: External validation of these newly developed a prediction model demonstrated a moderate level of discrimination, adequate calibration, and high net benefit gains for predicting both having BOO and requiring prostatic surgery. Also a smartphone app implementing the prediction model was user-friendly with no major human factor issue.