INTRODUCTION: The term laryngopharyngeal reflux (LPR) is frequently applied to aerodigestive symptoms despite lack of objective reflux evidence. The aim of this initiative was to develop a modern care paradigm for LPR supported by otolaryngology and gastroenterology disciplines. METHODS: A 28-member international interdisciplinary working group developed practical statements within the following domains: definition/terminology, initial diagnostic evaluation, reflux monitoring, therapeutic trials, behavioral factors and therapy, and risk stratification. Literature reviews guided statement development and were presented at virtual/in-person meetings. Each statement underwent 2 or more rounds of voting per the RAND Appropriateness Method; statements reaching appropriateness with ≥80% agreement are included as recommendations. RESULTS: The term laryngopharyngeal symptoms (LPS) applies to aerodigestive symptoms with potential to be induced by reflux and include cough, voice change, throat clearing, excess throat phlegm, and throat pain. Laryngopharyngeal reflux disease (LPRD) refers to patients with LPS and objective evidence of reflux. Importantly, the presence of LPS does not equate to LPRD. Laryngoscopy has value in assessing for nonreflux laryngopharyngeal processes, but laryngoscopic findings alone cannot diagnose LPRD. LPS patients should be categorized as with or without concurrent esophageal reflux symptoms. While lifestyle modification and empiric trials of acid suppression ± alginates are appropriate when esophageal reflux symptoms coexist, upper endoscopy and ambulatory reflux monitoring are required for LPRD diagnosis when symptoms persist, when LPS is isolated, or when management needs to be escalated to include invasive antireflux management. The two recommended ambulatory reflux monitoring modalities, 24-hour pH-impedance and 96-hour wireless pH monitoring, are not mutually exclusive with distinct roles for the evaluation of LPS. Laryngeal hyperresponsiveness and hypervigilance commonly contribute to both LPS and LPRD presentations and are responsive to laryngeal recalibration therapy and neuromodulators. DISCUSSION: The San Diego Consensus represents the formal modern-day interdisciplinary care paradigm to evaluate and manage LPS and LPRD.

Objective: This study aims to develop and validate a convolutional neural network (CNN)‐based algorithm for automatic selection of informative frames in flexible laryngoscopic videos. The classifier has the potential to aid in the development of computer‐aided diagnosis systems and reduce data processing time for clinician‐computer scientist teams.Methods: A dataset of 22,132 laryngoscopic frames was extracted from 137 flexible laryngostroboscopic videos from 115 patients. 55 videos were from healthy patients with no laryngeal pathology and 82 videos were from patients with vocal fold polyps. The extracted frames were manually labeled as informative or uninformative by two independent reviewers based on vocal fold visibility, lighting, focus, and camera distance, resulting in 18,114 informative frames and 4018 uninformative frames. The dataset was split into training and test sets. A pre‐trained ResNet‐18 model was trained using transfer learning to classify frames as informative or uninformative. Hyperparameters were set using cross‐validation. The primary outcome was precision for the informative class and secondary outcomes were precision, recall, and F1‐score for all classes. The processing rate for frames between the model and a human annotator were compared.Results: The automated classifier achieved an informative frame precision, recall, and F1‐score of 94.4%, 90.2%, and 92.3%, respectively, when evaluated on a hold‐out test set of 4438 frames. The model processed frames 16 times faster than a human annotator.Conclusion: The CNN‐based classifier demonstrates high precision for classifying informative frames in flexible laryngostroboscopic videos. This model has the potential to aid researchers with dataset creation for computer‐aided diagnosis systems by automatically extracting relevant frames from laryngoscopic videos.