Objectives: To investigate the psychometric properties of the reflux symptom index (RSI) as short screening approach for the diagnostic of laryngopharyngeal reflux (LPR) in patients with confirmed diagnosed regarding the 24-hour multichannel intraluminal impedance-pH monitoring (MII-pH). Methods: From January 2017 to December 2018, 56 patients with LPR symptoms and 71 healthy individuals (control group) were prospectively enrolled. The LPR diagnosis was confirmed through MII-pH results. All subjects (n = 127) fulfilled RSI and the Reflux Finding Score (RFS) was performed through flexible fiberoptic endoscopy. The sensitivity and the specificity of RSI was assessed by ROC (Receiver Operating Characteristic) analysis. Results: A total of 15 LPR patients (26.8%) of the clinical group met MII-pH diagnostic criteria. Among subjects classified as positive for MII- pH diagnoses, RSI and RFS mean scores were respectively 20 (SD ± 10.5) and 7.1 (SD ± 2.5), values not significantly different compared to the negative MII-pH group. The metric analysis of the items led to the realization of a binary recoding of the score. Both versions had similar psychometric properties, α was 0.840 for RSI original version and 0.836 for RSI binary version. High and comparable area under curve (AUC) values indicate a good ability of both scales to discriminate between individuals with and without LPR pathology diagnosis. Based on balanced sensitivity and specificity, the optimal cut-off scores for LPR pathology were ≥ 5 for RSI binary version and ≥ 15 for RSI original version. Both version overestimated LPR prevalence. The original version had more sensitivity and the RSI Binary version had more specificity. Conclusions: It would be necessary to think about modifying the original RSI in order to improve its sensitivity and specificity (RSI binary version, adding or changing some items), or to introduce new scores in order to better frame the probably affected of LPR patient.
|Titolo:||Assessment and Diagnostic Accuracy Evaluation of the Reflux Symptom Index (RSI) Scale: Psychometric Properties using Optimal Scaling Techniques|
BARILLARI, Maria Rosaria [Writing – Review & Editing]
|Data di pubblicazione:||2020|
|Appare nelle tipologie:||1.1 Articolo in rivista|