Effects of Early Surgical Exploration in Suspected Barotraumatic Perilymph Fistulas

ObjectivesTreatment of traumatic perilymph fistula (PLF) remains controversial between surgical repair and conservative therapy. The aim of this study is to analyze the outcomes of early surgical exploration in suspected barotraumatic PLF.MethodsNine patients (10 cases) who developed sudden sensorineural hearing loss and dizziness following barotrauma and underwent surgical exploration with the clinical impression of PLF were enrolled. Types of antecedent trauma, operative findings, control of dizziness after surgery, postoperative hearing outcomes, and relations to the time interval between traumatic event and surgery were assessed retrospectively.ResultsAll patients had sudden or progressive hearing loss and dizziness following trauma. Types of barotrauma were classified by the origin of the trauma: 4 external (car accident, slap injury) and 6 internal traumas (lifting, nasal blowing, straining). Surgical exploration was performed whenever PLF was suspected with the time interval of 2 to 47 days after the trauma. The possible evidence of PLF was found during surgery in 9 cases: a fibrous web around the oval window (n=3), fluid collection in the round window (RW; n=6) and bulging of the RW pseudomembrane (n=1). In every patient, vestibular symptoms disappeared immediately after surgery. The hearing was improved with a mean gain of 27.0±14.9 dB. When the surgical exploration was performed as early as less than 10 days after the trauma, serviceable hearing (≤40 dB) was obtained in 4 out of 7 cases (57.1%).ConclusionSudden or progressive sensorineural hearing loss accompanied by dizziness following barotrauma should prompt consideration of PLF. Early surgical exploration is recommended to improve hearing and vestibular symptoms

A New Bloom Filter Architecture for FIB Lookup in Named Data Networking

Network traffic has increased rapidly in recent years, mainly associated with the massive growth of various applications on mobile devices. Named data networking (NDN) technology has been proposed as a future Internet architecture for effectively handling this ever-increasing network traffic. In order to realize the NDN, high-speed lookup algorithms for a forwarding information base (FIB) are crucial. This paper proposes a level-priority trie (LPT) and a 2-phase Bloom filter architecture implementing the LPT. The proposed Bloom filters are sufficiently small to be implemented with on-chip memories (less than 3 MB) for FIB tables with up to 100,000 name prefixes. Hence, the proposed structure enables high-speed FIB lookup. The performance evaluation result shows that FIB lookups for more than 99.99% of inputs are achieved without needing to access the database stored in an off-chip memory

Effects of Scrambler Therapy in Patients with Failed Back Surgery Syndromes and Factors Associated with Depression Affecting Pain before and after the Therapy

Objectives. To report the effects of scrambler therapy in patients diagnosed with failed back surgery syndromes and to analyze the factors affecting pain before and after the therapy. Methods. This study included 26 patients (12 males and 14 females). The Oswestry Disability Index (ODI) and Brief Pain Inventory (BPI) before and after scrambler therapy, Beck Depression Inventory (BDI) score before therapy, and residual pain after therapy were assessed. The changes in the ODI, BPI, and residual pain before and after the therapy were analyzed using the Wilcoxon signed rank test. Spearman correlation analysis and Fisher’s exact test were used to confirm the correlation between BDI and other factors. Multiple regression analysis was used to identify independent factors predicting residual pain, posttherapy ODI, and posttherapy BPI. Results. The ODI changed from 25.69 ± 7.98 to 21.80 ± 9.41 (p<0.05), and the BPI changed from 68.96 ± 18.00 to 61.62 ± 20.27 after scrambler therapy (p<0.05). In addition, residual pain changed from 100 to 76.15 (p<0.05). The BDI was negatively correlated with the duration of scrambler therapy and positively correlated with the initial OPD and BPI. In multiple regression analysis, residual pain was significantly correlated with the BDI (p<0.05). Conclusion. Scrambler therapy can be used to change the total scores of the ODI and BPI after 5 sessions of treatment. Also, residual pain was significantly related to the BDI. Clinical significance of depression severity on pain should be further investigated via prospective studies

Feasibility of the Machine Learning Network to Diagnose Tympanic Membrane Lesions without Coding Experience

A machine learning platform operated without coding knowledge (Teachable machine&reg;) has been introduced. The aims of the present study were to assess the performance of the Teachable machine&reg; for diagnosing tympanic membrane lesions. A total of 3024 tympanic membrane images were used to train and validate the diagnostic performance of the network. Tympanic membrane images were labeled as normal, otitis media with effusion (OME), chronic otitis media (COM), and cholesteatoma. According to the complexity of the categorization, Level I refers to normal versus abnormal tympanic membrane; Level II was defined as normal, OME, or COM + cholesteatoma; and Level III distinguishes between all four pathologies. In addition, eighty representative test images were used to assess the performance. Teachable machine&reg; automatically creates a classification network and presents diagnostic performance when images are uploaded. The mean accuracy of the Teachable machine&reg; for classifying tympanic membranes as normal or abnormal (Level I) was 90.1%. For Level II, the mean accuracy was 89.0% and for Level III it was 86.2%. The overall accuracy of the classification of the 80 representative tympanic membrane images was 78.75%, and the hit rates for normal, OME, COM, and cholesteatoma were 95.0%, 70.0%, 90.0%, and 60.0%, respectively. Teachable machine&reg; could successfully generate the diagnostic network for classifying tympanic membrane

Possible Existence of Cochlear Synaptopathy in Patients Completely Recovered from Idiopathic Sudden Sensorineural Hearing Loss

Cochlear synaptopathy refers to a subclinical hearing pathology which could potentially explain hearing difficulties within the normal hearing threshold; it is also called &ldquo;hidden hearing loss&rdquo;. We hypothesized that a temporary threshold shift in sudden sensorineural hearing loss (ISSNHL) also affects the function in the synapse. The aim of the study was to evaluate the presence of cochlear synaptopathy in patients who had completely recovered from unilateral SSNHL Nineteen patients who had completely recovered from ISSNHL from January 2018 to June 2021 were assessed. Complete recovery was established by pure tone audiometry (PTA) 3 months after treatment, according to the American Academy of Otolaryngology&ndash;Head and Neck Surgery criteria. Subjects completed the pure tone audiometry, speech audiometry and auditory brain stem response (ABR) test, and completed a questionnaire regarding hearing loss after hearing recovery. The ABR amplitudes of wave I and wave V, and the ratio of wave I/V of both ears (recovered side and healthy side) were assessed. A visual analog scale (VAS) and a hidden hearing loss questionnaire were used to evaluate subjective hearing difficulty. The ABR waves I of the recovered ears had a significantly lower amplitude (p = 0.002) than those of the healthy side, whereas there was no difference in wave V (p = 0.985) or in the ratio of wave I/V (p = 0.107). Some patients still felt mild hearing difficulty although their PTA results were normal, but there was no clear relationship between the VAS score, wave I amplitude and speech recognition scores. The present findings point to the possible existence of cochlear synaptopathy in ears that have completely recovered from unilateral sudden sensorineural hearing loss. We suggest that the causes of cochlear synaptopathy and of idiopathic sudden hearing loss may have something in common

A content analysis of YouTube videos on tinnitus in South Korea

Abstract More people use the internet for medical information, especially YouTube. Nevertheless, no study has been conducted to analyze the quality of YouTube videos about tinnitus in Korea. This study aims to review the contents and quality of YouTube videos on tinnitus. The top 100 Korean YouTube videos on tinnitus were reviewed by a tinnitus expert. This study assessed video details: title, creator, length, and popularity indicators—subscribers, views, and likes. The contents of the video clips were analyzed to determine the relevance, understandability, actionability, and quality of information. Out of 100 tinnitus videos, 27 were created by otolaryngologists, 25 by traditional Korean medicine doctors, 25 by other medical professionals, and 3 by lay persons. Sensorineural tinnitus was frequently dealt, and hearing loss, stress, and noise were introduced as main causes of tinnitus. Otolaryngologists' videos covered verified treatments, but others suggested unproven therapies including herbal medicine or acupressure. Otolaryngologists' videos showed significantly higher understandability and quality of information compared to others (p < 0.001). This study found that tinnitus YouTube videos frequently present low-quality and incorrect material, which could have an adverse effect on patients. Results highlight the need for tinnitus specialists to provide accurate information

An Assistive Role of a Machine Learning Network in Diagnosis of Middle Ear Diseases

The present study aimed to develop a machine learning network to diagnose middle ear diseases with tympanic membrane images and to identify its assistive role in the diagnostic process. The medical records of subjects who underwent ear endoscopy tests were reviewed. From these records, 2272 diagnostic tympanic membranes images were appropriately labeled as normal, otitis media with effusion (OME), chronic otitis media (COM), or cholesteatoma and were used for training. We developed the “ResNet18 + Shuffle” network and validated the model performance. Seventy-one representative cases were selected to test the final accuracy of the network and resident physicians. We asked 10 resident physicians to make diagnoses from tympanic membrane images with and without the help of the machine learning network, and the change of the diagnostic performance of resident physicians with the aid of the answers from the machine learning network was assessed. The devised network showed a highest accuracy of 97.18%. A five-fold validation showed that the network successfully diagnosed ear diseases with an accuracy greater than 93%. All resident physicians were able to diagnose middle ear diseases more accurately with the help of the machine learning network. The increase in diagnostic accuracy was up to 18% (1.4% to 18.4%). The machine learning network successfully classified middle ear diseases and was assistive to clinicians in the interpretation of tympanic membrane images