Background: Tinnitus diagnosis poses a challenge in otolaryngology owing to an extremely complex pathogenesis, lack of effective objectification methods, and factor-affected diagnosis. There is currently a lack of explainable auxiliary diagnostic tools for tinnitus in clinical practice. Objective: This study aims to develop a diagnostic model using an explainable artificial intelligence (AI) method to address the issue of low accuracy in tinnitus diagnosis. Methods: In this study, a knowledge graph–based tinnitus diagnostic method was developed by combining clinical medical knowledge with electronic medical records. Electronic medical record data from 1267 patients were integrated with traditional Chinese clinical medical knowledge to construct a tinnitus knowledge graph. Subsequently, weights were introduced, which measured patient similarity in the knowledge graph based on mutual information values. Finally, a collaborative neighbor algorithm was proposed, which scored patient similarity to obtain the recommended diagnosis. We conducted 2 group experiments and 1 case derivation to explore the effectiveness of our models and compared the models with state-of-the-art graph algorithms and other explainable machine learning models. Results: The experimental results indicate that the method achieved 99.4% accuracy, 98.5% sensitivity, 99.6% specificity, 98.7% precision, 98.6% F1-score, and 99% area under the receiver operating characteristic curve for the inference of 5 tinnitus subtypes among 253 test patients. Additionally, it demonstrated good interpretability. The topological structure of knowledge graphs provides transparency that can explain the reasons for the similarity between patients. Conclusions: This method provides doctors with a reliable and explainable diagnostic tool that is expected to improve tinnitus diagnosis accuracy.

Objective: This study aimed to understand the demographics, clinical characteristics, and psychoacoustic status of subjective tinnitus patients to explore the factors associated with acute and chronic tinnitus in the general hospitals of Shanghai.Methods: A cross‐sectional study was conducted to investigate the clinical characteristics and psychoacoustic status of subjective tinnitus patients with history greater than 1 month. Data were collected during January 2021 and January 2022 from eight general hospitals in five districts of Shanghai, China. All patients accepted questionnaires and acoustic examination, then SPSS 22.0 and GraphPad Prism 8.0.2 were applied for data analysis.Results: Among the 359 tinnitus patients, 126 cases were diagnosed with acute tinnitus, 58 cases were subacute tinnitus, and 175 cases were chronic tinnitus. Patients with acute and chronic tinnitus differed in terms of side of tinnitus, hearing loss, frequency of tinnitus, severity of tinnitus, anxiety, depression, and sleep status. Different characteristics were included in the multivariate ordinal logistic regression analysis. Persistent tinnitus (OR = 2.00, p = .008), high frequency hearing loss (OR = 4.77, p < .001), depression (OR = 1.23, p < .001) were found to be positively associated with the course of tinnitus. Unilateral tinnitus (OR = 0.48, p = .003), mild (OR = 0.29, p = .001) and moderate (OR = 0.46, p = .038) hearing loss, VAS scores (OR = 0.82, p = .032), anxiety (OR = 0.81, p < .001), THI scores (OR = 0.98, p = .002), and sleep disorders (OR = 0.94, p = .025) were found to be negatively associated with the course of tinnitus.Conclusion: Patients with acute tinnitus were at greater risk for anxiety, sleep disturbances, and exacerbation of tinnitus perception, and those with chronic tinnitus were at greater risk for depression.Lay Summary: Our study demonstrated that patients with acute tinnitus were at greater risk for anxiety, sleep disturbances, and exacerbation of tinnitus perception, and those with chronic tinnitus were at greater risk for depression.

Objective: To provide evidence for medical management of tinnitus based on an assessment of the evidence concerning the effectiveness of acupuncture as a treatment for tinnitus using network meta-analysis (NMA). Methods: We conducted a systematic literature review by searching 8 national and international databases (inception to February 2023) for randomized controlled trials (RCTs) for tinnitus. Only RCTs that recruited participants aged over 18 and diagnosed with tinnitus, and that evaluated acupuncture or acupuncture in combination with conventional western medical therapy were included. We used response rate and tinnitus handicap inventory (THI) to examine efficacy. We conducted NMA with random effects, and the rate ratio or mean difference with its 95% credible interval was calculated. In addition, we ranked all treatments via their SUCRA and assessed the quality of evidence according to the GRADE criteria. Results: A total of 2575 patients were included in the study. The main findings of the current NMA were that acupoint injection combined with warm acupuncture was the most effective for response rate, followed by warm acupuncture and acupoint injection combined with western medical treatment. Acupuncture combined with western medical treatment was the most effective for THI, followed by electroacupuncture combined with warm acupuncture and acupuncture combined with moxibustion. Conclusion: Acupuncture seems to be a better trend treatment for tinnitus. Further rigorous RCT studies that include direct comparisons for different acupuncture-related treatments are encouraged to provide the most promising evidence for patients with tinnitus. Protocol registration: CRD42023398745.

Tinnitus is a common disease, its pathogenesis and etiology are very complex, and the exact cause of the disease has not yet been determined. However, there are still difficulties in the treatment of tinnitus. This meta-analysis was conducted to evaluate the effectiveness of cognitive behavioral therapy in the treatment of patients in otolaryngology-head and neck surgery with tinnitus. The study was registered on the PROSPERO website (registration number: CRD42024496003). Of the 211 articles reviewed, 26 high-quality studies were included, and 7 articles were supplemented from previous meta-analyses. These studies focused on cognitive behavioral therapy for the treatment of Tinnitus Questionnaire (TQ), Tinnitus Handicap Inventory (THI), Hospital Anxiety Depression Scale (HADS, A-anxiety, D-depression), Insomnia Severity Index (ISI), Tinnitus Reaction Questionnaire (TRQ), and Visual Analogue Scale (VAS) in patients with tinnitus. Compared with other treatments, patients with tinnitus received cognitive behavioral therapy and had significantly lower TQ, THI, HADS, ISI, TRQ, and VAS scores. In the review of the conclusions: cognitive behavioral therapy is expected to reduce the auditory psychological indicators of tinnitus, reduce the impact of tinnitus on patients' lives, improve the anxiety and depression state of tinnitus patients, and improve the sleep state of tinnitus patients. These findings suggest that cognitive behavioral therapy is an effective treatment to improve tinnitus symptoms, and that cognitive behavioral therapy can significantly improve the anxiety and depression state and sleep state of patients with tinnitus, and cognitive behavioral therapy may improve the symptoms of tinnitus from a psychological perspective by improving the anxiety and depression state and sleep state of patients. Research data supporting this publication are available from the NN repository at located at https://www.crd.york.ac.uk/PROSPERO/recorddashboard. The meta-analysis process was documented in the supplementary documents.

This study aimed to explore the potential causal relationship between migraine and cochlear disease by using a bidirectional Mendelian randomization (MR) approach. We searched datasets related to migraine in the FinnGen database and genome-wide association studies catalog. We conducted 2-sample MR analyses. Instrumental variables were selected based on stringent criteria, including genome-wide significance, clumping to ensure independence, and exclusion of palindromic single nucleotide polymorphisms and those associated with confounders. The primary MR analysis employed the inverse-variance weighted (IVW) method supplemented by sensitivity analyses using the Weighted Median and MR-Egger (MR-Egger) methods to address potential pleiotropy. MR analyses suggested a causal relationship between migraine and increased risk of cochlear disease. MR analyses suggested that migraine was associated with an increase in tinnitus (IVWMR odds ratio (OR) = 1.516, 95% confidence interval (CI): 1.064–2.159, P = .021). Migraine was also associated with an increase in vertigo (IVW MR OR = 1.631, 95% CI: 1.003–2.651, P = .049). Medication use (antimigraine preparations) was associated with an increase in sudden idiopathic hearing loss (IVW MR OR = 1.187, 95% CI: 1.023–1.378, P = .024). Medication use (antimigraine preparations) was also associated with an increase in other hearing loss (IVW MR OR = 1.085, 95% CI: 1.007–1.169, P = .032). Migraine with no aura triptan was associated with an increase in tinnitus (IVW MR OR = 1.226, 95% CI: 1.075–1.398, P = .002). These findings were robust across various sensitivity analyses, including MR-Egger and MR Pleiotropy RESidual Sum and Outlier, supporting the absence of pleiotropy and outliers. Our results establish a causal link between migraine and cochlear disease, indicating that migraine may exacerbate cochlear disease. Additionally, these findings strengthen the evidence-based medical foundation of the relationship between migraines and cochlear disease. They offer theoretical support for future migraine aimed at treating cochlear disease.

This study investigates the potential causal relationships among immune cells, plasma liposomes, and plasma metabolites in allergic rhinitis (AR) using a two-sample bidirectional multivariate and mediated Mendelian Randomization (MR) approach. Genetic data from five GWAS datasets covering traits linked to immune cells, plasma liposomes, plasma metabolites, and AR were used. Instrumental variables were selected based on strict criteria to ensure independence and exclude confounders. The primary MR analysis employed the Inverse Variance Weighted method, supplemented by sensitivity analyses using the Weighted Median and MR-Egger methods. The MR analyses suggest a genetic correlation among immune cells, plasma liposomes, and plasma metabolites, influencing the risk of AR. Findings were robust across various sensitivity analyses, supporting the absence of pleiotropy and outliers. No reverse causality was found, indicating a unidirectional influence. Genetic predispositions to immune cells, plasma liposomes, and plasma metabolites significantly change the risk of developing AR. Further studies are needed to explore these associations in diverse populations and refine the underlying mechanisms.