Prognosis of Idiopathic Sudden Sensorineural Hearing Loss: The Nomogram Perspective

Predicting Sudden Sensorineural Hearing Loss Recovery with Patient-Personalized Seigel's Criteria Using Machine Learning

BACKGROUND

Accurate prognostic prediction is crucial for managing Idiopathic Sudden Sensorineural Hearing Loss (ISSHL). Previous studies developing ISSHL prognosis models often overlooked individual variability in hearing damage by relying on fixed frequency domains. This study aims to develop models predicting ISSHL prognosis one month after treatment, focusing on patient-specific hearing impairments.

METHODS

Patient-Personalized Seigel's Criteria (PPSC) were developed considering patient-specific hearing impairment related to ISSHL criteria. We performed a statistical test to assess the shift in the recovery assessment when applying PPSC. The utilized dataset of 581 patients comprised demographic information, health records, laboratory testing, onset and treatment, and hearing levels. To reduce the model's reliance on hearing level features, we used only the averages of hearing levels of the impaired frequencies. Then, model development, evaluation, and interpretation proceeded.

RESULTS

The chi-square test (p-value: 0.106) indicated that the shift in recovery assessment is not statistically significant. The soft-voting ensemble model was most effective, achieving an Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.864 (95% CI: 0.801-0.927), with model interpretation based on the SHapley Additive exPlanations value.

CONCLUSIONS

With PPSC, providing a hearing assessment comparable to traditional Seigel's criteria, the developed models successfully predicted ISSHL recovery one month post-treatment by considering patient-specific impairments.

Nomogram for prediction of hearing rehabilitation outcome in children with congenital sensorineural hearing loss after cochlear implantation

Background

Reliable predictors for rehabilitation outcomes in patients with congenital sensorineural hearing loss (CSNHL) after cochlear implantation (CI) are lacking. The purchase of this study was to develop a nomogram based on clinical characteristics and neuroimaging features to predict the outcome in children with CSNHL after CI.

Methods

Children with CSNHL prior to CI surgery and children with normal hearing were enrolled into the study. Clinical data, high resolution computed tomography (HRCT) for ototemporal bone, conventional brain MRI for structural analysis and brain resting-state fMRI (rs-fMRI) for the power spectrum assessment were assessed. A nomogram combining both clinical and imaging data was constructed using multivariate logistic regression analysis. Model performance was evaluated and validated using bootstrap resampling.

Results

The final cohort consisted of 72 children with CSNHL (41 children with poor outcome and 31 children with good outcome) and 32 healthy controls. The white matter lesion from structural assessment and six power spectrum parameters from rs-fMRI, including Power4, Power13, Power14, Power19, Power23 and Power25 were used to build the nomogram. The area under the receiver operating characteristic (ROC) curve of the nomogram obtained using the bootstrapping method was 0.812 (95 % CI = 0.772-0.836). The calibration curve showed no statistical difference between the predicted value and the actual value, indicating a robust performance of the nomogram. The clinical decision analysis curve showed a high clinical value of this model.

Conclusions

The nomogram constructed with clinical data, and neuroimaging features encompassing ototemporal bone measurements, white matter lesion values from structural brain MRI and power spectrum data from rs-fMRI showed a robust performance in predicting outcome of hearing rehabilitation in children with CSNHL after CI.

Assessing the Effectiveness of Different Hyperbaric Oxygen Treatment Methods in Patients with Sudden Sensorineural Hearing Loss

INTRODUCTION

Hyperbaric oxygen therapy (HBOT) is one of the treatment methods in patients with sudden sensorineural hearing loss (SSNHL). It is recommended as an elective treatment in patients undergoing steroid therapy. According to current scientific reports, HBOT should be implemented within two weeks after the first symptoms. However, as far as the profile of HBOT is concerned, there are no straightforward recommendations.

METHODS

The data obtained from the medical records of 218 patients undergoing HBOT for SSNHL at the Military Institute of Medicine-National Research Institute were analyzed statistically for the impact of the duration and the delay in implementing HBOT on the end results of pure-tone audiometry (PTA).

RESULTS

A statistically significant hearing improvement in patients undergoing more than 15 cycles of HBOT was detected at all frequencies except for 1500 Hz; in the group reporting for treatment with a delay of more than 10 days, hearing improvement was statistically unsignificant at frequencies of 1500, 3000, and 4000 Hz.

CONCLUSIONS

The statistical analysis showed that the urgent onset of HBOT could be a significant factor in the therapy of SSNHL.

Machine Learning Models for Predicting Sudden Sensorineural Hearing Loss Outcome: A Systematic Review

BACKGROUND

Machine Learning models have been applied in various healthcare fields, including Audiology, to predict disease outcomes. The prognosis of sudden sensorineural hearing loss is difficult to predict due to the variable course of the disease. Hence, researchers have attempted to utilize ML models to predict the outcome of patients with sudden sensorineural hearing loss. The objectives of this study were to review the performance of these machine learning models and assess their applicability in real-world settings.

METHODS

A systematic search was conducted in PubMed, Web of Science and Scopus. Only studies that built machine learning prediction models were included, and studies that used algorithms such as logistic regression only for the purpose of adjusting for confounding variables were excluded. The risk of bias was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST).

RESULTS

After screening, a total of 7 papers were eligible for synthesis. In total, these studies built 48 ML models. The most common utilized algorithms were Logistic Regression, Support Vector Machine (SVM) and boosting. The area under the curve of the receiver operating characteristic curve ranged between 0.59 and 0.915. All of the included studies had a high risk of bias; hence there are concerns regarding their applicability.

CONCLUSION

Although these models showed great performance and promising results, future studies are still needed before these models can be applied in a real-world setting. Future studies should employ multiple cohorts, different feature selection methods, and external validation to further validate the models' applicability.

Predictive Model for Prognosis of Sudden Sensorineural Hearing Loss by Nomogram

Objective: To explore the prognostic factors of patients with sudden sensorineural hearing loss (SSNHL), analyze the possible influencing factors, and construct a nomogram for personalized evaluation of their prognosis. Methods: A retrospective study was conducted on 269 patients with SSNHL. The prognostic factors were analyzed by univariate analysis and multivariate logistic regression analysis. The nomogram was constructed based on the results of multivariate logistic regression analysis, and the model was verified by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: Among the 269 patients hospitalized, 136 cases were improved (44 cases were cured, 28 cases were markedly effective, 64 cases were effective) and 133 cases were ineffective. After univariate analysis, it was found that age, duration from onset to treatment, audiometric configuration, serum albumin (ALB), and neutrophil-to-lymphocyte ratio (NLR) were associated with hearing outcomes. Duration from onset to treatment and audiometric configuration were independent risk factors when the treatment outcome was divided into ineffective, effective, significant improvement, and complete recovery groups or divided into improvement and ineffective groups after multivariate logistic regression analysis. The factors according to univariate analysis and multivariate logistic regression analysis results were included in the nomogram to construct the prediction models. The area under the ROC curve of model discrimination was 0.752 [95% confidence interval (CI): 0.695-0.808] when the treatment outcome was divided into 2 groups. The calibration curve showed the consistency of the results, and the DCA prediction curve showed good clinical efficacy. The C-index was 0.756 (95% CI: 0.710-0.802) when the treatment outcome was divided into 4 groups. Conclusion: Age, duration from onset to treatment, audiometric configuration, ALB, and NLR are influencing factors for SSNHL. Duration from onset to treatment and audiometric configuration are independent risk factors for SSNHL. The nomogram presents the prognosis of patients with SSNHL in an intuitive, visual, and readable graph, providing clinicians with a personalized assessment.

Salvage therapy for refractory sudden sensorineural hearing loss (RSSNHL): a systematic review and network meta-analysis

OBJECTIVE

Approximately 30-50% of sudden sensorineural hearing loss (SSNHL) patients show poor response to systemic steroid therapy. Additionally, the most appropriate treatment for patients with refractory sudden sensorineural hearing loss (RSSNHL) is unknown. This study aimed to explore the best treatment for RSSNHL.

DESIGN

Using a frequentist contrast-based model and PRISMA guidelines, this study compared five salvage regimes: intratympanic injection of steroids (ITS), hyperbaric oxygen (HBO) therapy, post auricle steroid injection (PSI), ITS combined with HBO therapy, and continued systemic steroids.

STUDY SAMPLE

We searched the PubMed, EMBASE, Web of Science, and Cochrane Library databases for randomised controlled trials and cohort studies comparing treatment regimens for RSSNHL.

RESULTS

Compared with the control group (no additional treatment), PSI and ITS demonstrated significant improvements. The mean hearing gain was greater after PSI (11.1 dB [95% CI, 4.4-17.9]) than after ITS (7.7 dB [95% CI, 4.8-10.7]). When a restricted definition of RSSNHL was used, the ITS + HBO therapy showed the largest difference in improvement for pure tone average compared with the control group (14.5 dB [95% CI, 4.2-25.0]).

CONCLUSIONS

The administration of either PSI or ITS leads to the greatest therapeutic effect in patients with RSSNHL. However, a consensus on the definition of RSSNHL is needed.

The potential relationship between uric acid and the recovery in sudden sensorineural hearing loss

OBJECTIVE

Serum uric acid is proven to be associated with chronic hearing loss, but its effect on Sudden Sensorineural Hearing Loss (SSNHL) is unclear. This study aims to evaluate the prognostic values of serum uric acid levels in SSNHL patients.

METHODS

The clinical records of SSNHL patients were retrospectively reviewed. Patients were divided into different groups based on hearing recovery and audiogram type, and uric acid levels were compared. Based on uric acid levels, patients were categorized into normouricemia and hyperuricemia groups, and clinical features and hearing recovery were evaluated. Univariate and multivariate analyses were performed to identify prognostic factors.

RESULTS

In total, 520 SSNHL patients were included in this study, including 226 females and 294 males. In female patients, 186 patients were included in the normouricemia group, and 40 patients were enrolled in the hyperuricemia group. Significant differences were observed in uric acid levels, Total Cholesterol (TC), rate of complete recovery, and slight recovery between the two groups. In male patients, 237 subjects were categorized into the normouricemia group, and 57 patients were included in the hyperuricemia group. The rate of complete recovery and slight recovery was lower in the hyperuricemia group compared to the normouricemia group. All patients were further divided into good recovery and poor recovery groups based on hearing outcomes. The uric acid levels, initial hearing threshold, rate of hyperuricemia, and TC were lower in the good recovery group than the poor recovery group both in female and male patients. Binary logistic regression results showed that uric acid levels, initial hearing threshold, and hyperuricemia were associated with hearing recovery.

CONCLUSION

Hyperuricemia might be an independent risk factor for hearing recovery in SSNHL patients. Serum uric acid and initial hearing threshold possibly affected the hearing outcome in males and females with SSNHL.

LEVEL OF EVIDENCE

Level 4.

The prognostic value of peripheral blood parameters on all-frequency sudden sensorineural hearing loss

OBJECTIVE

To determine whether peripheral blood parameters have any predictive value for all-frequency Sudden Sensorineural Hearing Loss (SSNHL).

METHODS

We chose 78 individuals with all-frequency SSNHL who had been admitted to our department. They were divided into two groups: the effective group and the ineffective group. In patients with all-frequency SSNHL, the prognostic variables, including peripheral blood tests and clinical traits, were examined by a logistic regression analysis. In addition, the predictive value was carried out.

RESULTS

The effective rate of all-frequency SSNHL was 61.5%. Pre-treatment hearing level and the proportion of patients with diabetes were both significantly lower in the effective group than in the ineffective group (p = 0.024 and 0.000, respectively). The levels of fibrinogen and C-reactive protein were also significantly different between the two groups (p = 0.001 and 0.025, respectively). Pre-treatment hearing level and fibrinogen level both significantly impacted the prognosis of all-frequency SSNHL (p = 0.032 and 0.002, respectively), according to a logistic regression analysis. Furthermore, the prognosis was significantly predicted by both fibrinogen level and pre-treatment hearing level (p = 0.001 and 0.0002, respectively). The receiver operating characteristic curve showed that the fibrinogen level had a sensitivity of 85.4% and a specificity of 60.0% for predicting the prognosis of all-frequency SSNHL.

CONCLUSION

For the prognosis of all-frequency SSNHL, the fibrinogen level can be regarded as a useful predictor. The level of C-reactive protein, however, does not have a significant prognostic effect on predicting all-frequency SSNHL. Therefore, more attention should be devoted to the level of fibrinogen in the acute period of all-frequency SSNHL.

LEVEL OF EVIDENCE: 4

Abnormal posterior semicircular canal function may predict poor prognosis in patients with severe and profound ISSNHL

Background

Severe and profound idiopathic sudden sensorineural hearing loss (ISSNHL) generally leads to unfavorable prognosis, and has a considerable impact on patient quality of life. However, related prognostic factors remain controversial.

Objective

To elaborate the relationship between vestibular function impairment and the prognosis of patients with severe and profound ISSNHL, and investigated the relevant factors affecting prognosis.

Methods

Forty-nine patients with severe and profound ISSNHL were divided into good outcome group [GO group, pure tone average (PTA) improvement > 30 dB] and poor outcome group (PO group, PTA improvement ≤ 30 dB) according to hearing outcomes. The clinical characteristics and the proportion of abnormal vestibular function tests in these two groups were analyzed by univariate analysis, and multivariable logistic regression analysis was performed for parameters with significant differences.

Results

Forty-six patients had abnormal vestibular function test results (46/49, 93.88%). The number of vestibular organ injuries was 1.82 ± 1.29 in all patients, with higher mean numbers in PO group (2.22 ± 1.37) than in GO group (1.32 ± 0.99). Univariate analysis revealed no statistical differences between the GO and PO groups in terms of gender, age, side of the affected ear, vestibular symptoms, delayed treatment, instantaneous gain value of horizontal semicircular canal, regression gain value of vertical semicircular canal, abnormal rates of oVEMP, cVEMP, caloric test and vHIT in anterior and horizontal semicircular canal, however, significant differences were found in the initial hearing loss and abnormal vHIT of posterior semicircular canal (PSC). Multivariable analysis revealed that only PSC injury was an independent risk factor for predicting the prognosis of patients with severe and profound ISSNHL. Patients with abnormal PSC function had worse initial hearing impairment and prognosis than patients with normal PSC function. The sensitivity of abnormal PSC function in predicting poor prognosis in patients with severe and profound ISSNHL was 66.67%, specificity was 95.45%, and positive and negative likelihood ratios were 14.65 and 0.35, respectively.

Conclusion

Abnormal PSC function is an independent risk factor for poor prognosis in patients with severe and profound ISSNHL. Ischemia in the branches of the internal auditory artery supplying the cochlea and PSC may be the underlying mechanism.

Diagnostic and predictive values of serum metabolic profiles in sudden sensorineural hearing loss patients

Sudden sensorineural hearing loss (SSNHL) is an otologic emergency, and metabolic disturbance is involved in its pathogenesis. This study recruited 20 SSNHL patients and 20 healthy controls (HCs) and collected their serum samples. Serum metabolites were detected by liquid chromatography-mass spectrometry, and metabolic profiles were analyzed. All patients were followed up for 3 months and categorized into recovery and non-recovery groups. The distinctive metabolites were assessed between two groups, and their predictive values for hearing recovery were evaluated. Analysis results revealed that SSNHL patients exhibited significantly characteristic metabolite signatures compared to HCs. The top 10 differential metabolites were further analyzed, and most of them showed potential diagnostic values based on receiver operator characteristic (ROC) curves. Finally, 14 SSNHL patients were divided into the recovery group, and six patients were included in the non-recovery group. Twelve distinctive metabolites were observed between the two groups, and ROC curves demonstrated that N4-acetylcytidine, p-phenylenediamine, sphingosine, glycero-3-phosphocholine, and nonadecanoic acid presented good predictabilities in the hearing recovery. Multivariate analysis results demonstrated that serum N4-Acetylcytidine, sphingosine and nonadecanoic acid levels were associated with hearing recovery in SSNHL patients. Our results identified that SSNHL patients exhibited distinctive serum metabolomics signatures, and several serum biomarkers were proved to be potential in predicting hearing recovery. The discriminative metabolites might contribute to illustrating the mechanisms of SSNHL and provide possible clues for its treatments.