Multi-modal deep learning for joint prediction of otitis media and diagnostic difficulty.

Objectives: In this study, we propose a diagnostic model for automatic detection of otitis media based on combined input of otoscopy images and wideband tympanometry measurements. Methods: We present a neural network-based model for the joint prediction of otitis media and diagnostic difficulty. We use the subclassifications acute otitis media and otitis media with effusion. The proposed approach is based on deep metric learning, and we compare this with the performance of a standard multi-task network. Results: The proposed deep metric approach shows good performance on both tasks, and we show that the multi-modal input increases the performance for both classification and difficulty estimation compared to the models trained on the modalities separately. An accuracy of 86.5% is achieved for the classification task, and a Kendall rank correlation coefficient of 0.45 is achieved for difficulty estimation, corresponding to a correct ranking of 72.6% of the cases. Conclusion: This study demonstrates the strengths of a multi-modal diagnostic tool using both otoscopy images and wideband tympanometry measurements for the diagnosis of otitis media. Furthermore, we show that deep metric learning improves the performance of the models.

Removing direct oral factor Xa inhibitor interferences from routine and specialised coagulation assays using a raw activated charcoal product.

BACKGROUND: Direct oral anticoagulants (DOACs) are increasingly prescribed for the prevention and treatment of thrombosis. However, DOACs are associated with extensive interference in coagulation assays. Herein, we evaluate raw activated charcoal (AC) as an adsorbent material, to minimise DOAC-associated interferences in routine and specialised coagulation parameters on CS-series analysers (Sysmex, Kobe, Japan). METHODS: Commercial human-derived non-anticoagulated plasma materials, with or without increasing concentrations of anticoagulant, were assayed for routine and specialised coagulation parameters before and after treatment with AC. RESULTS: Treatment of non-anticoagulated plasma with raw AC had minimal impact on routine and specialised coagulation parameters available on the CS-series; however, clinically relevant prolongations of certain activated partial thromboplastin time (APTT)-based assays were observed after treatment. Furthermore, in apixaban- and rivaroxaban-containing plasma material, AC efficiently adsorbed therapeutic and supratherapeutic DOAC concentrations; and, treatment with raw AC resolved DOAC-associated interferences on all affected routine and specialised coagulation parameters. CONCLUSIONS: Overall, raw AC efficiently adsorbed apixaban and rivaroxaban from human-derived plasma, without significantly affecting the majority of underlying routine and specialised coagulation parameters available on CS-series analysers.

It's in the blood: a review of the hematological system in SARS-CoV-2-associated COVID-19.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an unprecedented global healthcare crisis. While SARS-CoV-2-associated COVID-19 affects primarily the respiratory system, patients with COVID-19 frequently develop extrapulmonary manifestations. Notably, changes in the hematological system, including lymphocytopenia, neutrophilia and significant abnormalities of hemostatic markers, were observed early in the pandemic. Hematological manifestations have since been recognized as important parameters in the pathophysiology of SARS-CoV-2 and in the management of patients with COVID-19. In this narrative review, we summarize the state-of-the-art regarding the hematological and hemostatic abnormalities observed in patients with SARS-CoV-2-associated COVID-19, as well as the current understanding of the hematological system in the pathophysiology of acute and chronic SARS-CoV-2-associated COVID-19.

Aided Cortical Auditory Evoked Potentials in Infants With Frequency-Specific Synthetic Speech Stimuli: Sensitivity, Repeatability, and Feasibility.

OBJECTIVES: The cortical auditory evoked potential (CAEP) test is a candidate for supplementing clinical practice for infant hearing aid users and others who are not developmentally ready for behavioral testing. Sensitivity of the test for given sensation levels (SLs) has been reported to some degree, but further data are needed from large numbers of infants within the target age range, including repeat data where CAEPs were not detected initially. This study aims to assess sensitivity, repeatability, acceptability, and feasibility of CAEPs as a clinical measure of aided audibility in infants. DESIGN: One hundred and three infant hearing aid users were recruited from 53 pediatric audiology centers across the UK. Infants underwent aided CAEP testing at age 3 to 7 months to a mid-frequency (MF) and (mid-)high-frequency (HF) synthetic speech stimulus. CAEP testing was repeated within 7 days. When developmentally ready (aged 7-21 months), the infants underwent aided behavioral hearing testing using the same stimuli, to estimate the decibel (dB) SL (i.e., level above threshold) of those stimuli when presented at the CAEP test sessions. Percentage of CAEP detections for different dB SLs are reported using an objective detection method (Hotellings T 2 ). Acceptability was assessed using caregiver interviews and a questionnaire, and feasibility by recording test duration and completion rate. RESULTS: The overall sensitivity for a single CAEP test when the stimuli were ≥0 dB SL (i.e., audible) was 70% for the MF stimulus and 54% for the HF stimulus. After repeat testing, this increased to 84% and 72%, respectively. For SL >10 dB, the respective MF and HF test sensitivities were 80% and 60% for a single test, increasing to 94% and 79% for the two tests combined. Clinical feasibility was demonstrated by an excellent >99% completion rate, and acceptable median test duration of 24 minutes, including preparation time. Caregivers reported overall positive experiences of the test. CONCLUSIONS: By addressing the clinical need to provide data in the target age group at different SLs, we have demonstrated that aided CAEP testing can supplement existing clinical practice when infants with hearing loss are not developmentally ready for traditional behavioral assessment. Repeat testing is valuable to increase test sensitivity. For clinical application, it is important to be aware of CAEP response variability in this age group.

Modified T2 Statistics for Improved Detection of Aided Cortical Auditory Evoked Potentials in Hearing-Impaired Infants.

The cortical auditory evoked potential (CAEP) is a change in neural activity in response to sound, and is of interest for audiological assessment of infants, especially those who use hearing aids. Within this population, CAEP waveforms are known to vary substantially across individuals, which makes detecting the CAEP through visual inspection a challenging task. It also means that some of the best automated CAEP detection methods used in adults are probably not suitable for this population. This study therefore evaluates and optimizes the performance of new and existing methods for aided (i.e., the stimuli are presented through subjects' hearing aid(s)) CAEP detection in infants with hearing loss. Methods include the conventional Hotellings T2 test, various modified q-sample statistics, and two novel variants of T2 statistics, which were designed to exploit the correlation structure underlying the data. Various additional methods from the literature were also evaluated, including the previously best-performing methods for adult CAEP detection. Data for the assessment consisted of aided CAEPs recorded from 59 infant hearing aid users with mild to profound bilateral hearing loss, and simulated signals. The highest test sensitivities were observed for the modified T2 statistics, followed by the modified q-sample statistics, and lastly by the conventional Hotelling's T2 test, which showed low detection rates for ensemble sizes <80 epochs. The high test sensitivities at small ensemble sizes observed for the modified T2 and q-sample statistics are especially relevant for infant testing, as the time available for data collection tends to be limited in this population.

Do cochlear microphonics evoked by narrow-band chirp stimuli affect the objective detection of auditory steady-state responses?

OBJECTIVE: It has recently been discussed whether hearing screening and hearing threshold assessment can accurately be completed using automated ASSR methods for children with auditory neuropathy spectrum disorder (ANSD). Possible causes for the claimed potential failures were investigated here. DESIGN: The study is based on the analysis of stored ASSR raw data. STUDY SAMPLE: This study reviewed raw ASSR data from 274 patients with a total of 5809 individual recordings. RESULTS: Cochlear microphonics (CM) were found in 18 of the 274 patient records. Four of these 18 were obtained from patients with ANSD. One patient with ANSD without click auditory brainstem responses up to 100 dBnHL demonstrated clear ASSR responses from 65 dBnHL upwards. Where click stimulation suggests an auditory nerve defect, narrow-band chirps were shown to evoke ASSR in certain patients. CMs are elicited by narrow-band chirps in the same way as by broadband stimuli. CM residuals as well as a presumed enlarged wave I with absent neural responses, always accompanied by CM, were found as possible causes of misinterpretation at high stimulus levels. A CM detector was created. CONCLUSIONS: The CM detector, indicating the presence of CM, will prevent misinterpretation of clinical ASSR results.

Categorization of tinnitus listeners with a focus on cochlear synaptopathy.

Tinnitus is a complex and not yet fully understood phenomenon. Often the treatments provided are effective only for subgroups of sufferers. We are presently not able to predict benefit with the currently available diagnostic tools and analysis methods. Being able to identify and specifically treat sub-categories of tinnitus would help develop and implement more targeted treatments with higher success rate. In this study we use a clustering analysis based on 17 predictors to cluster an audiologically homogeneous group of normal hearing participants, both with and without tinnitus. The predictors have been chosen to be either tinnitus-specific measures or measures that are thought to be connected to cochlear synaptopathy. Our aim was to identify a subgroup of participants with characteristics consistent with the current hypothesized impact of cochlear synaptopathy. Our results show that this approach can separate the listeners into different clusters. But not in all cases could the tinnitus sufferers be separated from the control group. Another challenge is the use of categorical measures which seem to dominate the importance analysis of the factors. The study showed that data-driven clustering of a homogeneous listener group based on a mixed set of experimental outcome measures is a promising tool for tinnitus sub-typing, with the caveat that sample sizes might need to be sufficiently high, and higher than in the present study, to keep a meaningful sample size after clustering.

Metalloprotease-Dependent S2'-Activation Promotes Cell-Cell Fusion and Syncytiation of SARS-CoV-2.

SARS-CoV-2 cell-cell fusion and syncytiation is an emerging pathomechanism in COVID-19, but the precise factors contributing to the process remain ill-defined. In this study, we show that metalloproteases promote SARS-CoV-2 spike protein-induced syncytiation in the absence of established serine proteases using in vitro cell-cell fusion assays. We also show that metalloproteases promote S2'-activation of the SARS-CoV-2 spike protein, and that metalloprotease inhibition significantly reduces the syncytiation of SARS-CoV-2 variants of concern. In the presence of serine proteases, however, metalloprotease inhibition does not reduce spike protein-induced syncytiation and a combination of metalloprotease and serine protease inhibition is necessitated. Moreover, we show that the spike protein induces metalloprotease-dependent ectodomain shedding of the ACE2 receptor and that ACE2 shedding contributes to spike protein-induced syncytiation. These observations suggest a benefit to the incorporation of pharmacological inhibitors of metalloproteases into treatment strategies for patients with COVID-19.

A Deep Learning Approach for Detecting Otitis Media From Wideband Tympanometry Measurements.

OBJECTIVE: In this study, wepropose an automatic diagnostic algorithm for detecting otitis media based on wideband tympanometry measurements. METHODS: We develop a convolutional neural network for classification of otitis media based on the analysis of the wideband tympanogram. Saliency maps are computed to gain insight into the decision process of the convolutional neural network. Finally, we attempt to distinguish between otitis media with effusion and acute otitis media, a clinical subclassification important for the choice of treatment. RESULTS: The approach shows high performance on the overall otitis media detection with an accuracy of 92.6%. However, the approach is not able to distinguish between specific types of otitis media. CONCLUSION: Out approach can detect otitis media with high accuracy and the wideband tympanogram holds more diagnostic information than the commonly used techniques wideband absorbance measurements and simple tympanograms. SIGNIFICANCE: This study shows how advanced deep learning methods enable automatic diagnosis of otitis media based on wideband tympanometry measurements, which could become a valuable diagnostic tool.

Inter-rater reliability of the diagnosis of otitis media based on otoscopic images and wideband tympanometry measurements.

OBJECTIVES: This study aims to investigate the inter-rater reliability and agreement of the diagnosis of otitis media with effusion, acute otitis media, and no effusion cases based on an otoscopy image and in some cases an additional wideband tympanometry measurement of the patient. METHODS: 1409 cases were examined and diagnosed by an otolaryngologist in the clinic, and otoscopy examination and wideband tympanometry (WBT) measurement were conducted. Afterwards, four otolaryngologists (Ear, Nose, and Throat doctors, ENTs), who did not perform the acute examination of the patients, evaluated the otoscopy images and WBT measurements results for diagnosis (acute otitis media, otitis media with effusion, or no effusion). They also specified their diagnostic certainty for each case, and reported whether they used the image, wideband tympanometry, or both, for diagnosis. RESULTS: All four ENTs agreed on the diagnosis in 57% of the cases, with a pairwise agreement of 74%, and a Light's Kappa of 0.58. There are, however, large differences in agreement and certainty between the three diagnoses. Acute otitis media yields the highest agreement (77% between all four ENTs) and certainty (0.90), while no effusion shows much lower agreement and certainty (34% and 0.58, respectively). There is a positive correlation between certainty and agreement between the ENTs across all cases, and both certainty and agreement increase for cases where a WBT measurement is shown in addition to the otoscopy image. CONCLUSIONS: The inter-rater reliability between four ENTs was high when diagnosing acute otitis media and lower when diagnosing otitis media with effusion. However, WBT can add valuable information to get closer to the ground-truth diagnosis without myringotomy. Furthermore, the diagnostic certainty increases when the WBT is examined together with the otoscopy image.

Chirp-Evoked Auditory Steady-State Response: The Effect of Repetition Rate.

OBJECTIVE: The auditory steady-state response (ASSR) is commonly used in clinical pediatric audiology in order to provide an electrophysiological estimate of hearing threshold, and has the potential to be used in unsupervised mobile EEG applications. Enhancement of the ASSR amplitude through optimization of the stimulation and recording methods shortens the required testing time or reduce the offset between the electrophysiological and behavioral thresholds. Here, we investigate the spatial distribution of the ASSR to broadband chirp stimuli across a wide range of repetition rates on the scalp and in the ears. Moreover, the ASSR amplitude is compared across repetition rates for commonly used electrode configurations. METHODS: ASSR to chirp stimuli with repetition rates from 6-198 Hz was recorded using scalp EEG and high-density ear-EEG. RESULTS: The distributions of the ASSR amplitude and phase were found to be dependent on the chirp repetition rate across the scalp, but independent of repetition rate in the ears. The normal drop in ASSR SNR for high repetition rates seen for click and pure tone stimuli was not found for chirp stimuli. Instead, the ASSR SNRs for chirp stimuli at high repetition rates (95-198 Hz) were found to be comparable to that found at 40 Hz for scalp EEG and even higher than 40 Hz ASSR for ear-EEG. CONCLUSION: Based on the results, use of chirp stimuli with high repetition rates (95-198 Hz) is advantageous for multiple stimulus ASSR recording in both clinical practice and mobile real-life applications.

Do Room Acoustics Affect the Amplitude of Sound-Field Auditory Steady-State Responses?

The sound-field auditory steady-state response (ASSR) is a promising measure for the objective validation of hearing-aid fitting in patients who are unable to respond to behavioral testing reliably. To record the sound-field ASSR, the stimulus is reproduced through a loudspeaker placed in front of the patient. However, the reverberation and background noise of the measurement room could reduce the stimulus modulation used for eliciting the ASSR. As the ASSR level is heavily dependent on the stimulus modulation, any reduction due to room acoustics could affect the clinical viability of sound-field ASSR testing. This study investigated the effect of room acoustics on the level and detection rate of sound-field ASSR. The study also analyzed whether early decay time and an auditory-inspired relative modulation power model could be used to predict the changes in the recorded ASSR in rooms. A monaural auralization approach was used to measure sound-field ASSR via insert earphones. ASSR was measured for 15 normal-hearing adult subjects using narrow-band CE-Chirps® centered at the octave bands of 500, 1000, 2000, and 4000 Hz. These stimuli were convolved with simulated impulse responses of three rooms inspired by audiological testing rooms. The results showed a significant reduction of the ASSR level for the room conditions compared with the reference anechoic condition. Despite this reduction, the detection rates for the first harmonics of the ASSR were unaffected when sufficiently long recordings (up to 6 min) were made. Furthermore, the early decay time and relative modulation power appear to be useful predictors of the ASSR level in the measurement rooms.

The Influence of the Type of Background Noise on Perceptual Learning of Speech in Noise.

OBJECTIVES: Auditory perceptual learning studies tend to focus on the nature of the target stimuli. However, features of the background noise can also have a significant impact on the amount of benefit that participants obtain from training. This study explores whether perceptual learning of speech in background babble noise generalizes to other, real-life environmental background noises (car and rain), and if the benefits are sustained over time. DESIGN: Normal-hearing native English speakers were randomly assigned to a training (n = 12) or control group (n = 12). Both groups completed a pre- and post-test session in which they identified Bamford-Kowal-Bench (BKB) target words in babble, car, or rain noise. The training group completed speech-in-babble noise training on three consecutive days between the pre- and post-tests. A follow up session was conducted between 8 and 18 weeks after the post-test session (training group: n = 9; control group: n = 7). RESULTS: Participants who received training had significantly higher post-test word identification accuracy than control participants for all three types of noise, although benefits were greatest for the babble noise condition and weaker for the car- and rain-noise conditions. Both training and control groups maintained their pre- to post-test improvement over a period of several weeks for speech in babble noise, but returned to pre-test accuracy for speech in car and rain noise. CONCLUSION: The findings show that training benefits can show some generalization from speech-in-babble noise to speech in other types of environmental noise. Both groups sustained their learning over a period of several weeks for speech-in-babble noise. As the control group received equal exposure to all three noise types, the sustained learning with babble noise, but not other noises, implies that a structural feature of babble noise was conducive to the sustained improvement. These findings emphasize the importance of considering the background noise as well as the target stimuli in auditory perceptual learning studies.

Deep metric learning for otitis media classification.

In this study, we propose an automatic diagnostic algorithm for detecting otitis media based on otoscopy images of the tympanic membrane. A total of 1336 images were assessed by a medical specialist into three diagnostic groups: acute otitis media, otitis media with effusion, and no effusion. To provide proper treatment and care and limit the use of unnecessary antibiotics, it is crucial to correctly detect tympanic membrane abnormalities, and to distinguish between acute otitis media and otitis media with effusion. The proposed approach for this classification task is based on deep metric learning, and this study compares the performance of different distance-based metric loss functions. Contrastive loss, triplet loss and multi-class N-pair loss are employed, and compared with the performance of standard cross-entropy and class-weighted cross-entropy classification networks. Triplet loss achieves high precision on a highly imbalanced data set, and the deep metric methods provide useful insight into the decision making of a neural network. The results are comparable to the best clinical experts and paves the way for more accurate and operator-independent diagnosis of otitis media.

Efficient Detection of Cortical Auditory Evoked Potentials in Adults Using Bootstrapped Methods.

BACKGROUND: Statistical detection methods are useful tools for assisting clinicians with cortical auditory evoked potential (CAEP) detection, and can help improve the overall efficiency and reliability of the test. However, many of these detection methods rely on parametric distributions when evaluating test significance, and thus make various assumptions regarding the electroencephalogram (EEG) data. When these assumptions are violated, reduced test sensitivities and/or increased or decreased false-positive rates can be expected. As an alternative to the parametric approach, test significance can be evaluated using a bootstrap, which does not require some of the aforementioned assumptions. Bootstrapping also permits a large amount of freedom when choosing or designing the statistical test for response detection, as the distributions underlying the test statistic no longer need to be known prior to the test. OBJECTIVES: To improve the reliability and efficiency of CAEP-related applications by improving the specificity and sensitivity of objective CAEP detection methods. DESIGN: The methods included in the assessment were Hotelling's T2 test, the Fmp, four modified q-sample statistics, and various template-based detection methods (calculated between the ensemble coherent average and some predefined template), including the correlation coefficient, covariance, and dynamic time-warping (DTW). The assessment was carried out using both simulations and a CAEP threshold series collected from 23 adults with normal hearing. RESULTS: The most sensitive method was DTW, evaluated using the bootstrap, with maximum increases in test sensitivity (relative to the conventional Hotelling's T2 test) of up to 30%. An important factor underlying the performance of DTW is that the template adopted for the analysis correlates well with the subjects' CAEP. CONCLUSION: When subjects' CAEP morphology is approximately known before the test, then the DTW algorithm provides a highly sensitive method for CAEP detection.

The Convolutional Group Sequential Test: Reducing Test Time for Evoked Potentials.

When using a statistical test for automatically detecting evoked potentials, the number of stimuli presented to the subject (the sample size for the statistical test) should be specified at the outset. For evoked response detection, this may be inefficient, i.e., because the signal-to-noise ratio (SNR) of the response is not known in advance, the user would usually err on the cautious side and use a relatively high number of stimuli to ensure adequate statistical power. A more efficient approach is to apply the statistical test repeatedly to the accumulating data over time, as this allows the test to be stopped early for the high SNR responses (thus reducing test time), or later for the low SNR responses. The caveat is that the critical decision boundaries for rejecting the null hypothesis need to be adjusted if the intended type-I error rate is to be obtained. This study presents an intuitive and flexible method for controlling the type-I error rate for sequentially applied statistical tests. The method is built around the discrete convolution of truncated probability density functions, which allows the null distribution for the test statistic to be constructed at each stage of the sequential analysis. Because the null distribution remains tractable, the procedure for finding the stage-wise critical decision boundaries is greatly simplified. The method also permits data-driven adaptations (using data from previous stages) to both the sample size and the statistical test, which offers new opportunities to speed up testing for evoked response detection.

Mannose Binding Lectin Is Hydroxylated by Collagen Prolyl-4-hydroxylase and Inhibited by Some PHD Inhibitors.

Background: Mannose-binding lectin (MBL) is an important component of innate immune defense. MBL undergoes oligomerization to generate high mol weight (HMW) forms which act as pattern recognition molecules to detect and opsonize various microorganisms. Several post-translational modifications including prolyl hydroxylation are known to affect the oligomerization of MBL. Yet, the enzyme(s) which hydroxylate proline in the collagen-like domain residues have not been identified and the significance of prolyl hydroxylation is incompletely understood. Methods: To investigate post-translational modifications of MBL, we stably expressed Myc-DDK tagged MBL in HEK293S cells. We used pharmacologic and genetic inhibition of 2-oxoglutarate-dependent dioxygenases (2OGDD) to identify the enzyme required for prolyl hydroxylation of MBL. We performed mass spectrometry to determine the effects of various inhibitors on MBL modifications. Results: Secretion of HMW MBL was impaired by inhibitors of the superfamily of 2OGDD, and was dependent on prolyl-4-hydroxylase subunit α1. Roxadustat and vadadustat, but not molidustat, led to significant suppression of hydroxylation and secretion of HMW forms of MBL. Conclusions: These data suggest that prolyl hydroxylation in the collagen-like domain of MBL is mediated by collagen prolyl-4-hydroxylase. Reduced MBL activity is likely to be an off-target effect of some, but not all, prolyl hydroxylase domain (PHD) inhibitors. There may be advantages in selective PHD inhibitors that would not interfere with MBL production.