Cochlear Implantation: The Volumetric Measurement of Vestibular Aqueduct and Gusher Prediction

This study aimed to validate the role of 3D segmentation in measuring the volume of the vestibular aqueduct (VAD), and the inner ear, and to study the correlation between VAD volume and VAD linear measurements at the midpoint and operculum. The correlation with other cochlear metrics was also studied. We retrospectively recruited 21 children (42 ears) diagnosed with Mondini dysplasia (MD) plus enlarged vestibular aqueduct (EVA) from 2009 to 2021 and who underwent cochlear implantation (CI). Patients’ sociodemographic data were collected, and linear cochlear metrics were measured using Otoplan. Vestibular aqueduct width and vestibular aqueduct and inner ear volumes were measured by two independent neuro-otologists using 3D segmentation software (version 4.11.20210226) and high-resolution CT. We also conducted a regression analysis to determine the association between these variables and CT VAD and inner ear volumes. Among the 33 cochlear implanted ears, 13 ears had a gusher (39.4%). Regarding CT inner ear volume, we found that gender, age, A-value, and VAD at the operculum were statistically significant (p-Value = 0.003, <0.001, 0.031, and 0.027, respectively) by regression analysis. Moreover, we found that Age, H value, VAD at the midpoint, and VAD at the operculum were significant predictors of CT VAD volume (p-Value < 0.04). Finally, gender (OR: 0.092; 95%CI: 0.009–0.982; p-Value = 0.048) and VAD at the midpoint (OR: 0.106; 95%CI: 0.015–0.735; p-Value = 0.023) were significant predictors of gusher risk. Patients’ gusher risk was significantly differentiated by gender and VAD width at the midpoint

A novel method for evaluating mastoid defect regrowth after cochlear implantation

Abstract This retrospective study examined mastoid defects resulting from cochlear implant (CI) surgery and their potential for spontaneous regrowth across different age groups. Spontaneous closure of mastoid defects has been observed in certain CI patients during revision surgery or through post-operative temporal bone computer tomography (TB-CT). The analysis encompassed 123 CI recipients, comprising 81.3% children and 18.7% adults, who underwent post-operative TB-CT scans. Using image adjustment software, the study measured mastoid defect areas and found a significant reduction in children's defects between the initial and subsequent scans. Notably, mastoid defect areas differed significantly between children and adults at both time points. Furthermore, the analysis revealed significant correlations between mastoid defect areas and the age at implantation as well as the time elapsed since the CI surgery and the first CT scan. This study provides valuable insights for evaluating CI patients scheduled for revision surgery by assessing potential surgical challenges and duration. Furthermore, it may have a pivotal role in evaluating patients who experience postauricular swelling subsequent to CI surgery

Machine Learning and Cochlear Implantation: Predicting the Post-Operative Electrode Impedances

Cochlear implantation is the common treatment for severe to profound sensorineural hearing loss if there is no benefit from hearing aids. Measuring the electrode impedance along the electrode array at different time points after surgery is crucial in verifying the electrodes’ status, determining the compliance levels, and helping to identify the electric dynamic range. Increased impedance values without proper reprogramming can affect the patient’s performance. The prediction of acceptable levels of electrode impedance at different time points after the surgery could help clinicians during the fitting sessions through a comparison of the predicted with the measured levels. Accordingly, clinicians can decide if the measured levels are within the predicted normal range or not. In this work, we used a dataset of 80 pediatric patients who had received cochlear implants with the MED-EL FLEX 28 electrode array. We predicted the impedance of the electrode arrays in each channel at different time points: at one month, three months, six months, and one year after the date of surgery. We used different machine learning algorithms such as linear regression, Bayesian linear regression, decision forest regression, boosted decision tree regression, and neural networks. The used features include the patient’s age and the intra-operative electrode impedance at different electrodes. Our results indicated that the best algorithm varies depending on the channel, while the Bayesian linear regression and neural networks provide the best results for 75% of the channels. Furthermore, the accuracy level ranges between 83% and 100% in half of the channels one year after the surgery, when an error range between 0 and 3 KΩ is defined as an acceptable threshold. Moreover, the use of the patient’s age alone can provide the best prediction results for 50% of the channels at six months or one year after surgery. This reflects that the patient’s age could be a predictor of the electrode impedance after the surgery

Papular Elastorrhexis: Case report

Papular Elastorrhexis (PE) is a very rare acquired skin disease of unknown etiology characterized by asymptomatic, discrete, hypo-pigmented, non-follicular, tiny skin papules. We report a 52-year-old Saudi female patient who is otherwise healthy presented with a history of asymptomatic persistent skin lesions on her neck that have been increasing in number since adolescence. There are no similar skin lesions in the family. Skin examination showed multiple tiny non-scaly hypo-pigmented-skin colored dome-shaped papules on her neck. Skin biopsy showed normal epidermis and dermis. The elastic stain showed reduced and fragmented elastic fibers in the reticular dermis

Kawarabi: Administrative Structuring of a Multicenter Research Collaborative to Study Kawasaki Disease in the Arab Countries

Kawasaki disease (KD), the leading cause of acquired heart disease in children in developed countries, merits conducting detailed studies in Arab countries. We introduce Kawarabi, as a multicenter research collaborative effort dedicated to improving diagnosis, care, and outcome of children and adults with KD in the Arab world. During the COVID-19 pandemic, there emerged a new multisystem inflammatory syndrome in children; a disease similar to KD. This highlighted the challenges that Arab physicians face in diagnosing and managing children with KD and KD-like illnesses. Kawarabi brings together experts in North America and Arab nations to study this family of diseases in a not-for-profit, voluntary scientific collaborative setting. Bylaws addressing the vision, objectives, structure, and governance of Kawarabi were established, and vetted by the 45 organizing members in 2021. An initial scientific publication showed evidence of a decreased level of awareness of the disease in the general population, as well as the lack of access to resources available for physicians caring for children with KD in Arab countries. Kawarabi has since held several educational webinars and an inaugural yearly meeting. The groundwork for future initiatives targeted at increasing awareness and understanding of the management and the long-term outcomes of children with KD in the region was established. Data on KD in the Arab world are lacking. Kawarabi is a multicenter research collaborative organization that has the unique resources, diversified ethnic makeup, and energy, to accomplish significant advances in our understanding and management of KD and its variants

Access to Care and Therapy for Kawasaki Disease in the Arab Countries: A Kawasaki Disease Arab Initiative (Kawarabi) Multicenter Survey

Kawasaki Disease (KD) is still the most common acquired heart disease in children below the age of five years; it has been well described in the developed world; however, data from the Arab world are limited to case reports or single-center case series. In an effort of optimizing KD research in the Arab world, a group of physicians and researchers established the KD Arab Initiative (Kawarabi) in 2021, and published the first survey, which showed disparities in the availability of intravenous immunoglobulin (IVIG); this had prompted Kawarabi to assess the access to care and therapy of KD patients in Arab countries. A 32 structured questions survey was conducted in thirteen Arab countries and addressed KD patients\u27 access to healthcare in urban and rural settings. The survey results showed that access to care was uniform across large, mid-size cities and rural areas in 7/13 (54%) countries, while in 6/13 (46%) countries, it was in favor of large and mid-size cities over rural areas. The quality of medical services received by children with KD in large cities was rated as excellent in 6/13 or good in 7/13 countries compared to fair in 4/13 or poor in 4/13 countries in rural areas. Availability of IVIG was limited (23%) in mid-size cities and almost impossible (23%) in rural areas. The KD patients in mid-size cities and rural areas have limited access to standard healthcare in the Arab world. This survey laid the foundation for future Kawarabi endeavors to improve the care of children with KD

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population