Research

1. UCLH Biomedical Research Centre

The research of the evidENT team is closely linked to that of the NIHR UCLH Biomedical Research Centre, a partnership between University College London Hospitals NHS Foundation Trust and UCL. 

2. Clinical Trials

MACRO

MACRO programme is an NIHR-funded national research programme on Defining best Management in Adult Chronic
RhinOsinusitis (CRS). More information about the programme can be found on https://www.isrctn.com/ISRCTN36962030. The programme consists of three workstreams including: 1) mapping the current practice 2) a randomised clinical trial (more information about the trial can be found on the registry website https://www.isrctn.com/ISRCTN36962030 & the trial website https://workstream2.themacroprogramme.org.uk/macro/the-macro-programme-home), and 3)the final stage of collation of programme and trial results and findings to reach consensus on the best management of CRS.

The lay summary of the programme publications can also be found here in the lower part of the page https://workstream2.themacroprogramme.org.uk/macro/news"

Publications from WS 1 include:
Vennik J, Eyles C, Thomas M, et al. Management strategies for chronic rhinosinusitis: a qualitative study of GP and ENT specialist views of current practice in the UK. BMJ Open 2018;8:e022643 
Vennik J, Eyles C, Thomas M, et al. Chronic rhinosinusitis: a qualitative study of patient views and experiences of current management in primary and secondary care. BMJ Open 2019;9:e022644. 
Hopkins C, Williamson E, Morris S, et al. Antibiotic usage in chronic rhinosinusitis: analysis of national primary care electronic health records. Rhinology. 2019 Dec 1;57(6):420-429. Williamson E, Denaxas S, Morris S, et al. Risk of mortality and cardiovascular events following macrolide prescription in chronic rhinosinusitis patients: a cohort study using linked primary care electronic health records. Rhinology. 2019 Aug 1;57(4):252-260. 
Blackshaw H, Vennik J, Philpott C, et al. (2019) Expert panel process to optimise the design of a randomised controlled trial in chronic rhinosinusitis (the MACRO programme). 2019 Trials, 20, [230]. (2019) 
Ta N, Hopkins C, Vennik J, Philpott C. Optimising trial outcomes and patient retention for the MACRO trial for CRS. Rhinology 2019: Oct 1;57(5):358-366. doi: 10.4193/Rhin19 
Clarke S C, Williamson E, Denaxas S, et al. Cost of chronic rhinosinusitis surgery in England, using linked primary and secondary care electronic patient-level data. BMJ Open 2022;12:e055603. doi:10.1136/ bmjopen-2021-055603 
Publications from WS 2 include: 
Philpott C, le Conte S, Beard D, et al. Clarithromycin and endoscopic sinus surgery for adults with chronic rhinosinusitis with and without nasal polyps: study protocol for the MACRO randomised controlled trial. Trials 20, [246] (2019) 
McDermott C, Vennik J, Philpott C, et al. Maximising recruitment to a randomised controlled trial for chronic rhinosinusitis using qualitative research methods: the MACRO conversation study. Trials 22, 54 (2021).

COACH

Comparing cochlear implants with hearing aids in adults with severe hearing loss.

In the UK, cochlear implants are provided to some people with severe or profound hearing losses who do not get enough benefit from their hearing aids, and for these people, cochlear implants can improve the ability to recognise sounds and understand speech. Currently, only these adults are offered a cochlear implant on the NHS.

The COACH trial is looking to recruit 130 adults with severe hearing loss who do not meet the NHS criteria for a cochlear implant but who are close to meeting those criteria.

The trial will assess whether a cochlear implant or hearing aids are better at improving speech understanding for adults with severe hearing loss. We do not know which treatment option is better or if they are similar for this group of people which is why we need to run the trial.

For more information visit the coach website or the registry website. 

https://www.coachtrial.ac.uk/information-for-participants/information-for-participants.aspx

FAMOUS

Investigating the clinical and cost effectiveness of a 4-step follow-up and monitoring intervention compared to usual care for adults offered an NHS hearing aid for the first time.

For more information visit the NIHR website. 

Starfish

Hearing loss is a common and disabling condition that may result from problems with the cochlea, an inner ear structure that senses sound and sends information to the brain. Loss of hearing due to damage to the cochlea can occur suddenly and without an obvious cause, a condition described as idiopathic sudden sensorineural hearing loss (ISSNHL). ISSNHL usually occurs in one ear, and can range from a mild hearing loss to a completely deaf ear.

The recovery of hearing following ISSNHL may be helped by urgent treatment with steroids, and this is the standard treatment that most doctors would recommend for the condition.

In the UK, steroids are commonly given for this condition in three forms: as tablets, as an injection through the ear drum, or by both routes at the same time. At the moment we do not know how best to give steroids for ISSNHL, but this study aims to identify the method that will provide the best recovery of hearing for patients with ISSNHL.

For more information visit the Starfish website.

Bone Conduction Study

Bone conducting hearing aids provide a superior listening experience compared to conventional hearing aids when used by patients who's hearing is severely affected by inefficient sound transmission from the ear drum to the inner ear (conductive hearing loss).  

However, it is unclear whether such bone conducting hearing aids would also help those with milder forms of conductive hearing loss. 

Our study is funded by COCHLEAR LTD to explore the effectiveness of bone conduction versus conventional hearing devices in those with a small air-bone gap pattern of hearing loss. It is a multicentre study adopted by the NIHR portfolio to recruit 60 patients over 1 year. 

Akuous Study

The goal of the study is to find out if the study drug, an adeno-associated viral (AAV) vector gene therapy, is safe and improves hearing in children with sensorineural hearing loss (SNHL) due to otoferlin gene (OTOF) mutations.

For more information visit the OTOF clinical trials website. 

Gene Therapy Trial

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Enhance

The ENHANCE study (TailorEd iNtervention for brain HeAlth aNd Cognitive Enrichment) aims to reduce dementia risk by addressing factors including hearing loss in older adults, adapting successful South Korean strategies with gaming technology and public health approaches for the UK. 

For more information visit UCL page (https://www.ucl.ac.uk/uclic/research-projects/2024/feb/enhance-tailored-intervention-brain-health-and-cognitive-enrichment) and NIHR website (https://fundingawards.nihr.ac.uk/award/NIHR203670)

Publications:

Hee Kyung Park, Jee Hyang Jeong, So Young Moon, Yoo Kyoung Park, Chang Hyung Hong, Hae Ri Naet al. South Korean Study to Prevent Cognitive Impairment and Protect Brain Health Through Lifestyle Intervention in At-Risk Elderly People: Protocol of a Multicenter, Randomized Controlled Feasibility Trial. J Clin Neurol. 2020 Apr; 16(2): 292–303.  doi: 10.3988/jcn.2020.16.2.292.

3. Data Science Projects

NIHR Health Informatics Collaborative – Hearing Health

Mr Nish Mehta co-leads this collaborative which focuses on making better use of patient hearing health data captured in NHS records. Participating sites across the UK collect hearing data in a standardised and integrated manner and have set up a structure for sharing and analysing these data anonymously. Plans for future research include exploration of effects of known and novel risk factors for hearing loss, identification of genetic causes of hearing loss and identification of candidates for upcoming clinical trials.

For more information visit the NIHR website. 

Artificial Intelligence Projects

Automatic Audiogram Phenotyping

Using the latest advancements in unsupervised and deep learning, our team is developing a set of models to automatically group people with hearing loss into different phenotypes depending on their audiometric data. Specifically, we consider the audiogram to provide direction towards as yet unknown sub-types of sensorineural hearing loss.

The work is spearheaded by Nishchay Mehta and Lilia Dimitrov, amongst others in the lab.

Audiogram Digitisation

Datasets containing rich information, such as audiograms, were hand-drawn in the UK before 2005. This has considerable implications for the UK population as it limits our ability to understand hearing loss progression using only digital data captured from roughly the mid 2000’s. There is a need to include hand-drawn historical data in analyses. The project's primary goal is to build and evaluate an AI system for digitising hand-drawn audiograms. By doing so, we aim to create an inclusive database that captures the diversity of hearing data, enabling more accurate predictions and isights into hearing health over time.

The work is spearheaded by Nishchay Mehta and Liam Barrett, et al..

Artificially Intelligent Audiometry

This project looks to automate audiometric data collection and analysis. While the project will consider a range of audiometric testing such as, speech audiometry, auditory brainstem responses and, otoacoustic emissions, only pure-tone audiometry (PTA) is described here currently. PTA is a gold standard of audiometric testing and is done routinely across audiology, otology and related fields. It is, therefore, an excellent candidate to start integrating AI techniques with audiometric data collection and analysis.

The work is spearheaded by Nishchay Mehta and Liam Barrett, et al..

Automatic Ossicle Segmentation

Cone beam computed tomography (CBCT) is used extensively in otology for diagnosis, disease extent, and surgical planning, amongst other uses. A key component of CBCT’s use in otology is the identification and separation of the middle-ear structures, which often requires a specialist radiologist. This provides a potential area for AI assistance, with our team developing a set of advanced vision models to automatically detect and segment the ossicular chain at specialist levels. We aim to take these models forward to have diagnostic capabilities for clinical questions that currently even expert head and neck radiologists struggle to answer.

The work is spearheaded by Nishchay Mehta and Talisa Ross, et al..

Synthesising Audiometric Data

The potential for data-driven pure-tone audiometry (PTA) synthesis has not been fully explored, particularly concerning anonymising audiometric data and its implications for public health reporting. We are developing a series of techniques to generate valid and completely synthetic data that represent specific hearing loss aetiologies.

The work is spearheaded by Nishchay Mehta and Liam Barrett, et al..

Evaluating Healthcare Records Through Deep Learning

Electronic Health Records (EHRs) provide rich, unstructured textual data containing expert observations about patients. However, this unstructured nature presents challenges for machine learning applications. This project leverages large language models to analyse EHRs, specifically focusing on clinical notes and letters to derive symptoms and diagnosis lists. This project's aims include automating the process of phenotyping patients with hearing loss using natural language processing techniques, amongst others.

The work is spearheaded by Nishchay Mehta and Nikhil Joshi, et al.

4. Observational Studies

Ototoxicity monitoring in platinum based chemotherapy,

Monitoring ototoxicity in patients undergoing treatment with platinum-based chemotherapy for sarcoma and testicular cancer using tablet based self-administered hearing tests and serum biomarkers.

SeaSHeL

National cohort study investigating patient pathways, quality of life and prognosis for sudden-onset sensorineural hearing loss.

For more information visit the SeaSHeL website.

Publications:

• Mandavia R, Hannink G, Ahmed MN, et al. Prognostic factors for outcomes of idiopathic sudden sensorineural hearing loss: protocol for the SeaSHeL national prospective cohort study. BMJ Open. 2020;10(9):e038552. Published 2020 Sep 28. doi:10.1136/bmjopen-2020-038552