Schuster-Bruce, J;
Shetty, P;
O'Donovan, J;
Mandavia, R;
Sokdavy, T;
Bhutta, MF;
(2021)
Comparative performance of prediction model, non-expert and telediagnosis of common external and middle ear disease using a patient cohort from Cambodia that included one hundred and thirty-eight ears.
Clinical Otolaryngology
, 46
(3)
pp. 635-641.
10.1111/coa.13695.
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Abstract
Efforts to combat the large global burden of ear and hearing disorders are hampered by poor availability of expert diagnosis We report the first study to directly compare prediction model, non-expert and tele-diagnosis of middle and external ear disorders. A prediction model based upon a novel automated otological symptom questionnaire performed poorly, but absence of otorrhoea was found to reliably exclude a diagnosis of chronic suppurative otitis media. Both on-site non-expert and expert tele-diagnosis had high diagnostic specificity, but low sensitivity. Future work could explore how the validity of these diagnostic methods may be improved.
| Type: | Article |
|---|---|
| Title: | Comparative performance of prediction model, non-expert and telediagnosis of common external and middle ear disease using a patient cohort from Cambodia that included one hundred and thirty-eight ears |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/coa.13695 |
| Publisher version: | https://doi.org/10.1111/coa.13695 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Smartphone otoscope, community health workers, digital otoscopy, ear disease, prediction model, remote diagnosis, symptom algorithm |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > The Ear Institute |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10118230 |
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