Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form
D-Scholarship @ Pitt Banner and Links to Homepage

Development of an algorithm for the diagnosis of otitis media

Shaikh, N and Hoberman, A and Rockette, HE and Kurs-Lasky, M (2012) Development of an algorithm for the diagnosis of otitis media. Academic Pediatrics, 12 (3). 214 - 218. ISSN 1876-2859

[img]
Preview
 PDF
Published Version
Available under License : See the attached license file.
Download (476kB) | Preview
[img] Plain Text (licence)
Available under License : See the attached license file.
Download (1kB)

Abstract

Background: The relative importance of signs and symptoms in the diagnosis of otitis media has not been adequately evaluated. This has led to a large degree of variation in the criteria used to diagnose otitis media, which has resulted in inconsistencies in clinical care and discrepant research findings. Methods: A group of experienced otoscopists examined children presenting for primary care. We investigated the signs and symptoms that these otoscopists used to distinguish acute otitis media (AOM), otitis media with effusion (OME), and no effusion. We used recursive partitioning to develop a diagnostic algorithm. To assess the algorithm, we validated it in an independent dataset. Results: Bulging of the tympanic membrane (TM) was the main finding that otoscopists used to discriminate AOM from OME; information regarding the presence or absence of other signs and symptoms added little to the diagnostic process. Overall, 92% of children with AOM had a bulging TM compared with 0% of children with OME. Opacification and/or an air-fluid level was the main finding that the otoscopists used to discriminate OME from no effusion; 97% of children diagnosed with OME had an opaque TM compared with 5% of children diagnosed with no effusion. An algorithm that used bulging and opacification of the TM correctly classified 99% of ears in an independent dataset. Conclusions: Bulging of the TM was the finding that best discriminated AOM from OME. The algorithm developed here may prove to be useful in clinical care, research, and education concerning otitis media. Copyright © 2012 by Academic Pediatric Association.

Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Shaikh, Nnas67@pitt.eduNAS67
Hoberman, A
Rockette, HE
Kurs-Lasky, M
Date: 1 May 2012
Date Type: Publication
Journal or Publication Title: Academic Pediatrics
Volume: 12
Number: 3
Page Range: 214 - 218
DOI or Unique Handle: 10.1016/j.acap.2012.01.007
Schools and Programs: School of Medicine > Pediatrics
Refereed: Yes
ISSN: 1876-2859
Related URLs:
MeSH Headings: Adolescent; Algorithms; Child; Child, Preschool; Decision Making; Diagnosis, Differential; Humans; Male; Middle Ear Ventilation--methods; Otitis Media--diagnosis; Otitis Media with Effusion--diagnosis; Otoscopy--methods; Primary Health Care; Reproducibility of Results; Tympanic Membrane--physiopathology
PubMed ID: 22459064
Date Deposited: 13 Sep 2012 20:03
Last Modified: 02 Feb 2019 16:58
URI: http://d-scholarship.pitt.edu/id/eprint/14061

Metrics

Monthly Views for the past 3 years

Plum Analytics

Altmetric.com

Actions (login required)

View Item View Item