Cargando…

A smartphone ocular alignment measurement app in school screening for strabismus

BACKGROUND: Strabismus is the leading risk factor for amblyopia, which should be early detected for minimized visual impairment. However, traditional school screening for strabismus can be challenged due to several factors, most notably training, mobility and cost. The purpose of our study is to eva...

Descripción completa

Detalles Bibliográficos
Autores principales: Cheng, Wenbo, Lynn, Marissa H., Pundlik, Shrinivas, Almeida, Cheryl, Luo, Gang, Houston, Kevin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992982/
https://www.ncbi.nlm.nih.gov/pubmed/33765984
http://dx.doi.org/10.1186/s12886-021-01902-w
Descripción
Sumario:BACKGROUND: Strabismus is the leading risk factor for amblyopia, which should be early detected for minimized visual impairment. However, traditional school screening for strabismus can be challenged due to several factors, most notably training, mobility and cost. The purpose of our study is to evaluate the feasibility of using a smartphone application in school vision screening for detection of strabismus. METHODS: The beta smartphone application, EyeTurn, can measure ocular misalignment by computerized Hirschberg test. The application was used by a school nurse in a routine vision screening for 133 elementary school children. All app measurements were reviewed by an ophthalmologist to assess the rate of successful measurement and were flagged for in-person verification with prism alternating cover test (PACT) using a 2.4Δ threshold (root mean squared error of the app). A receiver operating characteristic (ROC) curve was used to determine the best sensitivity and specificity for an 8Δ threshold (recommended by AAPOS) with the PACT measurement as ground truth. RESULTS: The nurse obtained at least one successful app measurement for 93% of children (125/133). 40 were flagged for PACT, of which 6 were confirmed to have strabismus, including 4 exotropia (10△, 10△, 14△ and 18△), 1 constant esotropia (25△) and 1 accommodative esotropia (14△). Based on the ROC curve, the optimum threshold for the app to detect strabismus was determined to be 3.0△, with the best sensitivity (83.0%), specificity (76.5%). With this threshold the app would have missed one child with accommodative esotriopia, whereas conventional screening missed 3 cases of intermittent extropia. CONCLUSIONS: Results support feasibility of use of the app by personnel without professional training in routine school screenings to improve detection of strabismus. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12886-021-01902-w.