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. 2009 Sep;148(3):466-70.
doi: 10.1016/j.ajo.2009.03.032. Epub 2009 May 23.

A data-driven approach to the management of accommodative esotropia

Affiliations

A data-driven approach to the management of accommodative esotropia

Ashvini K Reddy et al. Am J Ophthalmol. 2009 Sep.

Abstract

Purpose: To determine if key findings on initial examination are predictive of ability to achieve and maintain functional alignment (residual esotropia of less than 8 prism diopters) with single-vision spectacles, bifocals, or surgery in children with accommodative esotropia.

Design: Retrospective, observational case series.

Methods: Institutional review of 68 consecutive accommodative esotropia patients. Exclusion criteria included previous spectacles use, other ocular pathologic features or surgery, or follow-up of less than 2 years. The main outcome measure was the ability to achieve functional alignment.

Results: Mean age at the time of single-vision spectacle prescription (P = .02), mean cycloplegic refractive error (P = .016), amblyopia (P = .02), uncorrected near deviation (P < .001), and uncorrected distance deviation (P < .001) differed significantly between children who achieved functional alignment with single-vision lenses and those who did not. The most parsimonious prediction model revealed that presence of amblyopia (P = .113; odds ratio [OR], 0.138; 95% confidence interval [CI], 0.012 to 1.59), uncorrected distance deviation (P = .004; OR, 1.156; 95% CI, 1.049 to 1.274), mean cycloplegic refractive error (P = .008; OR, 0.300; 95% CI, 0.123 to 0.732), and age at time of single-vision lens prescription (P = .007; OR, 0.259; 95% CI, 0.097 to 0.690) were the best predictors of ability to achieve orthotropia with single-vision spectacles with a sensitivity of 94% (95% CI, 71% to 99%) and specificity of 91% (95% CI, 75% to 98%).

Conclusions: Significant differences exist in the clinical presentations of children who achieve functional orthotropia with single-vision spectacles and those who require bifocals or surgery. An evidence-based algorithm may help practitioners predict which intervention is most likely to benefit an individual child.

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