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Randomized Trial Comparing Prediction Accuracy of Two Swept Source Optical Coherence Tomography Biometers.
Multack, Sam; Plummer, Nellie; Smits, Gerard; Hall, Brad.
Afiliação
  • Multack S; Multack Eye Care, Frankfort, IL, USA.
  • Plummer N; Multack Eye Care, Frankfort, IL, USA.
  • Smits G; CSC, Inc., Santa Barbara, CA, USA.
  • Hall B; Sengi, Penniac, NB, Canada.
Clin Ophthalmol ; 17: 2423-2428, 2023.
Article em En | MEDLINE | ID: mdl-37609646
ABSTRACT

Purpose:

To compare the prediction accuracy of the Argos biometer using standard keratometry to the prediction accuracy of the IOLMaster 700 biometer using Total Keratometry.

Methods:

This was a randomized, prospective, single surgeon study of 80 right eyes of 80 patients that had preoperative biometry with both the Argos and IOLMaster 700 devices, followed by cataract surgery and intraocular lens (IOL) implantation. Prediction errors (directional and absolute) for each device were determined from the 1 month postoperative manifest refraction.

Results:

The directional prediction error was 0.07 ± 0.32 D for the Argos and 0.08 ± 0.34 D for the IOLMaster 700. The mean of the difference in prediction error (directional) was 0.02 D, which was not statistically significant (p > 0.05). The absolute prediction error was 0.21 ± 0.25 D for the Argos and 0.25 ± 0.24 D for the IOLMaster 700. The mean of the difference in absolute prediction error was 0.04 D, which was statistically significant (p < 0.004) but not clinically significant. The percentage of eyes with absolute prediction error ≤ 0.5 D was 91% (73 eyes) for the Argos and 88% (70 eyes) for the IOLMaster 700. This difference was not statistically significant.

Conclusion:

The prediction accuracies were similar between the Argos and IOLMaster 700 in eyes with normal axial length. There was a significant difference in mean absolute prediction error between devices; however, this was not clinically meaningful.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article