Abstract

SO.12.10

Adapting the correction factor – a long-term study

Herschel D., Höh H. 
Dietrich-Bonhoeffer-Klinikum Neubrandenburg

Objective: A-constants require a location-dependent correction factor (CF) to more accurately compute the optical power of intra-ocular lenses (IOL). To study the stability of the CF, we studied all eyes that were implanted the silicon lens Acriflex 414 (now: Lentis L-200, Fa. Wave Light AG, Erlangen) at the Dietrich-Bonhoeffer-Klinikum within a two year period.
Methods: Our study considers 1023 eyes that underwent surgery due to a cataract between Oct. 2002 and Sept. 2004. We collected pre-operative and post-operative data, target refraction, etc. For our retrospective data analysis, we considered 839 eyes (f=490, m=349) of 594 patients in the age of 19 to 94. The IOL implantation into the capsular bag was continuously performed by the same surgeon, who used the CCC method. The target refraction was computed after ultrasonic (US)-biometry with the SRK-II-formula, considering an A-constant equal to 118. We computed the CF as the difference between the target refraction and the post-operative refraction.
Results: The cumulation of CF averages in our long term study graphically showed two significant steps, which separate three blocks. The second step can be explained by a repair of the US-biometry device in Jan. 2004. For varying axial length, we determined a CF of -0.45dpt for small eyes (<22mm, n=82), a CF of -0.38dpt for eyes of medium size (³22mm & <24.5mm, n=724), and a CF equal to -0.06dpt for large eyes (³24.5mm, n=33). For the three blocks observed when cumulating CF averages, we obtained CF(I) = -0.77dpt (n=80), CF(II) = -0.48dpt (n=340), and CF(III) = -0.21dpt (n=419). We thus observe that the CF varied twice by at least 0.2dpt during the period we considered.
Conclusions: Our results show that a unique verification of the correction factor of the so called A-constant is not sufficient in practice to make accurate assertions. We therefore suggest a recurring verification, especially after events such as device maintenance, employee changes, etc. A periodic optimization is also sensible, as no such event could be attributed to the first step in our study.

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