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The Effect of Preoperative Biometry and IntraOcular Lens Fixation Site on Postoperative Effective Le

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Title: The Effect of Preoperative Biometry and IntraOcular Lens Fixation Site on Postoperative Effective Le


1
The Effect of Pre-operative Biometry and
Intra-Ocular Lens Fixation Site on Postoperative
Effective Lens Position in Cataract Surgery
  • Golnaz Javey, MD Christopher T. Leffler, MD, MPH
    Krishna Mukkamala, BSMuneera A. Mahmood, MD,
    FRCOphth
  • Hunter Holmes McGuire VA Medical Center
  • Virginia Commonwealth University School of
    MedicineRichmond, Virginia

2
  • Purpose
  • To more accurately predict the deviation from
    the expected lens position (?dELP), calculated as
    the difference between the observed effective
    lens position (dELP) and expected effective lens
    position (dELP0) as predicted by the manufacturer
    (?dELP dELP dELP0) for in-the-bag or
    sulcus fixated intraocular lenses (IOL). We
    sought to optimize postoperative refraction
    predictions for our surgical methods including
    preoperative immersion biometry measurements, and
    predominant use of the single-piece acrylic Alcon
    SA60AT lens.
  • Study Design
  • Retrospective study of 186 consecutive eyes that
    underwent phacoemulsification for visually
    significant cataract with capsular bag or sulcus
    IOL fixation at Hunter Holmes McGuire Veterans
    Administration Medical Center.
  • Exclusion Criteria
  • Pre-operative ocular co-morbidities
  • Intra-operative complications
  • Post-operative macular edema
  • Incomplete post-operative follow up
  • IOL dislocation
  • Post-operative best corrected visual acuity of
    less than 20/60

3
Methods
  • For each eye, post-operative effective thin-lens
    position (dELP) was calculated based on
    pre-operative biometry and post-operative
    refraction using Holladays method (1997).
  • For each IOL, the lens A constant was converted
    to the expected effective thin-lens position
    (dELP0) using a previously observed empiric
    relation (Holladay 1997).
  • ?dELP was calculated for each case and predicted
    by multiple linear regression using pre-operative
    variables including age, refraction, corneal
    curvature, and site of IOL fixation, as well as
    axial length, anterior chamber depth, and
    posterior lens capsule position as measured by
    immersion A-scan biometry.
  • The ability of the regression equation to predict
    post-operative refraction was compared with
    established methods.

4
Biometric and refractive patient
characteristics.
Intraocular lenses used
5
Predictors of Deviation from Effective Expected
Lens Position.
6
Results
  • Axial length (AL), anterior chamber depth, age,
    and sulcus fixation were univariate predictors of
    ?dELP (all p 0.002).
  • In multivariable analyses of in-the-bag cases,
    age, AL, and mean corneal radius of curvature
    (rmean) were statistically significant in
    predicting dELP (all p 0.002).
  • Corneal radius of curvature in the vertical
    meridian (r90) was retained in models of
    in-the-bag cases when only biometric variables
    were included and in analysis of combined
    capsular bag and sulcus fixated IOLs.

7
Unpredicted Postoperative Refractive Error For
In-the-Bag Fixated IOLs.
Error Actual Refraction Predicted
Refraction. Actual postoperative refraction
Slope (Predicted Refraction) Intercept.
8
Results
  • The mean absolute unpredicted post-operative
    refractive error was reduced when utilizing our
    equation as compared to predictions by SRK/T,
    Haigis, or Holladay formula.
  • The fraction of variance in post-operative
    refraction by the current method (0.10) was
    higher than for the Haigis (0.06), Holladay
    (0.03), or SRK-T (0.02) equations.
  • The actual post-operative refraction was slightly
    more myopic than predicted by the Holladay and
    Haigis equations.

9
Prediction of Postoperative Refraction by SRK-T
Rormula
10
Prediction of Postoperative Refraction by Novel
Equation
11
Conclusions
  • Age, axial length, and mean corneal radius were
    important predictors of effective lens position.
  • Vertical corneal curvature may also have value in
    predicting the effective lens position of
    capsular bag and sulcus fixated IOLs.
  • Accurate prediction of lens position results in
    reduction of post-operative refractive error.

12
References
  • Haigis W. The Haigis formula. In Shammas HJ, ed.
    Intraocular Lens Power Calculations. Thorofare,
    NJ, Slack, 2004 41-57.
  • Olsen T, Olsen H, Thim K, Corydon L. Prediction
    of postoperative intraocular lens chamber depth.
    J Cataract Refract Surg 1990 16587-590.
  • Olsen T, Olsen H, Thim K, Corydon L. Prediction
    of pseudophakic anterior chamber depth with the
    newer IOL calculation formulas. J Cataract
    Refract Surg 1992 18280-285.
  • Olsen T, Corydon L, Gimbel H. Intraocular lens
    power calculation with an improved anterior
    chamber depth prediction algorithm. J Cataract
    Refract Surg 1995 21313-319.
  • Olsen T. The Olsen formula. In Shammas HJ, ed.
    Intraocular Lens Power Calculations. Thorofare,
    NJ, Slack, 2004 27-38.
  • Kriechbaum K, Findl O, Preussner P, Koppl C, Wahl
    J, Drexler W. Determining postoperative anterior
    chamber depth. J Cataract Refract Surg 2003
    292122-2126.
  • Olsen T, Corydon L, Gimbel H. Intraocular lens
    power calculation with an improved anterior
    chamber depth prediction algorithm. J Cataract
    Refract Surg 1995 21313-319.
  • Holladay JT. Standardizing constants for
    ultrasonic biometry, keratometry, and intraocular
    lens power calculations. J Cataract Refract Surg
    1997 231356-1370.
  • Retzlaff JA, Sanders Dr, Draff MC. Development
    of the SRK/T intraocular lens implant power
    calculation formula. J Cataract Refract Surg
    1990 16333-340.
  • Olsen, T. Prediction of the effective
    postoperative (intraocular lens) anterior chamber
    depth. J Cataract Refract Surg 2006 32419-424.
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