Prediction of axial length on the basis of vitreous body length and lens thickness: retrospective echobiometric study.
OBJECTIVE
To examine the predictability of axial length measurement when lens thickness and vitreous body length are known.


METHODS
Center of Ophthalmology, University of Cologne, Cologne, Germany.


METHODS
This study comprised 227 patients with a mean age of 70.01 years +/- 12.47 (SD). None of the eyes examined had a history of surgery or trauma. Patients with systemic disease were excluded from the study. Before cataract surgery, the length of the vitreous body and thickness of the lens were measured and the correlation between these data and the axial length was evaluated. Two ultrasonic devices were used for biometric measurements: the BMS 811 Biometric System (Grieshaber) and the Cooper Vision Ultrascan Digital A+B-Scan 2000. The correlations between the axial length and vitreous body length and the lens thickness and vitreous body length were analyzed using multiple linear regression.


RESULTS
The BMS 811 provided the best prediction of axial length based on vitreous body length. Considering sex but not age significantly improved the model fit. With the BMS 811, the following formula was developed to predict axial length: Axial length (mm) = 7.129 mm + 0.095 mm x sex (female = 0, male = 1) + 1.040 x vitreous body length (mm). An approximate 95% prediction limit may be calculated by the following formula: Axial length (mm) +/- 2 x 0.413 mm.


CONCLUSIONS
This study yielded an easy-to-use formula for predicting the axial length using the vitreous body length and the patient's sex. The remaining error in prediction is likely to be the result of patient heterogeneity in age, ocular globe size, and lens thickness (cataract formation). Good prediction of the axial length is important to refractive outcomes to distinguish corneal myopia from axial length myopia to choose grafts and the opening size in penetrating keratoplasty. Further studies to detect a clinically relevant improvement in such outcomes are required to assess the utility of the prediction formula.
Roters
Sigrid
S
Department of Ophthalmology, University of Cologne, Cologne, Germany.
Hellmich
Martin
M
Szurman
Peter
P
D000368:Aged; D000465:Algorithms; D001699:Biometry / Q000379:methods*; D001837:Body Weights and Measures / Q000706:statistics & numerical data*; D005123:Eye / Q000033:anatomy & histology; D005260:Female; D006801:Humans; D007908:Lens, Crystalline / Q000033:anatomy & histology*; D008297:Male; D012189:Retrospective Studies; D014822:Vitreous Body / Q000033:anatomy & histology*