Abstract
Purpose :
During emmetropization the refractive components of the eye change shape and position over a period of several years in order to optimize ocular refraction towards a value of about +1D. This work reports the ocular biometry in a group of newborn infants aged 1 – 7 days, before emmetropization has taken place, derived from a number of sources in the literature.
Methods :
The newborn biometry was obtained from several sources (Gernet 1964, Luyckx 1966, Insler 1987, Blomdahl 1979, Axer-Siegel 2007), leading to a combined set of 302 eyes. All infants were reported as full-term with gestational ages between 36 and 42 weeks, and measured within 7 days after birth. All sources reported using ultrasound biometry (for axial length L, total anterior chamber depth ACD and lens thickness LT), keratometry (anterior corneal curvature Rca) and hand-held retinoscopy after cycloplegia (refraction SE). From these data the lens power PL and curvature was estimated using the Bennett and Royston equations, respectively. Full records were available for 59/302 eyes, all others had partial records.
Results :
The mean biometry values were SE = 2.55 ± 1.39 D, Rca = 7.07 ± 0.38 mm, ACD = 2.30 ± 0.15 mm, L = 17.15 ± 0.67 mm, and PL = 49.91 ± 3.29 D. The axial length L at birth was significantly correlated with birth weight (Spearman r = 0.443, p < 0.001), SE (r = -0.298, p < 0.001), Rca (r = -0.505, p < 0.001), ACD (r = 0.595, p < 0.001) and PL (r = -0.664, p < 0.001). Corneal curvature Rca was significantly correlated with birth length (r = 0.470, p < 0.001) and birth weight (r = 0.532, p < 0.001). Gestational age was significantly correlated with L (r = 0.362, p = 0.003) and ACD (r = 0.425, p < 0.001).
Conclusions :
These observations are consistent with the notion that at birth most ocular parameters are scalable with respect to axial length, which in turn is associated with gestational age. The values presented may be used as a pre-emmetropization reference for future studies and could be used to develop a newborn eye model.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.