Newborn skin reflection: Proof of concept for a new approach for predicting gestational age at birth. A cross-sectional study

Abstract

Background: Current methods to assess the gestational age during prenatal care or at birth are a global challenge. Disadvantages, such as low accessibility, high costs, and imprecision of clinical tests and ultrasonography measurements, may compromise health decisions at birth, based on the gestational age. Newborns' organs and tissues can indirectly indicate their physical maturity, and we hypothesized that evolutionary changes in their skin, detected using an optoelectronic device meter, may aid in estimating the gestational age. This study analyzed the feasibility of using newborn skin reflectance to estimate the gestational age at birth noninvasively.

Methods and findings: A cross-sectional study evaluated the skin reflectance of selected infants, preferably premature, at birth. The first-trimester ultrasound was the reference for gestational age. A prototype of a new noninvasive optoelectronic device measured the backscattering of light from the skin, using a light emitting diode at wavelengths of 470 nm, 575 nm, and 630 nm. Univariate and multivariate regression analysis models were employed to predict gestational age, combining skin reflectance with clinical variables for gestational age estimation. The gestational age at birth of 115 newborns from 24.1 to 41.8 weeks of gestation correlated with the light at 630 nm wavelength reflectance 3.3 mm/6.5 mm ratio distant of the sensor, at the forearm and sole (Pearson's correlation = 0.505, P < 0.001 and 0.710, P < 0.001, respectively). The best-combined variables to predict the gold standard gestational age at birth was the skin reflectance at wavelengths of 630 nm and 470 nm in combination with birth weight, phototherapy, and adjusted to include incubator stay, and sex (R2 = 0.828, P < 0.001). The main limitation of the study is that it was very specific to the premature population we studied and needs to be studied in a broader spectrum of newborns.

Conclusions: A novel automated skin reflectometer device, in combination with clinical variables, was able to predict the gestational age and could be useful when the information is in doubt or is unknown. Multivariable predictive models associated the skin reflectance with easy to obtain clinical parameters, at the birth scenario. External validation needs to be proven in an actual population with the real incidence of premature infants.

Fig 1. Prototype of the sensor probe.

(A) Exploded perspective drawing of optoelectronic components fitting in the cover probe. (B) 3D illustration of the second version of the sensor module. Note: Exact positions between the LEDs and photodiode, in the middle of the sensor are: Red 1 = 3.3 mm; Red 2 = 6.5 mm; Green 1 = 4.0 mm; Green 2 = 7.2 mm; Blue 1 = 3.3 mm; Blue 2 = 6.5 mm.

Fig 2. Gestational age distribution in the selected sample of newborns.

This was calculated by using the gold standard approach [4]. Normal distribution (Kolmogorov-Smirnov > 5%).

Fig 3. Gestational age estimated by the skin reflectance, during the first day of life, at the skin of the sole of foot vs. gestational age by early obstetric ultrasound.

Fig 4. Standard deviation of residual values and histogram of residual value for the skin reflectance vs. gestational age.

(A) Residual values (B) Histogram of residual values. This was during the first day of life, at the skin of the sole of the foot.

Fig 5. Title gestational age estimated by the multivariate model vs. gestational age by the early obstetric ultrasound.

Fig 6. Standard deviation of residual values and histogram of residual value for the best multivariate model vs. gestational age.

(A) Residual values (B) Histogram of residual values. This was during the first day of life, at the skin of the sole of the foot.

Fig 7. The skin reflectance versus gestational age comparing different studies.

Cross symbol is the current reflectance data over the sole, at R₆₃₀ 3.3; Dot symbol represents data by Lynn at al. [17]. The line is the correspondent reflectance equation fitted on our data: GA = 45.6 − 51.9*R₆₃₀.