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Prediction of the complicated early neonatal period in large for gestational age newborns

https://doi.org/10.29235/1814-6023-2022-19-1-19-26

Abstract

The aim of the study is to develop a method for predicting the complicated course of the early neonatal period in the large newborns for gestational age in order to optimize and increase the efficiency of medical care for this category of children.

A survey of 157 large newborns large for gestational age was carried out. The study group consisted of 105 large newborns for gestational age. The control of the correct operation of the regression model was carried out on an examination sample of children with large birth weight (n = 52). The control group consisted of 221 newborns with the physical development corresponding to the gestational age (appropriate for the gestational age). The anamnestic, clinical, laboratory, instrumental, morphological data were analyzed with a subsequent determination of the most significant factors associated with early adaptation disorders in newborns. The predicted event was considered to be a complicated course of the early neonatal period, which was determined by the presence of one or more diseases in a newborn.

Based on the multivariate regression analysis, it was found that the most significant prognostic factors associated with the disadaptation risk of large newborns were the pregravid maternal body weight of more than 70 kg, the delivery mode, the harmonicity coefficient (ponderal index) at a birth of 26.5 kg/m3 or more, the neutrophils level in the complete blood count on the 1-2 days of life. A mathematical model was developed for determining the probability of a complicated course of the early neonatal period in the large newborns large for gestational age. The threshold value was calculated and a classification scheme was created, allowing one to calculate the infant's belonging to the risk group of the complicated course of the early neonatal period based on the calculation of points for timely correction. It is shown that the developed multivariate mathematical model and the classification scheme based on it work steadily on the examination sample and can be used in practice in health care organizations at all levels of perinatal care.

About the Authors

V. A. Prylutskaya
Belarusian State Medical University
Belarus

Veranika A. Prylutskaya - Ph. D. (Med.), Associate Professor, Belarusian State Medical University.

83, Dzerzhinski Ave., 220116, Minsk.



A. V. Sukalo
Belarusian State Medical University
Belarus

Alexander V. Sukalo - Academician, D. Sc. (Med.), Professor, Head of the Department, Belarusian State Medical University.

83, Dzerzhinski Ave., 220116, Minsk.



References

1. Chiavaroli V., Derraik J. G., Hofman P. L., Cutfield W. S. Born large for gestational age: bigger is not always better. Journal of Pediatrics, 2016, vol. 170, pp. 307-311. https://doi.org/10.1016/j.jpeds.2015.11.043

2. Mengistu T. S., Schreiber V., Flatley C., Fox J., Kumar S. Factors associated with increased risk of early severe neonatal morbidity in late preterm and early term infants. Journal of Clinical Medicine, 2021, vol. 10, no. 6, art. 1319. https://doi.org/10.3390/jcm10061319

3. Sukalo A. V., Elinevskaya G. F., Prylutskaya V. A. Large for gestational age newborns: prospects for physical development and health. Minsk, Belaruskaya navuka Publ., 2016. 87 p. (in Russian).

4. The Global Health network. Available at : https://intergrowth21.tghn.org/standards-tools/ (accessed 25.05.2021).

5. Lang T. A., Sesik M. How to report statistics in medicine. Moscow, Prakticheskaya meditsina Publ., 2011. 480 p. (in Russian).

6. Petri A., Sebin K. Medical Statistics at a Glance. 3nd ed. Moscow, GEOTAR-Media Publ., 2019. 216 p. (in Russian).


Review

For citations:


Prylutskaya V.A., Sukalo A.V. Prediction of the complicated early neonatal period in large for gestational age newborns. Proceedings of the National Academy of Sciences of Belarus, Medical series. 2022;19(1):19-26. (In Russ.) https://doi.org/10.29235/1814-6023-2022-19-1-19-26

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ISSN 1814-6023 (Print)
ISSN 2524-2350 (Online)