Value of different calculation methods for weight growth velocity in predicting long-term neurological and physical development outcomes in preterm infants
JI Pei-Hong, SUN Xuan, GAO Jin-Zhi, CHEN Ling
Department of Neonatology,Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Abstract：Objective To investigate the value of weight growth velocity, calculated using the Patel exponential model and the Z-score change method, in predicting the neurological and physical development outcomes of preterm infants with a gestational age of <30 weeks in the long term. Methods A retrospective study was conducted involving preterm infants with a gestational age of <30 weeks who were hospitalized and treated in the Department of Neonatology at Tongji Hospital, Huazhong University of Science and Technology, from January 2017 to June 2022, and were followed up at the outpatient service more than 18 months of age. The preterm infants were divided into high and low rate groups based on the two calculation methods, and the two methods were compared regarding their predictive value for neurological and physical development outcomes in the long term. Results The average age of the last follow-up was (23.0±3.6) months. For neurological development, according to the Patel exponential model, the low rate group exhibited a significantly higher abnormal rate in the fine motor domain compared to the high rate group (P<0.05). Using the Z-score change method, the low rate group had significantly higher abnormal rates in both gross motor and fine motor domains, and significantly lower developmental quotients for gross motor, fine motor, and adaptive behavior domains compared to the high rate group (P<0.05). For physical development, there were no significant differences in body length, body weight, head circumference, or the incidence rate of growth restriction between the low rate and high rate groups identified by either method (P>0.05). Conclusions Weight growth velocity calculated using the Z-score change method is more effective in predicting long-term neurological outcomes in preterm infants, while weight growth velocity derived from both methods shows no significant association with long-term physical development outcomes.
JI Pei-Hong,SUN Xuan,GAO Jin-Zhi et al. Value of different calculation methods for weight growth velocity in predicting long-term neurological and physical development outcomes in preterm infants[J]. CJCP, 2025, 27(2): 165-170.
Ehrenkranz RA, Dusick AM, Vohr BR, et al. Growth in the neonatal intensive care unit influences neurodevelopmental and growth outcomes of extremely low birth weight infants[J]. Pediatrics, 2006, 117(4): 1253-1261. PMID: 16585322. DOI: 10.1542/peds.2005-1368.
Sériès T, Guillot M, Angoa G, et al. Does growth velocity affect associations between birth weight and neurodevelopment for infants born very preterm?[J]. J Pediatr, 2023, 260: 113531. PMID: 37268036. DOI: 10.1016/j.jpeds.2023.113531.
Fenton TR, Chan HT, Madhu A, et al. Preterm infant growth velocity calculations: a systematic review[J]. Pediatrics, 2017, 139(3): e20162045. PMID: 28246339. DOI: 10.1542/peds.2016-2045.
Patel AL, Engstrom JL, Meier PP, et al. Accuracy of methods for calculating postnatal growth velocity for extremely low birth weight infants[J]. Pediatrics, 2005, 116(6): 1466-1473. PMID: 16322172. DOI: 10.1542/peds.2004-1699.
Zozaya C, Díaz C, Saenz de Pipaón M. How should we define postnatal growth restriction in preterm infants?[J]. Neonatology, 2018, 114(2): 177-180. PMID: 29920494. DOI: 10.1159/000489388.
El Rafei R, Maier RF, Jarreau PH, et al. Postnatal growth restriction and neurodevelopment at 5 years of age: a European extremely preterm birth cohort study[J]. Arch Dis Child Fetal Neonatal Ed, 2023, 108(5): 492-498. PMID: 36868809. DOI: 10.1136/archdischild-2022-324988.
Papageorghiou AT, Ohuma EO, Altman DG, et al. International standards for fetal growth based on serial ultrasound measurements: the fetal growth longitudinal study of the INTERGROWTH-21st project[J]. Lancet, 2014, 384(9946): 869-879. PMID: 25209488. DOI: 10.1016/S0140-6736(14)61490-2.
Wang N, Zhang J, Yu Z, et al. Evaluation of nutrition status of very preterm infants in neonatal intensive care units using different growth indicators[J]. Nutr Clin Pract, 2021, 36(6): 1312-1319. PMID: 34339517. DOI: 10.1002/ncp.10741.
Kim SY, Kim EK, Song H, et al. Association of brain microstructure and functional connectivity with cognitive outcomes and postnatal growth among early school-aged children born with extremely low birth weight[J]. JAMA Netw Open, 2023, 6(3): e230198. PMID: 36862414. PMCID: PMC9982697. DOI: 10.1001/jamanetworkopen.2023.0198.
