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Open Access 01-12-2024 | Research

NeoVault: empowering neonatal research through a neonate data hub

Authors: Janet Pigueiras-del-Real, Angel Ruiz-Zafra, Isabel Benavente-Fernández, Simón P. Lubián-López, Syed Adil Hussain Shah, Syed Taimoor Hussain Shah, Lionel C. Gontard

Published in: BMC Pediatrics | Issue 1/2024

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Abstract

Background

Stability during early postnatal life in preterm infants is related to better outcomes. Although vital signs are monitored continuously in Neonatal Intensive Care Unites, this monitoring does not include all physiological parameters nor data such as movement patterns. Although there are scattered sources of data, there is no centralized data hub for neonates information.

Results

We have created the first neonate data hub for easy and interactive access to upload or download postural, physiological, and medical data of neonates: NeoVault. NeoVault is a platform that provides access to information through two interfaces: 1) via a Web interface (designed for medical personnel, data scientists, researchers); and 2) via a RESTful API (Application Programming Interfaces) -designed for developers-, aiming to integrate access to information into third-party applications. The web access allows searching and filtering according to specific parameters, visualization of data through graphs and images, and generation of datasets in CSV format. Access through the RESTful API is described in OpenAPI, enabling access to information from any device, facilitating it in an interoperable format. Currently, it contains nearly 800,000 postural records and 3.000 physiological data entries. The physiological and postural data stored for each neonate in NeoVault are collected through the NRP (Neonates Recording Platform) tool, which allows for the automatic and reliable collection of data.

Conclusion

NeoVault is an open platform for simple access to postural, physiological, and medical data of neonates that can be utilized by researchers, data scientists, medical personnel, and programmers. It enables integration into third-party applications and the generation of customized datasets.
Literature
2.
go back to reference Alvarez-Garcia A, Fornieles-Deu A, Costas-Moragas C, Botet-Mussons F. Maturational changes associated with neonatal stress in preterm infants hospitalised in the NICU. J Reprod Infant Psychol. 2014;32(4):412–22.CrossRef Alvarez-Garcia A, Fornieles-Deu A, Costas-Moragas C, Botet-Mussons F. Maturational changes associated with neonatal stress in preterm infants hospitalised in the NICU. J Reprod Infant Psychol. 2014;32(4):412–22.CrossRef
3.
go back to reference Soleimani F, Azari N, Ghiasvand H, Shahrokhi A, Rahmani N, Fatollahierad S. Do NICU developmental care improve cognitive and motor outcomes for preterm infants? A systematic review and meta-analysis. BMC Pediatr. 2020;20:1–16.CrossRef Soleimani F, Azari N, Ghiasvand H, Shahrokhi A, Rahmani N, Fatollahierad S. Do NICU developmental care improve cognitive and motor outcomes for preterm infants? A systematic review and meta-analysis. BMC Pediatr. 2020;20:1–16.CrossRef
4.
go back to reference Kolb B, Harker A, Gibb R. Principles of plasticity in the developing brain. Dev Med Child Neurol. 2017;59(12):1218–23.CrossRefPubMed Kolb B, Harker A, Gibb R. Principles of plasticity in the developing brain. Dev Med Child Neurol. 2017;59(12):1218–23.CrossRefPubMed
5.
go back to reference Leo M, Bernava GM, Carcagnì P, Distante C. Video-Based Automatic Baby Motion Analysis for Early Neurological Disorder Diagnosis: State of the Art and Future Directions. Sensors. 2022;22(3):866.CrossRefPubMedPubMedCentral Leo M, Bernava GM, Carcagnì P, Distante C. Video-Based Automatic Baby Motion Analysis for Early Neurological Disorder Diagnosis: State of the Art and Future Directions. Sensors. 2022;22(3):866.CrossRefPubMedPubMedCentral
6.
go back to reference Zhao T, Griffith T, Zhang Y, Li H, Hussain N, Lester B, et al. Early-life factors associated with neurobehavioral outcomes in preterm infants during NICU hospitalization. Pediatr Res. 2022;92(6):1695–704.CrossRefPubMedPubMedCentral Zhao T, Griffith T, Zhang Y, Li H, Hussain N, Lester B, et al. Early-life factors associated with neurobehavioral outcomes in preterm infants during NICU hospitalization. Pediatr Res. 2022;92(6):1695–704.CrossRefPubMedPubMedCentral
7.
go back to reference Olmi B, Frassineti L, Lanata A, Manfredi C. Automatic Detection of Epileptic Seizures in Neonatal Intensive Care Units Through EEG, ECG and Video Recordings: A Survey. IEEE Access. 2021;9:138174–91.CrossRef Olmi B, Frassineti L, Lanata A, Manfredi C. Automatic Detection of Epileptic Seizures in Neonatal Intensive Care Units Through EEG, ECG and Video Recordings: A Survey. IEEE Access. 2021;9:138174–91.CrossRef
8.
go back to reference Pigueiras-del Real J, Gontard LC, Benavente-Fernández I, Lubián-López SP, Gallero-Rebollo E, Ruiz-Zafra A. NRP: A multi-source, heterogeneous, automatic data collection system for infants in neonatal intensive care units. IEEE J Biomed Health Inform. 2023;28(2):678–89.CrossRef Pigueiras-del Real J, Gontard LC, Benavente-Fernández I, Lubián-López SP, Gallero-Rebollo E, Ruiz-Zafra A. NRP: A multi-source, heterogeneous, automatic data collection system for infants in neonatal intensive care units. IEEE J Biomed Health Inform. 2023;28(2):678–89.CrossRef
9.
go back to reference Ruiz-Zafra A, Precioso D, Salvador B, Lubián-López SP, Jiménez J, Benavente-Fernández I, et al. NeoCam: An edge-cloud platform for non-invasive real-time monitoring in neonatal intensive care units. IEEE J Biomed Health Inform. 2023;27(6):2614–24.CrossRefPubMed Ruiz-Zafra A, Precioso D, Salvador B, Lubián-López SP, Jiménez J, Benavente-Fernández I, et al. NeoCam: An edge-cloud platform for non-invasive real-time monitoring in neonatal intensive care units. IEEE J Biomed Health Inform. 2023;27(6):2614–24.CrossRefPubMed
10.
go back to reference Pigueiras-del-Real J, Gontard LC, Lubián-López SP, Benavente-Fernández I, Ruiz-Zafra Á. Towards an AI driven early detection of brain injuries in neonates through non-contact audio and video recording. In DETERMINED. 2022. p. 122–32. Pigueiras-del-Real J, Gontard LC, Lubián-López SP, Benavente-Fernández I, Ruiz-Zafra Á. Towards an AI driven early detection of brain injuries in neonates through non-contact audio and video recording. In DETERMINED. 2022. p. 122–32.
11.
go back to reference Cabon S, Porée F, Simon A, Rosec O, Pladys P, Carrault G. Video and audio processing in paediatrics: A review. Physiol Meas. 2019;40(2):02TR02. Cabon S, Porée F, Simon A, Rosec O, Pladys P, Carrault G. Video and audio processing in paediatrics: A review. Physiol Meas. 2019;40(2):02TR02.
12.
go back to reference Carter J, Tribe RM, Sandall J, Shennan AH. The Preterm Clinical Network (PCN) Database: a web-based systematic method of collecting data on the care of women at risk of preterm birth. BMC Pregnancy Childbirth. 2018;18(1):1–9.CrossRef Carter J, Tribe RM, Sandall J, Shennan AH. The Preterm Clinical Network (PCN) Database: a web-based systematic method of collecting data on the care of women at risk of preterm birth. BMC Pregnancy Childbirth. 2018;18(1):1–9.CrossRef
13.
go back to reference Ismail L, Materwala H, Karduck AP, Adem A. Requirements of health data management systems for biomedical care and research: scoping review. J Med Internet Res. 2020;22(7):e17508.CrossRefPubMedPubMedCentral Ismail L, Materwala H, Karduck AP, Adem A. Requirements of health data management systems for biomedical care and research: scoping review. J Med Internet Res. 2020;22(7):e17508.CrossRefPubMedPubMedCentral
14.
go back to reference Samadbeik M, Fatehi F, Braunstein M, Barry B, Saremian M, Kalhor F, et al. Education and Training on Electronic Medical Records (EMRs) for health care professionals and students: A Scoping Review. Int J Med Inform. 2020;142:104238.CrossRefPubMed Samadbeik M, Fatehi F, Braunstein M, Barry B, Saremian M, Kalhor F, et al. Education and Training on Electronic Medical Records (EMRs) for health care professionals and students: A Scoping Review. Int J Med Inform. 2020;142:104238.CrossRefPubMed
18.
go back to reference Aranha VP. Multi modal stimulations to modify the neuromotor responses of hospitalized preterm infants [PhD dissertation]. Haryana: Maharishi Markandeshwar; 2019. Aranha VP. Multi modal stimulations to modify the neuromotor responses of hospitalized preterm infants [PhD dissertation]. Haryana: Maharishi Markandeshwar; 2019.
20.
go back to reference Bhat V, Bhandari V. Sex specificity in neonatal diseases. In: Principles of Gender-Specific Medicine. Elsevier; 2023. pp. 841–867. Bhat V, Bhandari V. Sex specificity in neonatal diseases. In: Principles of Gender-Specific Medicine. Elsevier; 2023. pp. 841–867.
21.
go back to reference Garfinkle J, Yoon EW, Alvaro R, Nwaesei C, Claveau M, Lee SK, et al. Trends in sex-specific differences in outcomes in extreme preterms: progress or natural barriers? Arch Dis Child-Fetal Neonatal Ed. 2020;105(2):158–63.CrossRefPubMed Garfinkle J, Yoon EW, Alvaro R, Nwaesei C, Claveau M, Lee SK, et al. Trends in sex-specific differences in outcomes in extreme preterms: progress or natural barriers? Arch Dis Child-Fetal Neonatal Ed. 2020;105(2):158–63.CrossRefPubMed
22.
go back to reference Crilly CJ, Haneuse S, Litt JS. Predicting the outcomes of preterm neonates beyond the neonatal intensive care unit: what are we missing? Pediatr Res. 2021;89(3):426–45.CrossRefPubMed Crilly CJ, Haneuse S, Litt JS. Predicting the outcomes of preterm neonates beyond the neonatal intensive care unit: what are we missing? Pediatr Res. 2021;89(3):426–45.CrossRefPubMed
23.
go back to reference Belachew A, Tewabe T. Neonatal sepsis and its association with birth weight and gestational age among admitted neonates in Ethiopia: systematic review and meta-analysis. BMC Pediatr. 2020;20:1–7.CrossRef Belachew A, Tewabe T. Neonatal sepsis and its association with birth weight and gestational age among admitted neonates in Ethiopia: systematic review and meta-analysis. BMC Pediatr. 2020;20:1–7.CrossRef
24.
go back to reference Cheung Y, Yip P, Karlberg J. Size at birth and neonatal and postneonatal mortality. Acta Paediatr. 2002;91(4):447–52.CrossRefPubMed Cheung Y, Yip P, Karlberg J. Size at birth and neonatal and postneonatal mortality. Acta Paediatr. 2002;91(4):447–52.CrossRefPubMed
25.
go back to reference J P NA, Mitsuda N, Eitoku M, Yamasaki K, Maeda N, Fujieda M, et al. Influence of chest/head circumference ratio at birth on obstetric and neonatal outcomes: the Japan environment and children’s study. Am J Hum Biol. 2023;35(6):e23875. J P NA, Mitsuda N, Eitoku M, Yamasaki K, Maeda N, Fujieda M, et al. Influence of chest/head circumference ratio at birth on obstetric and neonatal outcomes: the Japan environment and children’s study. Am J Hum Biol. 2023;35(6):e23875.
26.
go back to reference Lee KA, Hayes BC. Head size and growth in the very preterm infant: a literature review. Res Rep Neonatol. 2015;5:1–7. Lee KA, Hayes BC. Head size and growth in the very preterm infant: a literature review. Res Rep Neonatol. 2015;5:1–7.
27.
go back to reference Andegiorgish AK, Andemariam M, Temesghen S, Ogbai L, Ogbe Z, Zeng L. Neonatal mortality and associated factors in the specialized neonatal care unit Asmara. Eritrea BMC Public Health. 2020;20:1–9. Andegiorgish AK, Andemariam M, Temesghen S, Ogbai L, Ogbe Z, Zeng L. Neonatal mortality and associated factors in the specialized neonatal care unit Asmara. Eritrea BMC Public Health. 2020;20:1–9.
28.
go back to reference Desalew A, Sintayehu Y, Teferi N, Amare F, Geda B, Worku T, et al. Cause and predictors of neonatal mortality among neonates admitted to neonatal intensive care units of public hospitals in eastern Ethiopia: a facility-based prospective follow-up study. BMC Pediatr. 2020;20:1–11.CrossRef Desalew A, Sintayehu Y, Teferi N, Amare F, Geda B, Worku T, et al. Cause and predictors of neonatal mortality among neonates admitted to neonatal intensive care units of public hospitals in eastern Ethiopia: a facility-based prospective follow-up study. BMC Pediatr. 2020;20:1–11.CrossRef
29.
go back to reference Thavarajah H, Flatley C, Kumar S. The relationship between the five minute Apgar score, mode of birth and neonatal outcomes. J Matern-Fetal Neonatal Med. 2018;31(10):1335–41.CrossRefPubMed Thavarajah H, Flatley C, Kumar S. The relationship between the five minute Apgar score, mode of birth and neonatal outcomes. J Matern-Fetal Neonatal Med. 2018;31(10):1335–41.CrossRefPubMed
30.
go back to reference VieirA CA, Afiune SMRP, Portal DC, Miguel PDP, Saidah TK. Evaluation of neonatal mortality risk in the crib score application. Editorial Board. 2021;211:15–8. VieirA CA, Afiune SMRP, Portal DC, Miguel PDP, Saidah TK. Evaluation of neonatal mortality risk in the crib score application. Editorial Board. 2021;211:15–8.
32.
go back to reference Wu Q, Xu G, Wei F, Chen L, Zhang S. Rgb-d videos-based early prediction of infant cerebral palsy via general movements complexity. IEEE Access. 2021;9:42314–24.CrossRef Wu Q, Xu G, Wei F, Chen L, Zhang S. Rgb-d videos-based early prediction of infant cerebral palsy via general movements complexity. IEEE Access. 2021;9:42314–24.CrossRef
33.
go back to reference Mithal LB, Yogev R, Palac HL, Kaminsky D, Gur I, Mestan KK. Vital signs analysis algorithm detects inflammatory response in premature infants with late onset sepsis and necrotizing enterocolitis. Early Hum Dev. 2018;117:83–9.CrossRefPubMedPubMedCentral Mithal LB, Yogev R, Palac HL, Kaminsky D, Gur I, Mestan KK. Vital signs analysis algorithm detects inflammatory response in premature infants with late onset sepsis and necrotizing enterocolitis. Early Hum Dev. 2018;117:83–9.CrossRefPubMedPubMedCentral
34.
go back to reference Sullivan BA, Fairchild KD. Vital signs as physiomarkers of neonatal sepsis. Pediatr Res. 2022;91(2):273–82.CrossRefPubMed Sullivan BA, Fairchild KD. Vital signs as physiomarkers of neonatal sepsis. Pediatr Res. 2022;91(2):273–82.CrossRefPubMed
35.
go back to reference Shin HI, Shin HI, Bang MS, Kim DK, Shin SH, Kim EK, et al. Deep learning-based quantitative analyses of spontaneous movements and their association with early neurological development in preterm infants. Sci Rep. 2022;12(1):3138.CrossRefPubMedPubMedCentral Shin HI, Shin HI, Bang MS, Kim DK, Shin SH, Kim EK, et al. Deep learning-based quantitative analyses of spontaneous movements and their association with early neurological development in preterm infants. Sci Rep. 2022;12(1):3138.CrossRefPubMedPubMedCentral
36.
go back to reference Zlatanovic D, Čolović H, Živković V, Stanković A, Kostić M, Vučić J, et al. The importance of assessing general motor activity in premature infants for predicting neurological outcomes. Folia Neuropathol. 2022;60(1):427–35.CrossRefPubMed Zlatanovic D, Čolović H, Živković V, Stanković A, Kostić M, Vučić J, et al. The importance of assessing general motor activity in premature infants for predicting neurological outcomes. Folia Neuropathol. 2022;60(1):427–35.CrossRefPubMed
37.
go back to reference Shin HI, Park MW, Lee WH. Spontaneous movements as a prognostic tool of neurodevelopmental outcomes in preterm infants: A narrative review. Clin Exp Pediatr. 2023;66(11):458–64.CrossRefPubMedPubMedCentral Shin HI, Park MW, Lee WH. Spontaneous movements as a prognostic tool of neurodevelopmental outcomes in preterm infants: A narrative review. Clin Exp Pediatr. 2023;66(11):458–64.CrossRefPubMedPubMedCentral
38.
go back to reference Park MW, Shin HI, Bang MS, et al. Reduction in limb-movement complexity at term-equivalent age is associated with motor developmental delay in very-preterm or very-low-birth-weight infants. Sci Rep. 2024;14:8432.CrossRefPubMedPubMedCentral Park MW, Shin HI, Bang MS, et al. Reduction in limb-movement complexity at term-equivalent age is associated with motor developmental delay in very-preterm or very-low-birth-weight infants. Sci Rep. 2024;14:8432.CrossRefPubMedPubMedCentral
39.
go back to reference Richardson L, Ruby S. RESTful web services. O’Reilly Media, Inc.; 2008. Richardson L, Ruby S. RESTful web services. O’Reilly Media, Inc.; 2008.
40.
go back to reference Kermani F, Sheikhtaheri A, Zarkesh MR, Tahmasebian S. Risk factors for neonatal mortality in Neonatal Intensive Care Units (NICUs): a systematic literature review and comparison with scoring systems. J Pediatr Neonatal Individualized Med. 2020;9(2):e090226–e090226. Kermani F, Sheikhtaheri A, Zarkesh MR, Tahmasebian S. Risk factors for neonatal mortality in Neonatal Intensive Care Units (NICUs): a systematic literature review and comparison with scoring systems. J Pediatr Neonatal Individualized Med. 2020;9(2):e090226–e090226.
41.
go back to reference Mangold C, Zoretic S, Thallapureddy K, Moreira A, Chorath K, Moreira A. Machine learning models for predicting neonatal mortality: a systematic review. Neonatology. 2021;118(4):394–405.CrossRefPubMed Mangold C, Zoretic S, Thallapureddy K, Moreira A, Chorath K, Moreira A. Machine learning models for predicting neonatal mortality: a systematic review. Neonatology. 2021;118(4):394–405.CrossRefPubMed
42.
go back to reference Laskey KB, Laskey K. Service oriented architecture. Wiley Interdiscip Rev Comput Stat. 2009;1(1):101–5.CrossRef Laskey KB, Laskey K. Service oriented architecture. Wiley Interdiscip Rev Comput Stat. 2009;1(1):101–5.CrossRef
Metadata
Title
NeoVault: empowering neonatal research through a neonate data hub
Authors
Janet Pigueiras-del-Real
Angel Ruiz-Zafra
Isabel Benavente-Fernández
Simón P. Lubián-López
Syed Adil Hussain Shah
Syed Taimoor Hussain Shah
Lionel C. Gontard
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Pediatrics / Issue 1/2024
Electronic ISSN: 1471-2431
DOI
https://doi.org/10.1186/s12887-024-05276-y

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