Am J Perinatol 2022; 39(06): 677-682
DOI: 10.1055/s-0040-1718877
Original Article

Longitudinal Analysis of Continuous Pulse Oximetry as Prognostic Factor in Neonatal Respiratory Distress

1   Department of Neonatology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Elena Maderuelo-Rodríguez
1   Department of Neonatology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Teresa Perez-Pérez
2   Department of Statistics, Universidad Complutense de Madrid, Madrid, Spain
,
Laura Torres-Soblechero
1   Department of Neonatology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Ana Gutiérrez-Vélez
1   Department of Neonatology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Cristina Ramos-Navarro
1   Department of Neonatology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Raúl López-Martínez
3   Information Technology Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Manuel Sánchez-Luna
1   Department of Neonatology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
› Author Affiliations

Abstract

Objective Analysis of longitudinal data can provide neonatologists with tools that can help predict clinical deterioration and improve outcomes. The aim of this study is to analyze continuous monitoring data in newborns, using vital signs to develop predictive models for intensive care admission and time to discharge.

Study Design We conducted a retrospective cohort study, including term and preterm newborns with respiratory distress patients admitted to the neonatal ward. Clinical and epidemiological data, as well as mean heart rate and saturation, at every minute for the first 12 hours of admission were collected. Multivariate mixed, survival and joint models were developed.

Results A total of 56,377 heart rate and 56,412 oxygen saturation data were analyzed from 80 admitted patients. Of them, 73 were discharged home and 7 required transfer to the intensive care unit (ICU). Longitudinal evolution of heart rate (p < 0.01) and oxygen saturation (p = 0.01) were associated with time to discharge, as well as birth weight (p < 0.01) and type of delivery (p < 0.01). Longitudinal heart rate evolution (p < 0.01) and fraction of inspired oxygen at admission at the ward (p < 0.01) predicted neonatal ICU (NICU) admission.

Conclusion Longitudinal evolution of heart rate can help predict time to transfer to intensive care, and both heart rate and oxygen saturation can help predict time to discharge. Analysis of continuous monitoring data in patients admitted to neonatal wards provides useful tools to stratify risks and helps in taking medical decisions.

Key Points

  • Continuous monitoring of vital signs can help predict and prevent clinical deterioration in neonatal patients.

  • In our study, longitudinal analysis of heart rate and oxygen saturation predicted time to discharge and intensive care admission.

  • More studies are needed to prospectively prove that these models can helpmake clinical decisions and stratify patients' risks.



Publication History

Received: 21 June 2020

Accepted: 15 September 2020

Article published online:
19 October 2020

© 2020. Thieme. All rights reserved.

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333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 
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