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Toward personalized medicine for pharmacological interventions in neonates using vital signs
Vital signs, such as heart rate and oxygen saturation, are continuously monitored for infants in neonatal care units. Pharmacological interventions can alter an infant's vital signs, either as an intended effect or as a side effect, and consequently could provide an approach to explore the wide...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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John Wiley and Sons Inc.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8937573/ https://www.ncbi.nlm.nih.gov/pubmed/35372840 http://dx.doi.org/10.1002/pne2.12065 |
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author | Hartley, Caroline |
author_facet | Hartley, Caroline |
author_sort | Hartley, Caroline |
collection | PubMed |
description | Vital signs, such as heart rate and oxygen saturation, are continuously monitored for infants in neonatal care units. Pharmacological interventions can alter an infant's vital signs, either as an intended effect or as a side effect, and consequently could provide an approach to explore the wide variability in pharmacodynamics across infants and could be used to develop models to predict outcome (efficacy or adverse effects) in an individual infant. This will enable doses to be tailored according to the individual, shifting the balance toward efficacy and away from the adverse effects of a drug. Pharmacological analgesics are frequently not given in part due to the risk of adverse effects, yet this exposes infants to the short‐ and long‐term effects of painful procedures. Personalized analgesic dosing will be an important step forward in providing safer effective pain relief in infants. The aim of this paper was to describe a framework to develop predictive models of drug outcome from analysis of vital signs data, focusing on analgesics as a representative example. This framework investigates changes in vital signs in response to the analgesic (prior to the painful procedure) and proposes using machine learning to examine if these changes are predictive of outcome—either efficacy (with pain response measured using a multimodal approach, as changes in vital signs alone have limited sensitivity and specificity) or adverse effects. The framework could be applied to both preterm and term infants in neonatal care units, as well as older children. Sharing vital signs data are proposed as a means to achieve this aim and bring personalized medicine rapidly to the forefront in neonatology. |
format | Online Article Text |
id | pubmed-8937573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89375732022-03-31 Toward personalized medicine for pharmacological interventions in neonates using vital signs Hartley, Caroline Paediatr Neonatal Pain Review Articles Vital signs, such as heart rate and oxygen saturation, are continuously monitored for infants in neonatal care units. Pharmacological interventions can alter an infant's vital signs, either as an intended effect or as a side effect, and consequently could provide an approach to explore the wide variability in pharmacodynamics across infants and could be used to develop models to predict outcome (efficacy or adverse effects) in an individual infant. This will enable doses to be tailored according to the individual, shifting the balance toward efficacy and away from the adverse effects of a drug. Pharmacological analgesics are frequently not given in part due to the risk of adverse effects, yet this exposes infants to the short‐ and long‐term effects of painful procedures. Personalized analgesic dosing will be an important step forward in providing safer effective pain relief in infants. The aim of this paper was to describe a framework to develop predictive models of drug outcome from analysis of vital signs data, focusing on analgesics as a representative example. This framework investigates changes in vital signs in response to the analgesic (prior to the painful procedure) and proposes using machine learning to examine if these changes are predictive of outcome—either efficacy (with pain response measured using a multimodal approach, as changes in vital signs alone have limited sensitivity and specificity) or adverse effects. The framework could be applied to both preterm and term infants in neonatal care units, as well as older children. Sharing vital signs data are proposed as a means to achieve this aim and bring personalized medicine rapidly to the forefront in neonatology. John Wiley and Sons Inc. 2021-11-22 /pmc/articles/PMC8937573/ /pubmed/35372840 http://dx.doi.org/10.1002/pne2.12065 Text en © 2021 The Authors. Paediatric and Neonatal Pain published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Articles Hartley, Caroline Toward personalized medicine for pharmacological interventions in neonates using vital signs |
title | Toward personalized medicine for pharmacological interventions in neonates using vital signs |
title_full | Toward personalized medicine for pharmacological interventions in neonates using vital signs |
title_fullStr | Toward personalized medicine for pharmacological interventions in neonates using vital signs |
title_full_unstemmed | Toward personalized medicine for pharmacological interventions in neonates using vital signs |
title_short | Toward personalized medicine for pharmacological interventions in neonates using vital signs |
title_sort | toward personalized medicine for pharmacological interventions in neonates using vital signs |
topic | Review Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8937573/ https://www.ncbi.nlm.nih.gov/pubmed/35372840 http://dx.doi.org/10.1002/pne2.12065 |
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