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Video-Based versus On-Site Neonatal Pain Assessment in Neonatal Intensive Care Units: The Impact of Video-Based Neonatal Pain Assessment in Real-World Scenario on Pain Diagnosis and Its Artificial Intelligence Application

Background: Neonatal pain assessment (NPA) represents a huge global problem of essential importance, as a timely and accurate assessment of neonatal pain is indispensable for implementing pain management. Purpose: To investigate the consistency of pain scores derived through video-based NPA (VB-NPA)...

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Autores principales: Chen, Xiaofei, Zhu, Huaiyu, Mei, Linli, Shu, Qi, Cheng, Xiaoying, Luo, Feixiang, Zhao, Yisheng, Chen, Shuohui, Pan, Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453072/
https://www.ncbi.nlm.nih.gov/pubmed/37627921
http://dx.doi.org/10.3390/diagnostics13162661
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author Chen, Xiaofei
Zhu, Huaiyu
Mei, Linli
Shu, Qi
Cheng, Xiaoying
Luo, Feixiang
Zhao, Yisheng
Chen, Shuohui
Pan, Yun
author_facet Chen, Xiaofei
Zhu, Huaiyu
Mei, Linli
Shu, Qi
Cheng, Xiaoying
Luo, Feixiang
Zhao, Yisheng
Chen, Shuohui
Pan, Yun
author_sort Chen, Xiaofei
collection PubMed
description Background: Neonatal pain assessment (NPA) represents a huge global problem of essential importance, as a timely and accurate assessment of neonatal pain is indispensable for implementing pain management. Purpose: To investigate the consistency of pain scores derived through video-based NPA (VB-NPA) and on-site NPA (OS-NPA), providing the scientific foundation and feasibility of adopting VB-NPA results in a real-world scenario as the gold standard for neonatal pain in clinical studies and labels for artificial intelligence (AI)-based NPA (AI-NPA) applications. Setting: A total of 598 neonates were recruited from a pediatric hospital in China. Methods: This observational study recorded 598 neonates who underwent one of 10 painful procedures, including arterial blood sampling, heel blood sampling, fingertip blood sampling, intravenous injection, subcutaneous injection, peripheral intravenous cannulation, nasopharyngeal suctioning, retention enema, adhesive removal, and wound dressing. Two experienced nurses performed OS-NPA and VB-NPA at a 10-day interval through double-blind scoring using the Neonatal Infant Pain Scale to evaluate the pain level of the neonates. Intra-rater and inter-rater reliability were calculated and analyzed, and a paired samples t-test was used to explore the bias and consistency of the assessors’ pain scores derived through OS-NPA and VB-NPA. The impact of different label sources was evaluated using three state-of-the-art AI methods trained with labels given by OS-NPA and VB-NPA, respectively. Results: The intra-rater reliability of the same assessor was 0.976–0.983 across different times, as measured by the intraclass correlation coefficient. The inter-rater reliability was 0.983 for single measures and 0.992 for average measures. No significant differences were observed between the OS-NPA scores and the assessment of an independent VB-NPA assessor. The different label sources only caused a limited accuracy loss of 0.022–0.044 for the three AI methods. Conclusion: VB-NPA in a real-world scenario is an effective way to assess neonatal pain due to its high intra-rater and inter-rater reliability compared to OS-NPA and could be used for the labeling of large-scale NPA video databases for clinical studies and AI training.
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spelling pubmed-104530722023-08-26 Video-Based versus On-Site Neonatal Pain Assessment in Neonatal Intensive Care Units: The Impact of Video-Based Neonatal Pain Assessment in Real-World Scenario on Pain Diagnosis and Its Artificial Intelligence Application Chen, Xiaofei Zhu, Huaiyu Mei, Linli Shu, Qi Cheng, Xiaoying Luo, Feixiang Zhao, Yisheng Chen, Shuohui Pan, Yun Diagnostics (Basel) Article Background: Neonatal pain assessment (NPA) represents a huge global problem of essential importance, as a timely and accurate assessment of neonatal pain is indispensable for implementing pain management. Purpose: To investigate the consistency of pain scores derived through video-based NPA (VB-NPA) and on-site NPA (OS-NPA), providing the scientific foundation and feasibility of adopting VB-NPA results in a real-world scenario as the gold standard for neonatal pain in clinical studies and labels for artificial intelligence (AI)-based NPA (AI-NPA) applications. Setting: A total of 598 neonates were recruited from a pediatric hospital in China. Methods: This observational study recorded 598 neonates who underwent one of 10 painful procedures, including arterial blood sampling, heel blood sampling, fingertip blood sampling, intravenous injection, subcutaneous injection, peripheral intravenous cannulation, nasopharyngeal suctioning, retention enema, adhesive removal, and wound dressing. Two experienced nurses performed OS-NPA and VB-NPA at a 10-day interval through double-blind scoring using the Neonatal Infant Pain Scale to evaluate the pain level of the neonates. Intra-rater and inter-rater reliability were calculated and analyzed, and a paired samples t-test was used to explore the bias and consistency of the assessors’ pain scores derived through OS-NPA and VB-NPA. The impact of different label sources was evaluated using three state-of-the-art AI methods trained with labels given by OS-NPA and VB-NPA, respectively. Results: The intra-rater reliability of the same assessor was 0.976–0.983 across different times, as measured by the intraclass correlation coefficient. The inter-rater reliability was 0.983 for single measures and 0.992 for average measures. No significant differences were observed between the OS-NPA scores and the assessment of an independent VB-NPA assessor. The different label sources only caused a limited accuracy loss of 0.022–0.044 for the three AI methods. Conclusion: VB-NPA in a real-world scenario is an effective way to assess neonatal pain due to its high intra-rater and inter-rater reliability compared to OS-NPA and could be used for the labeling of large-scale NPA video databases for clinical studies and AI training. MDPI 2023-08-12 /pmc/articles/PMC10453072/ /pubmed/37627921 http://dx.doi.org/10.3390/diagnostics13162661 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chen, Xiaofei
Zhu, Huaiyu
Mei, Linli
Shu, Qi
Cheng, Xiaoying
Luo, Feixiang
Zhao, Yisheng
Chen, Shuohui
Pan, Yun
Video-Based versus On-Site Neonatal Pain Assessment in Neonatal Intensive Care Units: The Impact of Video-Based Neonatal Pain Assessment in Real-World Scenario on Pain Diagnosis and Its Artificial Intelligence Application
title Video-Based versus On-Site Neonatal Pain Assessment in Neonatal Intensive Care Units: The Impact of Video-Based Neonatal Pain Assessment in Real-World Scenario on Pain Diagnosis and Its Artificial Intelligence Application
title_full Video-Based versus On-Site Neonatal Pain Assessment in Neonatal Intensive Care Units: The Impact of Video-Based Neonatal Pain Assessment in Real-World Scenario on Pain Diagnosis and Its Artificial Intelligence Application
title_fullStr Video-Based versus On-Site Neonatal Pain Assessment in Neonatal Intensive Care Units: The Impact of Video-Based Neonatal Pain Assessment in Real-World Scenario on Pain Diagnosis and Its Artificial Intelligence Application
title_full_unstemmed Video-Based versus On-Site Neonatal Pain Assessment in Neonatal Intensive Care Units: The Impact of Video-Based Neonatal Pain Assessment in Real-World Scenario on Pain Diagnosis and Its Artificial Intelligence Application
title_short Video-Based versus On-Site Neonatal Pain Assessment in Neonatal Intensive Care Units: The Impact of Video-Based Neonatal Pain Assessment in Real-World Scenario on Pain Diagnosis and Its Artificial Intelligence Application
title_sort video-based versus on-site neonatal pain assessment in neonatal intensive care units: the impact of video-based neonatal pain assessment in real-world scenario on pain diagnosis and its artificial intelligence application
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453072/
https://www.ncbi.nlm.nih.gov/pubmed/37627921
http://dx.doi.org/10.3390/diagnostics13162661
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