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Evaluation of illness severity of neonate infectious pneumonia and neurobehavioral development through ultrasonography under adaption algorithm

OBJECTIVES: To explore the diagnostic effect of ultrasound imaging on the illness severity, and to analyze neurobehavioral development of neonates with Infectious Pneumonia (IPN), Self- Adaptation (SD), and Spatial Smoothing (SS) technologies were adopted to build SDSS. Then, the WFFSF algorithm bas...

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Autores principales: Meng, Kangkang, Ying, Chao, Ji, Jianwei, Yang, Lianfang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Professional Medical Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8520381/
https://www.ncbi.nlm.nih.gov/pubmed/34712306
http://dx.doi.org/10.12669/pjms.37.6-WIT.4883
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author Meng, Kangkang
Ying, Chao
Ji, Jianwei
Yang, Lianfang
author_facet Meng, Kangkang
Ying, Chao
Ji, Jianwei
Yang, Lianfang
author_sort Meng, Kangkang
collection PubMed
description OBJECTIVES: To explore the diagnostic effect of ultrasound imaging on the illness severity, and to analyze neurobehavioral development of neonates with Infectious Pneumonia (IPN), Self- Adaptation (SD), and Spatial Smoothing (SS) technologies were adopted to build SDSS. Then, the WFFSF algorithm based on Wiener Filtering (WF) and Feature Space Fusion (FSF) and the SNRP-FSF algorithm based on Signal-to-noise ratio post-filtering (SNRP) and FSF were introduced for comparison. METHODS: One hundred and thirty-two neonates were divided into group without respiratory failure (S1) and respiratory failure group (S2). The study was conducted from March 2018 to July 2020. According to scoring systems for neonatal critically illness, they were divided into non-severe group (W1), severe group (W2), and extremely-severe group (W3). According to the Scale of Child Development Center of China (CDCC), they were divided into a normal neurobehavioral developmental group (P1) and an abnormal neurobehavioral developmental group (P2). RESULTS: The normalized mean square distance l and normalized mean absolute distance f of SDSS algorithm were significantly lower than that of WFFSF algorithm and SNRP-FSF algorithm, and the peak signal-to-noise ratio (PSNR) was significantly higher than that of WFFSF algorithm and SNRP-FSF algorithm (P<0.05). The lung ultrasound score (40.62±7.22%) of S1 was greatly higher than S2 group (28.47±6.29%) (P<0.05); the lung ultrasound score (39.13±8.25) in W1 was greatly higher than W2 (27.28±6.39) and W3 groups (14.33±7.03); neonates in group W2 had higher lung ultrasound scores than W3 (P<0.05), and lung ultrasound scores in P1 (42.57±8.58) was greatly higher than that the P2 group (26.49±6.09). CONCLUSION: In contrast with traditional algorithms, the SDSS algorithm based on AD has a better reconstruction effect on neonatal IPN ultrasound images. The lung ultrasound score can clearly indicate the severity of the disease and neurobehavioral development of neonate IPN, and the lung ultrasound score is negatively correlated with the severity of the child’s disease and the abnormality of neurobehavioral development.
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spelling pubmed-85203812021-10-27 Evaluation of illness severity of neonate infectious pneumonia and neurobehavioral development through ultrasonography under adaption algorithm Meng, Kangkang Ying, Chao Ji, Jianwei Yang, Lianfang Pak J Med Sci Original Article OBJECTIVES: To explore the diagnostic effect of ultrasound imaging on the illness severity, and to analyze neurobehavioral development of neonates with Infectious Pneumonia (IPN), Self- Adaptation (SD), and Spatial Smoothing (SS) technologies were adopted to build SDSS. Then, the WFFSF algorithm based on Wiener Filtering (WF) and Feature Space Fusion (FSF) and the SNRP-FSF algorithm based on Signal-to-noise ratio post-filtering (SNRP) and FSF were introduced for comparison. METHODS: One hundred and thirty-two neonates were divided into group without respiratory failure (S1) and respiratory failure group (S2). The study was conducted from March 2018 to July 2020. According to scoring systems for neonatal critically illness, they were divided into non-severe group (W1), severe group (W2), and extremely-severe group (W3). According to the Scale of Child Development Center of China (CDCC), they were divided into a normal neurobehavioral developmental group (P1) and an abnormal neurobehavioral developmental group (P2). RESULTS: The normalized mean square distance l and normalized mean absolute distance f of SDSS algorithm were significantly lower than that of WFFSF algorithm and SNRP-FSF algorithm, and the peak signal-to-noise ratio (PSNR) was significantly higher than that of WFFSF algorithm and SNRP-FSF algorithm (P<0.05). The lung ultrasound score (40.62±7.22%) of S1 was greatly higher than S2 group (28.47±6.29%) (P<0.05); the lung ultrasound score (39.13±8.25) in W1 was greatly higher than W2 (27.28±6.39) and W3 groups (14.33±7.03); neonates in group W2 had higher lung ultrasound scores than W3 (P<0.05), and lung ultrasound scores in P1 (42.57±8.58) was greatly higher than that the P2 group (26.49±6.09). CONCLUSION: In contrast with traditional algorithms, the SDSS algorithm based on AD has a better reconstruction effect on neonatal IPN ultrasound images. The lung ultrasound score can clearly indicate the severity of the disease and neurobehavioral development of neonate IPN, and the lung ultrasound score is negatively correlated with the severity of the child’s disease and the abnormality of neurobehavioral development. Professional Medical Publications 2021 /pmc/articles/PMC8520381/ /pubmed/34712306 http://dx.doi.org/10.12669/pjms.37.6-WIT.4883 Text en Copyright: © Pakistan Journal of Medical Sciences https://creativecommons.org/licenses/by/3.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0 (https://creativecommons.org/licenses/by/3.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Meng, Kangkang
Ying, Chao
Ji, Jianwei
Yang, Lianfang
Evaluation of illness severity of neonate infectious pneumonia and neurobehavioral development through ultrasonography under adaption algorithm
title Evaluation of illness severity of neonate infectious pneumonia and neurobehavioral development through ultrasonography under adaption algorithm
title_full Evaluation of illness severity of neonate infectious pneumonia and neurobehavioral development through ultrasonography under adaption algorithm
title_fullStr Evaluation of illness severity of neonate infectious pneumonia and neurobehavioral development through ultrasonography under adaption algorithm
title_full_unstemmed Evaluation of illness severity of neonate infectious pneumonia and neurobehavioral development through ultrasonography under adaption algorithm
title_short Evaluation of illness severity of neonate infectious pneumonia and neurobehavioral development through ultrasonography under adaption algorithm
title_sort evaluation of illness severity of neonate infectious pneumonia and neurobehavioral development through ultrasonography under adaption algorithm
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8520381/
https://www.ncbi.nlm.nih.gov/pubmed/34712306
http://dx.doi.org/10.12669/pjms.37.6-WIT.4883
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