Clearance Rate and BP-ANN Model in Paraquat Poisoned Patients Treated with Hemoperfusion

In order to investigate the effect of hemoperfusion (HP) on the clearance rate of paraquat (PQ) and develop a clearance model, 41 PQ-poisoned patients who acquired acute PQ intoxication received HP treatment. PQ concentrations were determined by high performance liquid chromatography (HPLC). Accordi...

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Published in:BioMed research international 2015-01, Vol.2015 (2015), p.1-6
Main Authors: Lu, Zhongqiu, Lin, Guanyang, Wang, Xianqin, Ma, Jianshe, Hong, Guangliang, Hu, Lufeng, Zhang, Xiuhua
Format: Article
Language:English
Subjects:
Adolescent
Adult
Artificial intelligence
Calibration
Chinese medicine
Chromatography
Female
Free radicals
Health aspects
Hemoperfusion - methods
Herbicides
Hospitals
Humans
Male
Mathematical models
Medical prognosis
Metabolic Clearance Rate - physiology
Middle Aged
Mortality
Neural networks
Neural Networks (Computer)
Paraquat - blood
Paraquat - metabolism
Paraquat - poisoning
Plasma
Young Adult
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Hu, Lufeng
Zhang, Xiuhua
description In order to investigate the effect of hemoperfusion (HP) on the clearance rate of paraquat (PQ) and develop a clearance model, 41 PQ-poisoned patients who acquired acute PQ intoxication received HP treatment. PQ concentrations were determined by high performance liquid chromatography (HPLC). According to initial PQ concentration, study subjects were divided into two groups: Low-PQ group (0.05–1.0 μg/mL) and High-PQ group (1.0–10 μg/mL). After initial HP treatment, PQ concentrations decreased in both groups. However, in the High-PQ group, PQ levels remained in excess of 0.05 μg/mL and increased when the second HP treatment was initiated. Based on the PQ concentrations before and after HP treatment, the mean clearance rate of PQ calculated was 73 ± 15%. We also established a backpropagation artificial neural network (BP-ANN) model, which set PQ concentrations before HP treatment as input data and after HP treatment as output data. When it is used to predict PQ concentration after HP treatment, high prediction accuracy (R=0.9977) can be obtained in this model. In conclusion, HP is an effective way to clear PQ from the blood, and the PQ concentration after HP treatment can be predicted by BP-ANN model.
doi_str_mv 10.1155/2015/298253
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PQ concentrations were determined by high performance liquid chromatography (HPLC). According to initial PQ concentration, study subjects were divided into two groups: Low-PQ group (0.05–1.0 μg/mL) and High-PQ group (1.0–10 μg/mL). After initial HP treatment, PQ concentrations decreased in both groups. However, in the High-PQ group, PQ levels remained in excess of 0.05 μg/mL and increased when the second HP treatment was initiated. Based on the PQ concentrations before and after HP treatment, the mean clearance rate of PQ calculated was 73 ± 15%. We also established a backpropagation artificial neural network (BP-ANN) model, which set PQ concentrations before HP treatment as input data and after HP treatment as output data. When it is used to predict PQ concentration after HP treatment, high prediction accuracy (R=0.9977) can be obtained in this model. In conclusion, HP is an effective way to clear PQ from the blood, and the PQ concentration after HP treatment can be predicted by BP-ANN model.</description><identifier>ISSN: 2314-6133</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2015/298253</identifier><identifier>PMID: 25695058</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Adolescent ; Adult ; Artificial intelligence ; Calibration ; Chinese medicine ; Chromatography ; Female ; Free radicals ; Health aspects ; Hemoperfusion - methods ; Herbicides ; Hospitals ; Humans ; Male ; Mathematical models ; Medical prognosis ; Metabolic Clearance Rate - physiology ; Middle Aged ; Mortality ; Neural networks ; Neural Networks (Computer) ; Paraquat - blood ; Paraquat - metabolism ; Paraquat - poisoning ; Plasma ; Young Adult</subject><ispartof>BioMed research international, 2015-01, Vol.2015 (2015), p.1-6</ispartof><rights>Copyright © 2015 Lufeng Hu et al.</rights><rights>COPYRIGHT 2015 John Wiley &amp; Sons, Inc.</rights><rights>Copyright © 2015 Lufeng Hu et al. 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subjects Adolescent
Adult
Artificial intelligence
Calibration
Chinese medicine
Chromatography
Female
Free radicals
Health aspects
Hemoperfusion - methods
Herbicides
Hospitals
Humans
Male
Mathematical models
Medical prognosis
Metabolic Clearance Rate - physiology
Middle Aged
Mortality
Neural networks
Neural Networks (Computer)
Paraquat - blood
Paraquat - metabolism
Paraquat - poisoning
Plasma
Young Adult
title Clearance Rate and BP-ANN Model in Paraquat Poisoned Patients Treated with Hemoperfusion
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