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Diagnostic value of a logistic model of occupational lead poisoning using hematological parameters

OBJECTIVE: We investigated the predictive value of a logistic model utilizing hematological parameters in diagnosing occupational lead poisoning. METHODS: This retrospective study (September 2020–December 2022) included patients with occupational lead poisoning. Differences in hematological paramete...

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Autores principales: Sun, Guokang, Xiang, Pinpin, Chen, Yiping, Li, Zheng, Wu, Bo, Rao, Yanping, Zhu, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10666822/
https://www.ncbi.nlm.nih.gov/pubmed/37994031
http://dx.doi.org/10.1177/03000605231213221
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author Sun, Guokang
Xiang, Pinpin
Chen, Yiping
Li, Zheng
Wu, Bo
Rao, Yanping
Zhu, Zheng
author_facet Sun, Guokang
Xiang, Pinpin
Chen, Yiping
Li, Zheng
Wu, Bo
Rao, Yanping
Zhu, Zheng
author_sort Sun, Guokang
collection PubMed
description OBJECTIVE: We investigated the predictive value of a logistic model utilizing hematological parameters in diagnosing occupational lead poisoning. METHODS: This retrospective study (September 2020–December 2022) included patients with occupational lead poisoning. Differences in hematological parameters were compared between individuals with occupational blood lead poisoning and healthy individuals. We used logistic regression analysis to develop a diagnostic prediction model for occupational blood lead poisoning. Receiver operating characteristic (ROC) curves and corresponding area under the ROC curve values were used to assess the diagnostic value of hematological parameters and logistic models. RESULTS: Compared with controls, several indicators were significantly higher in the group with blood lead poisoning, but others were significantly lower. Logistic regression analysis showed that the red blood cell distribution width coefficient of variation (RDW-CV), neutrophil/lymphocyte ratio (NLR), and percentage of small red blood cells (Micro%) were independent factors in diagnosing occupational blood lead poisoning. The logistic regression model constructed based on these three parameters had sensitivity 78.7% and specificity 83.8% for diagnosing occupational lead poisoning. CONCLUSION: We identified RDW-CV, NLR, and Micro% as independent predictors in the diagnosis of occupational lead poisoning. A logistic regression model that includes these may contribute to better detection of occupational lead poisoning.
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spelling pubmed-106668222023-11-22 Diagnostic value of a logistic model of occupational lead poisoning using hematological parameters Sun, Guokang Xiang, Pinpin Chen, Yiping Li, Zheng Wu, Bo Rao, Yanping Zhu, Zheng J Int Med Res Observational Study OBJECTIVE: We investigated the predictive value of a logistic model utilizing hematological parameters in diagnosing occupational lead poisoning. METHODS: This retrospective study (September 2020–December 2022) included patients with occupational lead poisoning. Differences in hematological parameters were compared between individuals with occupational blood lead poisoning and healthy individuals. We used logistic regression analysis to develop a diagnostic prediction model for occupational blood lead poisoning. Receiver operating characteristic (ROC) curves and corresponding area under the ROC curve values were used to assess the diagnostic value of hematological parameters and logistic models. RESULTS: Compared with controls, several indicators were significantly higher in the group with blood lead poisoning, but others were significantly lower. Logistic regression analysis showed that the red blood cell distribution width coefficient of variation (RDW-CV), neutrophil/lymphocyte ratio (NLR), and percentage of small red blood cells (Micro%) were independent factors in diagnosing occupational blood lead poisoning. The logistic regression model constructed based on these three parameters had sensitivity 78.7% and specificity 83.8% for diagnosing occupational lead poisoning. CONCLUSION: We identified RDW-CV, NLR, and Micro% as independent predictors in the diagnosis of occupational lead poisoning. A logistic regression model that includes these may contribute to better detection of occupational lead poisoning. SAGE Publications 2023-11-22 /pmc/articles/PMC10666822/ /pubmed/37994031 http://dx.doi.org/10.1177/03000605231213221 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Observational Study
Sun, Guokang
Xiang, Pinpin
Chen, Yiping
Li, Zheng
Wu, Bo
Rao, Yanping
Zhu, Zheng
Diagnostic value of a logistic model of occupational lead poisoning using hematological parameters
title Diagnostic value of a logistic model of occupational lead poisoning using hematological parameters
title_full Diagnostic value of a logistic model of occupational lead poisoning using hematological parameters
title_fullStr Diagnostic value of a logistic model of occupational lead poisoning using hematological parameters
title_full_unstemmed Diagnostic value of a logistic model of occupational lead poisoning using hematological parameters
title_short Diagnostic value of a logistic model of occupational lead poisoning using hematological parameters
title_sort diagnostic value of a logistic model of occupational lead poisoning using hematological parameters
topic Observational Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10666822/
https://www.ncbi.nlm.nih.gov/pubmed/37994031
http://dx.doi.org/10.1177/03000605231213221
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