Confounders in Identification and Analysis of Inflammatory Biomarkers in Cardiovascular Diseases
Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlation between the elevated level of inflammatory biom...
Ausführliche Beschreibung
Autor*in: |
Qurrat Ul Ain [verfasserIn] Mehak Sarfraz [verfasserIn] Gayuk Kalih Prasesti [verfasserIn] Triwedya Indra Dewi [verfasserIn] Neng Fisheri Kurniati [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2021 |
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Übergeordnetes Werk: |
In: Biomolecules - MDPI AG, 2013, 11(2021), 10, p 1464 |
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Übergeordnetes Werk: |
volume:11 ; year:2021 ; number:10, p 1464 |
Links: |
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DOI / URN: |
10.3390/biom11101464 |
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Katalog-ID: |
DOAJ016656482 |
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10.3390/biom11101464 doi (DE-627)DOAJ016656482 (DE-599)DOAJad58d5977b6a4015b4f2dcc384cc01fc DE-627 ger DE-627 rakwb eng QR1-502 Qurrat Ul Ain verfasserin aut Confounders in Identification and Analysis of Inflammatory Biomarkers in Cardiovascular Diseases 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlation between the elevated level of inflammatory biomarkers and the pathology of various cardiovascular diseases, the mechanisms of the underlying cause are unclear. Identification of pro-inflammatory biomarkers such as cytokines, chemokines, acute phase proteins, and other soluble immune factors can help in the early diagnosis of disease. The presence of certain confounding factors such as variations in age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, as well as inconsistencies in methodological practices such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. The purpose of the review is to identify and summarize the effect of demographic factors, epidemiological factors, medication use, and analytical and pre-analytical factors with a panel of inflammatory biomarkers CRP, IL-1b, IL-6, TNFa, and the soluble TNF receptors on the concentration of these inflammatory biomarkers in serum. pro-inflammatory biomarkers confounding factors inflammation chemokines cytokines acute-phase proteins Microbiology Mehak Sarfraz verfasserin aut Gayuk Kalih Prasesti verfasserin aut Triwedya Indra Dewi verfasserin aut Neng Fisheri Kurniati verfasserin aut In Biomolecules MDPI AG, 2013 11(2021), 10, p 1464 (DE-627)735688915 (DE-600)2701262-1 2218273X nnns volume:11 year:2021 number:10, p 1464 https://doi.org/10.3390/biom11101464 kostenfrei https://doaj.org/article/ad58d5977b6a4015b4f2dcc384cc01fc kostenfrei https://www.mdpi.com/2218-273X/11/10/1464 kostenfrei https://doaj.org/toc/2218-273X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 10, p 1464 |
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10.3390/biom11101464 doi (DE-627)DOAJ016656482 (DE-599)DOAJad58d5977b6a4015b4f2dcc384cc01fc DE-627 ger DE-627 rakwb eng QR1-502 Qurrat Ul Ain verfasserin aut Confounders in Identification and Analysis of Inflammatory Biomarkers in Cardiovascular Diseases 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlation between the elevated level of inflammatory biomarkers and the pathology of various cardiovascular diseases, the mechanisms of the underlying cause are unclear. Identification of pro-inflammatory biomarkers such as cytokines, chemokines, acute phase proteins, and other soluble immune factors can help in the early diagnosis of disease. The presence of certain confounding factors such as variations in age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, as well as inconsistencies in methodological practices such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. The purpose of the review is to identify and summarize the effect of demographic factors, epidemiological factors, medication use, and analytical and pre-analytical factors with a panel of inflammatory biomarkers CRP, IL-1b, IL-6, TNFa, and the soluble TNF receptors on the concentration of these inflammatory biomarkers in serum. pro-inflammatory biomarkers confounding factors inflammation chemokines cytokines acute-phase proteins Microbiology Mehak Sarfraz verfasserin aut Gayuk Kalih Prasesti verfasserin aut Triwedya Indra Dewi verfasserin aut Neng Fisheri Kurniati verfasserin aut In Biomolecules MDPI AG, 2013 11(2021), 10, p 1464 (DE-627)735688915 (DE-600)2701262-1 2218273X nnns volume:11 year:2021 number:10, p 1464 https://doi.org/10.3390/biom11101464 kostenfrei https://doaj.org/article/ad58d5977b6a4015b4f2dcc384cc01fc kostenfrei https://www.mdpi.com/2218-273X/11/10/1464 kostenfrei https://doaj.org/toc/2218-273X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 10, p 1464 |
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10.3390/biom11101464 doi (DE-627)DOAJ016656482 (DE-599)DOAJad58d5977b6a4015b4f2dcc384cc01fc DE-627 ger DE-627 rakwb eng QR1-502 Qurrat Ul Ain verfasserin aut Confounders in Identification and Analysis of Inflammatory Biomarkers in Cardiovascular Diseases 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlation between the elevated level of inflammatory biomarkers and the pathology of various cardiovascular diseases, the mechanisms of the underlying cause are unclear. Identification of pro-inflammatory biomarkers such as cytokines, chemokines, acute phase proteins, and other soluble immune factors can help in the early diagnosis of disease. The presence of certain confounding factors such as variations in age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, as well as inconsistencies in methodological practices such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. The purpose of the review is to identify and summarize the effect of demographic factors, epidemiological factors, medication use, and analytical and pre-analytical factors with a panel of inflammatory biomarkers CRP, IL-1b, IL-6, TNFa, and the soluble TNF receptors on the concentration of these inflammatory biomarkers in serum. pro-inflammatory biomarkers confounding factors inflammation chemokines cytokines acute-phase proteins Microbiology Mehak Sarfraz verfasserin aut Gayuk Kalih Prasesti verfasserin aut Triwedya Indra Dewi verfasserin aut Neng Fisheri Kurniati verfasserin aut In Biomolecules MDPI AG, 2013 11(2021), 10, p 1464 (DE-627)735688915 (DE-600)2701262-1 2218273X nnns volume:11 year:2021 number:10, p 1464 https://doi.org/10.3390/biom11101464 kostenfrei https://doaj.org/article/ad58d5977b6a4015b4f2dcc384cc01fc kostenfrei https://www.mdpi.com/2218-273X/11/10/1464 kostenfrei https://doaj.org/toc/2218-273X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 10, p 1464 |
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10.3390/biom11101464 doi (DE-627)DOAJ016656482 (DE-599)DOAJad58d5977b6a4015b4f2dcc384cc01fc DE-627 ger DE-627 rakwb eng QR1-502 Qurrat Ul Ain verfasserin aut Confounders in Identification and Analysis of Inflammatory Biomarkers in Cardiovascular Diseases 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlation between the elevated level of inflammatory biomarkers and the pathology of various cardiovascular diseases, the mechanisms of the underlying cause are unclear. Identification of pro-inflammatory biomarkers such as cytokines, chemokines, acute phase proteins, and other soluble immune factors can help in the early diagnosis of disease. The presence of certain confounding factors such as variations in age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, as well as inconsistencies in methodological practices such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. The purpose of the review is to identify and summarize the effect of demographic factors, epidemiological factors, medication use, and analytical and pre-analytical factors with a panel of inflammatory biomarkers CRP, IL-1b, IL-6, TNFa, and the soluble TNF receptors on the concentration of these inflammatory biomarkers in serum. pro-inflammatory biomarkers confounding factors inflammation chemokines cytokines acute-phase proteins Microbiology Mehak Sarfraz verfasserin aut Gayuk Kalih Prasesti verfasserin aut Triwedya Indra Dewi verfasserin aut Neng Fisheri Kurniati verfasserin aut In Biomolecules MDPI AG, 2013 11(2021), 10, p 1464 (DE-627)735688915 (DE-600)2701262-1 2218273X nnns volume:11 year:2021 number:10, p 1464 https://doi.org/10.3390/biom11101464 kostenfrei https://doaj.org/article/ad58d5977b6a4015b4f2dcc384cc01fc kostenfrei https://www.mdpi.com/2218-273X/11/10/1464 kostenfrei https://doaj.org/toc/2218-273X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 10, p 1464 |
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Confounders in Identification and Analysis of Inflammatory Biomarkers in Cardiovascular Diseases |
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Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlation between the elevated level of inflammatory biomarkers and the pathology of various cardiovascular diseases, the mechanisms of the underlying cause are unclear. Identification of pro-inflammatory biomarkers such as cytokines, chemokines, acute phase proteins, and other soluble immune factors can help in the early diagnosis of disease. The presence of certain confounding factors such as variations in age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, as well as inconsistencies in methodological practices such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. The purpose of the review is to identify and summarize the effect of demographic factors, epidemiological factors, medication use, and analytical and pre-analytical factors with a panel of inflammatory biomarkers CRP, IL-1b, IL-6, TNFa, and the soluble TNF receptors on the concentration of these inflammatory biomarkers in serum. |
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Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlation between the elevated level of inflammatory biomarkers and the pathology of various cardiovascular diseases, the mechanisms of the underlying cause are unclear. Identification of pro-inflammatory biomarkers such as cytokines, chemokines, acute phase proteins, and other soluble immune factors can help in the early diagnosis of disease. The presence of certain confounding factors such as variations in age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, as well as inconsistencies in methodological practices such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. The purpose of the review is to identify and summarize the effect of demographic factors, epidemiological factors, medication use, and analytical and pre-analytical factors with a panel of inflammatory biomarkers CRP, IL-1b, IL-6, TNFa, and the soluble TNF receptors on the concentration of these inflammatory biomarkers in serum. |
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Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlation between the elevated level of inflammatory biomarkers and the pathology of various cardiovascular diseases, the mechanisms of the underlying cause are unclear. Identification of pro-inflammatory biomarkers such as cytokines, chemokines, acute phase proteins, and other soluble immune factors can help in the early diagnosis of disease. The presence of certain confounding factors such as variations in age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, as well as inconsistencies in methodological practices such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. The purpose of the review is to identify and summarize the effect of demographic factors, epidemiological factors, medication use, and analytical and pre-analytical factors with a panel of inflammatory biomarkers CRP, IL-1b, IL-6, TNFa, and the soluble TNF receptors on the concentration of these inflammatory biomarkers in serum. |
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