Glucose series complexity at the threshold of diabetes
One of the earliest signs of dysfunction in a complex system is the simplification of its output. A well-accepted method to measure this phenomenon is detrended fluctuation analysis (DFA). Herein, we evaluated the usefulness of DFA at the threshold of type 2 diabetes mellitus (T2DM). We report on th...
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Veröffentlicht in: | Journal of diabetes 2015-03, Vol.7 (2), p.287-293 |
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creator | Varela, Manuel Rodriguez, Carmen Vigil, Luis Cirugeda, Eva Colas, Ana Vargas, Borja |
description | One of the earliest signs of dysfunction in a complex system is the simplification of its output. A well-accepted method to measure this phenomenon is detrended fluctuation analysis (DFA). Herein, we evaluated the usefulness of DFA at the threshold of type 2 diabetes mellitus (T2DM).
We report on the clinical and glucometric characteristics of a sample of 103 patients at increased risk of developing T2DM. All patients had HbA1c levels 5%-6.4% and met at least one of the following criteria: body mass index (BMI) > 30 kg/m2, essential hypertension or a first-degree relative with T2DM. For each patient, a 24-h glucose time series was obtained, and the clinical and glucometric variables were compared.
There was a significant correlation between the number of National Cholesterol Education Program--Adult Treatment Panel (ATP III) metabolic syndrome (MS)-defining criteria and DFA (ρ = 0.231, P = 0.019), and DFA differed significantly between patients meeting or not the ATP III definition of MS (1.443 vs. 1.399, respectively; P = 0.018). The DFA was not correlated with HbA1c. Depending on how it was calculated, the area under the log(Fn)∼log(n) curve correlated with HbA1c levels or the number of MS criteria. Conventional variability metrics (mean amplitude of glycemic excursions) did not differ between patients complying or not with the definition of MS.
Complexity analysis is capable of detecting differences in variables related to the risk of developing T2DM and could be a useful tool to study the initial phases of glucoregulatory dysfunction leading to T2DM. |
doi_str_mv | 10.1111/1753-0407.12182 |
format | Article |
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We report on the clinical and glucometric characteristics of a sample of 103 patients at increased risk of developing T2DM. All patients had HbA1c levels 5%-6.4% and met at least one of the following criteria: body mass index (BMI) > 30 kg/m2, essential hypertension or a first-degree relative with T2DM. For each patient, a 24-h glucose time series was obtained, and the clinical and glucometric variables were compared.
There was a significant correlation between the number of National Cholesterol Education Program--Adult Treatment Panel (ATP III) metabolic syndrome (MS)-defining criteria and DFA (ρ = 0.231, P = 0.019), and DFA differed significantly between patients meeting or not the ATP III definition of MS (1.443 vs. 1.399, respectively; P = 0.018). The DFA was not correlated with HbA1c. Depending on how it was calculated, the area under the log(Fn)∼log(n) curve correlated with HbA1c levels or the number of MS criteria. Conventional variability metrics (mean amplitude of glycemic excursions) did not differ between patients complying or not with the definition of MS.
Complexity analysis is capable of detecting differences in variables related to the risk of developing T2DM and could be a useful tool to study the initial phases of glucoregulatory dysfunction leading to T2DM.</description><identifier>ISSN: 1753-0393</identifier><identifier>EISSN: 1753-0407</identifier><identifier>DOI: 10.1111/1753-0407.12182</identifier><identifier>PMID: 24911946</identifier><language>eng</language><publisher>Australia: John Wiley & Sons, Inc</publisher><subject>Adult ; Blood Glucose - analysis ; Blood Pressure ; Body Mass Index ; Cholesterol ; Cross-Sectional Studies ; Diabetes ; Diabetes Mellitus, Type 2 - diagnosis ; Female ; Follow-Up Studies ; Glucose Tolerance Test ; Glycated Hemoglobin A - analysis ; Humans ; Male ; Middle Aged ; Monitoring, Physiologic - methods ; Prognosis ; Risk Factors</subject><ispartof>Journal of diabetes, 2015-03, Vol.7 (2), p.287-293</ispartof><rights>2014 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.</rights><rights>Copyright © 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24911946$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Varela, Manuel</creatorcontrib><creatorcontrib>Rodriguez, Carmen</creatorcontrib><creatorcontrib>Vigil, Luis</creatorcontrib><creatorcontrib>Cirugeda, Eva</creatorcontrib><creatorcontrib>Colas, Ana</creatorcontrib><creatorcontrib>Vargas, Borja</creatorcontrib><title>Glucose series complexity at the threshold of diabetes</title><title>Journal of diabetes</title><addtitle>J Diabetes</addtitle><description>One of the earliest signs of dysfunction in a complex system is the simplification of its output. A well-accepted method to measure this phenomenon is detrended fluctuation analysis (DFA). Herein, we evaluated the usefulness of DFA at the threshold of type 2 diabetes mellitus (T2DM).
We report on the clinical and glucometric characteristics of a sample of 103 patients at increased risk of developing T2DM. All patients had HbA1c levels 5%-6.4% and met at least one of the following criteria: body mass index (BMI) > 30 kg/m2, essential hypertension or a first-degree relative with T2DM. For each patient, a 24-h glucose time series was obtained, and the clinical and glucometric variables were compared.
There was a significant correlation between the number of National Cholesterol Education Program--Adult Treatment Panel (ATP III) metabolic syndrome (MS)-defining criteria and DFA (ρ = 0.231, P = 0.019), and DFA differed significantly between patients meeting or not the ATP III definition of MS (1.443 vs. 1.399, respectively; P = 0.018). The DFA was not correlated with HbA1c. Depending on how it was calculated, the area under the log(Fn)∼log(n) curve correlated with HbA1c levels or the number of MS criteria. Conventional variability metrics (mean amplitude of glycemic excursions) did not differ between patients complying or not with the definition of MS.
Complexity analysis is capable of detecting differences in variables related to the risk of developing T2DM and could be a useful tool to study the initial phases of glucoregulatory dysfunction leading to T2DM.</description><subject>Adult</subject><subject>Blood Glucose - analysis</subject><subject>Blood Pressure</subject><subject>Body Mass Index</subject><subject>Cholesterol</subject><subject>Cross-Sectional Studies</subject><subject>Diabetes</subject><subject>Diabetes Mellitus, Type 2 - diagnosis</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Glucose Tolerance Test</subject><subject>Glycated Hemoglobin A - analysis</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Monitoring, Physiologic - methods</subject><subject>Prognosis</subject><subject>Risk Factors</subject><issn>1753-0393</issn><issn>1753-0407</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpd0EtLw0AQAOBFFFurZ28S8OIldZ-T7FGKVqHgRc9hHxOaknRjNgH7712w9eDAMMPwMQxDyC2jS5bikRVK5FTSYsk4K_kZmf9Nzk-90GJGrmLcUQoFgLgkMy41Y1rCnMC6nVyImEUcGoyZC13f4nczHjIzZuMWUw4Yt6H1Wagz3xiLI8ZrclGbNuLNsS7I58vzx-o137yv31ZPm7wXVI95WXNHS824U8rxwpcI0ljvVK2kV7qQqDBBa72hVAO1onZaFRzBM5DcigV5-N3bD-FrwjhWXRMdtq3ZY5hixUBxKbiSkOj9P7oL07BP1yUlS8VBAU_q7qgm26Gv-qHpzHCoTh8RP3HpYIQ</recordid><startdate>20150301</startdate><enddate>20150301</enddate><creator>Varela, Manuel</creator><creator>Rodriguez, Carmen</creator><creator>Vigil, Luis</creator><creator>Cirugeda, Eva</creator><creator>Colas, Ana</creator><creator>Vargas, Borja</creator><general>John Wiley & Sons, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>K9.</scope><scope>7X8</scope></search><sort><creationdate>20150301</creationdate><title>Glucose series complexity at the threshold of diabetes</title><author>Varela, Manuel ; Rodriguez, Carmen ; Vigil, Luis ; Cirugeda, Eva ; Colas, Ana ; Vargas, Borja</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p309t-8f2c08912c55c27d8e64abdc5f54d5974e5e309bbda00960b3fc9572e6d1642b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adult</topic><topic>Blood Glucose - analysis</topic><topic>Blood Pressure</topic><topic>Body Mass Index</topic><topic>Cholesterol</topic><topic>Cross-Sectional Studies</topic><topic>Diabetes</topic><topic>Diabetes Mellitus, Type 2 - diagnosis</topic><topic>Female</topic><topic>Follow-Up Studies</topic><topic>Glucose Tolerance Test</topic><topic>Glycated Hemoglobin A - analysis</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Monitoring, Physiologic - methods</topic><topic>Prognosis</topic><topic>Risk Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Varela, Manuel</creatorcontrib><creatorcontrib>Rodriguez, Carmen</creatorcontrib><creatorcontrib>Vigil, Luis</creatorcontrib><creatorcontrib>Cirugeda, Eva</creatorcontrib><creatorcontrib>Colas, Ana</creatorcontrib><creatorcontrib>Vargas, Borja</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of diabetes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Varela, Manuel</au><au>Rodriguez, Carmen</au><au>Vigil, Luis</au><au>Cirugeda, Eva</au><au>Colas, Ana</au><au>Vargas, Borja</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Glucose series complexity at the threshold of diabetes</atitle><jtitle>Journal of diabetes</jtitle><addtitle>J Diabetes</addtitle><date>2015-03-01</date><risdate>2015</risdate><volume>7</volume><issue>2</issue><spage>287</spage><epage>293</epage><pages>287-293</pages><issn>1753-0393</issn><eissn>1753-0407</eissn><abstract>One of the earliest signs of dysfunction in a complex system is the simplification of its output. A well-accepted method to measure this phenomenon is detrended fluctuation analysis (DFA). Herein, we evaluated the usefulness of DFA at the threshold of type 2 diabetes mellitus (T2DM).
We report on the clinical and glucometric characteristics of a sample of 103 patients at increased risk of developing T2DM. All patients had HbA1c levels 5%-6.4% and met at least one of the following criteria: body mass index (BMI) > 30 kg/m2, essential hypertension or a first-degree relative with T2DM. For each patient, a 24-h glucose time series was obtained, and the clinical and glucometric variables were compared.
There was a significant correlation between the number of National Cholesterol Education Program--Adult Treatment Panel (ATP III) metabolic syndrome (MS)-defining criteria and DFA (ρ = 0.231, P = 0.019), and DFA differed significantly between patients meeting or not the ATP III definition of MS (1.443 vs. 1.399, respectively; P = 0.018). The DFA was not correlated with HbA1c. Depending on how it was calculated, the area under the log(Fn)∼log(n) curve correlated with HbA1c levels or the number of MS criteria. Conventional variability metrics (mean amplitude of glycemic excursions) did not differ between patients complying or not with the definition of MS.
Complexity analysis is capable of detecting differences in variables related to the risk of developing T2DM and could be a useful tool to study the initial phases of glucoregulatory dysfunction leading to T2DM.</abstract><cop>Australia</cop><pub>John Wiley & Sons, Inc</pub><pmid>24911946</pmid><doi>10.1111/1753-0407.12182</doi><tpages>7</tpages></addata></record> |
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subjects | Adult Blood Glucose - analysis Blood Pressure Body Mass Index Cholesterol Cross-Sectional Studies Diabetes Diabetes Mellitus, Type 2 - diagnosis Female Follow-Up Studies Glucose Tolerance Test Glycated Hemoglobin A - analysis Humans Male Middle Aged Monitoring, Physiologic - methods Prognosis Risk Factors |
title | Glucose series complexity at the threshold of diabetes |
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