A new model for predicting intravenous immunoglobin-resistant Kawasaki disease in Chongqing: a retrospective study on 5277 patients
Accurate evaluation of individual risk of intravenous immunoglobin (IVIG)-resistance is critical for adopting regimens for the first treatment and prevention of coronary artery lesions (CALs) in patients with Kawasaki disease (KD). Methods: The KD patients hospitalized in Chongqing Children’s Hospit...
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| Veröffentlicht in: | Scientific reports 2019-02, Vol.9 (1), p.1722-1722, Article 1722 |
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| creator | Tan, Xu-Hai Zhang, Xiao-Wei Wang, Xiao-Yun He, Xiang-Qian Fan, Chu Lyu, Tie-Wei Tian, Jie |
| description | Accurate evaluation of individual risk of intravenous immunoglobin (IVIG)-resistance is critical for adopting regimens for the first treatment and prevention of coronary artery lesions (CALs) in patients with Kawasaki disease (KD). Methods: The KD patients hospitalized in Chongqing Children’s Hospital, in west China, from October 2007 to December 2017 were retrospectively reviewed. Data were collected and compared between IVIG-resistant group and IVIG-responsive group. The independent risk factors were determined using multivariate regression analysis. A new prediction model was built and compared with the previous models. Results: A total of 5277 subjects were studied and eight independent risk factors were identified including higher red blood cell distribution width (RDW), lower platelet count (PLT), lower percentage of lymphocyte (P-LYM), higher total bile acid (TBA), lower albumin, lower serum sodium level, higher degree of CALs (D-CALs) and younger age. The new predictive model showed an AUC of 0.74, sensitivity of 76% and specificity of 59%. For individual’s risk probability of IVIG-resistance, an equation was given. Conclusions: IVIG-resistance could be predicted by RDW, PLT, P-LYM, TBA, albumin, serum sodium level, D-CALs and age. The new model appeared to be superior to those previous models for KD population in Chongqing city. |
| doi_str_mv | 10.1038/s41598-019-39330-y |
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Methods: The KD patients hospitalized in Chongqing Children’s Hospital, in west China, from October 2007 to December 2017 were retrospectively reviewed. Data were collected and compared between IVIG-resistant group and IVIG-responsive group. The independent risk factors were determined using multivariate regression analysis. A new prediction model was built and compared with the previous models. Results: A total of 5277 subjects were studied and eight independent risk factors were identified including higher red blood cell distribution width (RDW), lower platelet count (PLT), lower percentage of lymphocyte (P-LYM), higher total bile acid (TBA), lower albumin, lower serum sodium level, higher degree of CALs (D-CALs) and younger age. The new predictive model showed an AUC of 0.74, sensitivity of 76% and specificity of 59%. For individual’s risk probability of IVIG-resistance, an equation was given. Conclusions: IVIG-resistance could be predicted by RDW, PLT, P-LYM, TBA, albumin, serum sodium level, D-CALs and age. The new model appeared to be superior to those previous models for KD population in Chongqing city.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-019-39330-y</identifier><identifier>PMID: 30742060</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>692/4023/1670/427 ; 692/499 ; 692/700/1720/3187 ; Albumin ; Coronary artery ; Erythrocytes ; Humanities and Social Sciences ; Immunoglobulins ; Intravenous administration ; Kawasaki disease ; Lymphocytes ; Mucocutaneous lymph node syndrome ; multidisciplinary ; Patients ; Prediction models ; Regression analysis ; Risk factors ; Science ; Science (multidisciplinary) ; Sodium</subject><ispartof>Scientific reports, 2019-02, Vol.9 (1), p.1722-1722, Article 1722</ispartof><rights>The Author(s) 2019</rights><rights>This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-6a10859493fa9ac25097af2b9d5a0bcdc0e9349d301b8c76136cd138af1b9e183</citedby><cites>FETCH-LOGICAL-c474t-6a10859493fa9ac25097af2b9d5a0bcdc0e9349d301b8c76136cd138af1b9e183</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370794/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370794/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27903,27904,41099,42168,51554,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30742060$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tan, Xu-Hai</creatorcontrib><creatorcontrib>Zhang, Xiao-Wei</creatorcontrib><creatorcontrib>Wang, Xiao-Yun</creatorcontrib><creatorcontrib>He, Xiang-Qian</creatorcontrib><creatorcontrib>Fan, Chu</creatorcontrib><creatorcontrib>Lyu, Tie-Wei</creatorcontrib><creatorcontrib>Tian, Jie</creatorcontrib><title>A new model for predicting intravenous immunoglobin-resistant Kawasaki disease in Chongqing: a retrospective study on 5277 patients</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>Accurate evaluation of individual risk of intravenous immunoglobin (IVIG)-resistance is critical for adopting regimens for the first treatment and prevention of coronary artery lesions (CALs) in patients with Kawasaki disease (KD). Methods: The KD patients hospitalized in Chongqing Children’s Hospital, in west China, from October 2007 to December 2017 were retrospectively reviewed. Data were collected and compared between IVIG-resistant group and IVIG-responsive group. The independent risk factors were determined using multivariate regression analysis. A new prediction model was built and compared with the previous models. Results: A total of 5277 subjects were studied and eight independent risk factors were identified including higher red blood cell distribution width (RDW), lower platelet count (PLT), lower percentage of lymphocyte (P-LYM), higher total bile acid (TBA), lower albumin, lower serum sodium level, higher degree of CALs (D-CALs) and younger age. The new predictive model showed an AUC of 0.74, sensitivity of 76% and specificity of 59%. For individual’s risk probability of IVIG-resistance, an equation was given. Conclusions: IVIG-resistance could be predicted by RDW, PLT, P-LYM, TBA, albumin, serum sodium level, D-CALs and age. The new model appeared to be superior to those previous models for KD population in Chongqing city.</description><subject>692/4023/1670/427</subject><subject>692/499</subject><subject>692/700/1720/3187</subject><subject>Albumin</subject><subject>Coronary artery</subject><subject>Erythrocytes</subject><subject>Humanities and Social Sciences</subject><subject>Immunoglobulins</subject><subject>Intravenous administration</subject><subject>Kawasaki disease</subject><subject>Lymphocytes</subject><subject>Mucocutaneous lymph node syndrome</subject><subject>multidisciplinary</subject><subject>Patients</subject><subject>Prediction models</subject><subject>Regression analysis</subject><subject>Risk factors</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><subject>Sodium</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kc1u1TAQhS0EolXbF2CBLLFhE_Bf4pgFUnXVFkQlNrC2HGeSuiR2aju3umteHLe3lMICb2xpvjnjMwehV5S8o4S375OgtWorQlXFFeek2j1Dh4yIumKcsedP3gfoJKVrUk7NlKDqJTrgRApGGnKIfp5iD7d4Dj1MeAgRLxF6Z7PzI3Y-R7MFH9aE3TyvPoxT6JyvIiSXsvEZfzG3JpkfDvcugUlQevDmKvjxpgh8wAZHyDGkBYriFnDKa7_DweOaSYkXkx34nI7Ri8FMCU4e7iP0_fzs2-ZTdfn14vPm9LKyQopcNYaStlZC8cEoY1lNlDQD61RfG9LZ3hJQXKieE9q1VjaUN7anvDUD7RTQlh-hj3vdZe1m6C3c-Zv0Et1s4k4H4_TfFe-u9Bi2uuGSSCWKwNsHgRhuVkhZzy5ZmCbjoSxJszKkEXUreEHf_INehzX6Yq9Qsm0Ia0hTKLanbFlSijA8foYSfRez3sesS8z6Pma9K02vn9p4bPkdagH4Hkil5EeIf2b_R_YXRhW2CA</recordid><startdate>20190211</startdate><enddate>20190211</enddate><creator>Tan, Xu-Hai</creator><creator>Zhang, Xiao-Wei</creator><creator>Wang, Xiao-Yun</creator><creator>He, Xiang-Qian</creator><creator>Fan, Chu</creator><creator>Lyu, Tie-Wei</creator><creator>Tian, Jie</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20190211</creationdate><title>A new model for predicting intravenous immunoglobin-resistant Kawasaki disease in Chongqing: a retrospective study on 5277 patients</title><author>Tan, Xu-Hai ; Zhang, Xiao-Wei ; Wang, Xiao-Yun ; He, Xiang-Qian ; Fan, Chu ; Lyu, Tie-Wei ; Tian, Jie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-6a10859493fa9ac25097af2b9d5a0bcdc0e9349d301b8c76136cd138af1b9e183</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>692/4023/1670/427</topic><topic>692/499</topic><topic>692/700/1720/3187</topic><topic>Albumin</topic><topic>Coronary artery</topic><topic>Erythrocytes</topic><topic>Humanities and Social Sciences</topic><topic>Immunoglobulins</topic><topic>Intravenous administration</topic><topic>Kawasaki disease</topic><topic>Lymphocytes</topic><topic>Mucocutaneous lymph node syndrome</topic><topic>multidisciplinary</topic><topic>Patients</topic><topic>Prediction models</topic><topic>Regression analysis</topic><topic>Risk factors</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><topic>Sodium</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tan, Xu-Hai</creatorcontrib><creatorcontrib>Zhang, Xiao-Wei</creatorcontrib><creatorcontrib>Wang, Xiao-Yun</creatorcontrib><creatorcontrib>He, Xiang-Qian</creatorcontrib><creatorcontrib>Fan, Chu</creatorcontrib><creatorcontrib>Lyu, Tie-Wei</creatorcontrib><creatorcontrib>Tian, Jie</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database (ProQuest)</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tan, Xu-Hai</au><au>Zhang, Xiao-Wei</au><au>Wang, Xiao-Yun</au><au>He, Xiang-Qian</au><au>Fan, Chu</au><au>Lyu, Tie-Wei</au><au>Tian, Jie</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new model for predicting intravenous immunoglobin-resistant Kawasaki disease in Chongqing: a retrospective study on 5277 patients</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2019-02-11</date><risdate>2019</risdate><volume>9</volume><issue>1</issue><spage>1722</spage><epage>1722</epage><pages>1722-1722</pages><artnum>1722</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>Accurate evaluation of individual risk of intravenous immunoglobin (IVIG)-resistance is critical for adopting regimens for the first treatment and prevention of coronary artery lesions (CALs) in patients with Kawasaki disease (KD). Methods: The KD patients hospitalized in Chongqing Children’s Hospital, in west China, from October 2007 to December 2017 were retrospectively reviewed. Data were collected and compared between IVIG-resistant group and IVIG-responsive group. The independent risk factors were determined using multivariate regression analysis. A new prediction model was built and compared with the previous models. Results: A total of 5277 subjects were studied and eight independent risk factors were identified including higher red blood cell distribution width (RDW), lower platelet count (PLT), lower percentage of lymphocyte (P-LYM), higher total bile acid (TBA), lower albumin, lower serum sodium level, higher degree of CALs (D-CALs) and younger age. The new predictive model showed an AUC of 0.74, sensitivity of 76% and specificity of 59%. For individual’s risk probability of IVIG-resistance, an equation was given. Conclusions: IVIG-resistance could be predicted by RDW, PLT, P-LYM, TBA, albumin, serum sodium level, D-CALs and age. The new model appeared to be superior to those previous models for KD population in Chongqing city.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>30742060</pmid><doi>10.1038/s41598-019-39330-y</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | 692/4023/1670/427 692/499 692/700/1720/3187 Albumin Coronary artery Erythrocytes Humanities and Social Sciences Immunoglobulins Intravenous administration Kawasaki disease Lymphocytes Mucocutaneous lymph node syndrome multidisciplinary Patients Prediction models Regression analysis Risk factors Science Science (multidisciplinary) Sodium |
| title | A new model for predicting intravenous immunoglobin-resistant Kawasaki disease in Chongqing: a retrospective study on 5277 patients |
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