Predictive model of global tilt (GT) determined by individual thoracic kyphosis, lumbar lordosis and pelvic incidence in the human degenerative spine

Purpose Previous studies only investigated the simple linear relationships of global tilt (GT) with thoracic kyphosis (TK), lumbar lordosis (LL) and pelvic incidence (PI). This study aimed to establish multiple linear regressions of GT based on individual TK, LL and PI in patients with degenerative...

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Veröffentlicht in:European spine journal 2021-11, Vol.30 (11), p.3191-3199
Hauptverfasser: Pan, Changyu, Wang, Guodong, Li, Yunchao, Kuang, Lei, Sun, Jianmin, Lv, Guohua
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container_end_page 3199
container_issue 11
container_start_page 3191
container_title European spine journal
container_volume 30
creator Pan, Changyu
Wang, Guodong
Li, Yunchao
Kuang, Lei
Sun, Jianmin
Lv, Guohua
description Purpose Previous studies only investigated the simple linear relationships of global tilt (GT) with thoracic kyphosis (TK), lumbar lordosis (LL) and pelvic incidence (PI). This study aimed to establish multiple linear regressions of GT based on individual TK, LL and PI in patients with degenerative spines. Methods Four hundred sixty-nine adult patients aged older than 35 years with various degenerative spinal diseases were enrolled in this two-centre study between January 2017 and December 2020. Full-spine X-rays were performed for all the subjects in a standing position. The following regional and global parameters were measured in the sagittal plane: TK, LL, PI, pelvic tilt (PT), sagittal vertical axis (SVA) and GT. The correlations of the GT, PT and SVA with the TK, LL and PI were analysed, and then multiple linear regressions were constructed. Results GT was statistically correlated with TK, LL and PI. Additionally, TK, LL and PI were significant predictors for the GT, PT and SVA models. The relevant predictive formulae were as follows: GT = -9.60 + 1.09*PI + 0.89*LL + 0.42*TK (R 2  = 0.935), PT = -4.49 + 0.81*PI + 0.56*LL + 0.24*TK (R 2  = 0.792) and SVA = -25.68 + 2.98*LL + 2.37*PI + 1.67*TK (R 2  = 0.416). Conclusion The specific sagittal spinopelvic morphology, evaluated by GT parameters, should be determined by individual TK, LL and PI values in the degenerative spine. Surgeons can utilize such predictive models to better understand the degenerative evolution of sagittal alignment and recognize the relationships between regional parameters and global sagittal alignment to customize a precise correction strategy.
doi_str_mv 10.1007/s00586-021-06947-5
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This study aimed to establish multiple linear regressions of GT based on individual TK, LL and PI in patients with degenerative spines. Methods Four hundred sixty-nine adult patients aged older than 35 years with various degenerative spinal diseases were enrolled in this two-centre study between January 2017 and December 2020. Full-spine X-rays were performed for all the subjects in a standing position. The following regional and global parameters were measured in the sagittal plane: TK, LL, PI, pelvic tilt (PT), sagittal vertical axis (SVA) and GT. The correlations of the GT, PT and SVA with the TK, LL and PI were analysed, and then multiple linear regressions were constructed. Results GT was statistically correlated with TK, LL and PI. Additionally, TK, LL and PI were significant predictors for the GT, PT and SVA models. The relevant predictive formulae were as follows: GT = -9.60 + 1.09*PI + 0.89*LL + 0.42*TK (R 2  = 0.935), PT = -4.49 + 0.81*PI + 0.56*LL + 0.24*TK (R 2  = 0.792) and SVA = -25.68 + 2.98*LL + 2.37*PI + 1.67*TK (R 2  = 0.416). Conclusion The specific sagittal spinopelvic morphology, evaluated by GT parameters, should be determined by individual TK, LL and PI values in the degenerative spine. Surgeons can utilize such predictive models to better understand the degenerative evolution of sagittal alignment and recognize the relationships between regional parameters and global sagittal alignment to customize a precise correction strategy.</description><identifier>ISSN: 0940-6719</identifier><identifier>EISSN: 1432-0932</identifier><identifier>DOI: 10.1007/s00586-021-06947-5</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Arthritis ; Back surgery ; Degenerative disc disease ; Disease ; Kyphosis ; Medicine ; Medicine &amp; Public Health ; Morphology ; Neurosurgery ; Original Article ; Patients ; Prediction models ; Software ; Spine (lumbar) ; Surgeons ; Surgical Orthopedics ; Thorax ; Womens health ; X-rays</subject><ispartof>European spine journal, 2021-11, Vol.30 (11), p.3191-3199</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-p190t-974ff916dddd3a43740d47e0300353cc62e22112480834aa92660c79895171c43</cites><orcidid>0000-0002-5076-096X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00586-021-06947-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00586-021-06947-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Pan, Changyu</creatorcontrib><creatorcontrib>Wang, Guodong</creatorcontrib><creatorcontrib>Li, Yunchao</creatorcontrib><creatorcontrib>Kuang, Lei</creatorcontrib><creatorcontrib>Sun, Jianmin</creatorcontrib><creatorcontrib>Lv, Guohua</creatorcontrib><title>Predictive model of global tilt (GT) determined by individual thoracic kyphosis, lumbar lordosis and pelvic incidence in the human degenerative spine</title><title>European spine journal</title><addtitle>Eur Spine J</addtitle><description>Purpose Previous studies only investigated the simple linear relationships of global tilt (GT) with thoracic kyphosis (TK), lumbar lordosis (LL) and pelvic incidence (PI). This study aimed to establish multiple linear regressions of GT based on individual TK, LL and PI in patients with degenerative spines. Methods Four hundred sixty-nine adult patients aged older than 35 years with various degenerative spinal diseases were enrolled in this two-centre study between January 2017 and December 2020. Full-spine X-rays were performed for all the subjects in a standing position. The following regional and global parameters were measured in the sagittal plane: TK, LL, PI, pelvic tilt (PT), sagittal vertical axis (SVA) and GT. The correlations of the GT, PT and SVA with the TK, LL and PI were analysed, and then multiple linear regressions were constructed. Results GT was statistically correlated with TK, LL and PI. Additionally, TK, LL and PI were significant predictors for the GT, PT and SVA models. The relevant predictive formulae were as follows: GT = -9.60 + 1.09*PI + 0.89*LL + 0.42*TK (R 2  = 0.935), PT = -4.49 + 0.81*PI + 0.56*LL + 0.24*TK (R 2  = 0.792) and SVA = -25.68 + 2.98*LL + 2.37*PI + 1.67*TK (R 2  = 0.416). Conclusion The specific sagittal spinopelvic morphology, evaluated by GT parameters, should be determined by individual TK, LL and PI values in the degenerative spine. Surgeons can utilize such predictive models to better understand the degenerative evolution of sagittal alignment and recognize the relationships between regional parameters and global sagittal alignment to customize a precise correction strategy.</description><subject>Arthritis</subject><subject>Back surgery</subject><subject>Degenerative disc disease</subject><subject>Disease</subject><subject>Kyphosis</subject><subject>Medicine</subject><subject>Medicine &amp; Public Health</subject><subject>Morphology</subject><subject>Neurosurgery</subject><subject>Original Article</subject><subject>Patients</subject><subject>Prediction models</subject><subject>Software</subject><subject>Spine (lumbar)</subject><subject>Surgeons</subject><subject>Surgical Orthopedics</subject><subject>Thorax</subject><subject>Womens health</subject><subject>X-rays</subject><issn>0940-6719</issn><issn>1432-0932</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNpdkc-KFDEQxhtRcFx9AU8BLyvYa-V_5yiLrsLCeljPTSapmcmaTtqke2AfxPc1syMI1qWK4ldfffB13VsKVxRAf6wAclA9MNqDMkL38lm3oYKzHgxnz7sNGAG90tS87F7V-gBApQG16X5_L-iDW8IRyZQ9RpJ3ZB_z1kayhLiQy5v798TjgmUKCT3ZPpKQfDgGv56QQy7WBUd-Ps6HXEP9QOI6bW0hMRd_WhCbPJkxHhsUkgsek8M2tVMkh3WyqanvMWGxTybq3N687l7sbKz45m-_6H58-Xx__bW_vbv5dv3ptp-pgaU3Wux2hirfilvBtQAvNAIH4JI7pxgyRikTAwxcWGuYUuC0GYykmjrBL7rLs-5c8q8V6zJOoTqM0SbMax2ZlJoxo_kJffcf-pDXkpq7Rg2KGsHl0Ch-pupcQtpj-UdRGE9RjeeoxhbV-BTVKPkfxseHUQ</recordid><startdate>20211101</startdate><enddate>20211101</enddate><creator>Pan, Changyu</creator><creator>Wang, Guodong</creator><creator>Li, Yunchao</creator><creator>Kuang, Lei</creator><creator>Sun, Jianmin</creator><creator>Lv, Guohua</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>3V.</scope><scope>7QP</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-5076-096X</orcidid></search><sort><creationdate>20211101</creationdate><title>Predictive model of global tilt (GT) determined by individual thoracic kyphosis, lumbar lordosis and pelvic incidence in the human degenerative spine</title><author>Pan, Changyu ; Wang, Guodong ; Li, Yunchao ; Kuang, Lei ; Sun, Jianmin ; Lv, Guohua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p190t-974ff916dddd3a43740d47e0300353cc62e22112480834aa92660c79895171c43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Arthritis</topic><topic>Back surgery</topic><topic>Degenerative disc disease</topic><topic>Disease</topic><topic>Kyphosis</topic><topic>Medicine</topic><topic>Medicine &amp; Public Health</topic><topic>Morphology</topic><topic>Neurosurgery</topic><topic>Original Article</topic><topic>Patients</topic><topic>Prediction models</topic><topic>Software</topic><topic>Spine (lumbar)</topic><topic>Surgeons</topic><topic>Surgical Orthopedics</topic><topic>Thorax</topic><topic>Womens health</topic><topic>X-rays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pan, Changyu</creatorcontrib><creatorcontrib>Wang, Guodong</creatorcontrib><creatorcontrib>Li, Yunchao</creatorcontrib><creatorcontrib>Kuang, Lei</creatorcontrib><creatorcontrib>Sun, Jianmin</creatorcontrib><creatorcontrib>Lv, Guohua</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>Calcium &amp; Calcified Tissue Abstracts</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma 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 Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical 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>MEDLINE - Academic</collection><jtitle>European spine journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pan, Changyu</au><au>Wang, Guodong</au><au>Li, Yunchao</au><au>Kuang, Lei</au><au>Sun, Jianmin</au><au>Lv, Guohua</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predictive model of global tilt (GT) determined by individual thoracic kyphosis, lumbar lordosis and pelvic incidence in the human degenerative spine</atitle><jtitle>European spine journal</jtitle><stitle>Eur Spine J</stitle><date>2021-11-01</date><risdate>2021</risdate><volume>30</volume><issue>11</issue><spage>3191</spage><epage>3199</epage><pages>3191-3199</pages><issn>0940-6719</issn><eissn>1432-0932</eissn><abstract>Purpose Previous studies only investigated the simple linear relationships of global tilt (GT) with thoracic kyphosis (TK), lumbar lordosis (LL) and pelvic incidence (PI). This study aimed to establish multiple linear regressions of GT based on individual TK, LL and PI in patients with degenerative spines. Methods Four hundred sixty-nine adult patients aged older than 35 years with various degenerative spinal diseases were enrolled in this two-centre study between January 2017 and December 2020. Full-spine X-rays were performed for all the subjects in a standing position. The following regional and global parameters were measured in the sagittal plane: TK, LL, PI, pelvic tilt (PT), sagittal vertical axis (SVA) and GT. The correlations of the GT, PT and SVA with the TK, LL and PI were analysed, and then multiple linear regressions were constructed. Results GT was statistically correlated with TK, LL and PI. Additionally, TK, LL and PI were significant predictors for the GT, PT and SVA models. The relevant predictive formulae were as follows: GT = -9.60 + 1.09*PI + 0.89*LL + 0.42*TK (R 2  = 0.935), PT = -4.49 + 0.81*PI + 0.56*LL + 0.24*TK (R 2  = 0.792) and SVA = -25.68 + 2.98*LL + 2.37*PI + 1.67*TK (R 2  = 0.416). Conclusion The specific sagittal spinopelvic morphology, evaluated by GT parameters, should be determined by individual TK, LL and PI values in the degenerative spine. Surgeons can utilize such predictive models to better understand the degenerative evolution of sagittal alignment and recognize the relationships between regional parameters and global sagittal alignment to customize a precise correction strategy.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00586-021-06947-5</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-5076-096X</orcidid></addata></record>
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subjects Arthritis
Back surgery
Degenerative disc disease
Disease
Kyphosis
Medicine
Medicine & Public Health
Morphology
Neurosurgery
Original Article
Patients
Prediction models
Software
Spine (lumbar)
Surgeons
Surgical Orthopedics
Thorax
Womens health
X-rays
title Predictive model of global tilt (GT) determined by individual thoracic kyphosis, lumbar lordosis and pelvic incidence in the human degenerative spine
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