Constructing of predictive model for the surgical effect of patients with cleft lip and palate
To explore effective factors of surgical effect for patients with cleft lip and palate, and to construct the predictive model of surgical effect, which provide reference for improving the effect of cleft lip and palate surgery. This study has been ethically reviewed and approved by the Medical Ethic...
Gespeichert in:
| Veröffentlicht in: | PloS one 2023-06, Vol.18 (6), p.e0286976-e0286976 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e0286976 |
|---|---|
| container_issue | 6 |
| container_start_page | e0286976 |
| container_title | PloS one |
| container_volume | 18 |
| creator | Liu, Na Yang, Jingyuan Tan, Fang Zhu, Haijian |
| description | To explore effective factors of surgical effect for patients with cleft lip and palate, and to construct the predictive model of surgical effect, which provide reference for improving the effect of cleft lip and palate surgery.
This study has been ethically reviewed and approved by the Medical Ethics Committee of Guiyang Stomatological Hospital before the study began.A total of 997 cases of cleft lip and palate surgical treatment in Guiyang Stomatological Hospital from 2015 to 2020 were collected. Logistic regression analysis was used to analyze the factors influencing the surgical outcome, and a score system was established by assigning values to the influencing factors using the nomogram. Data of 110 patients were verified, and decision curve analysis was used to evaluate the predicted results.
Logistic regression analysis showed that the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition during pregnancy and labor intensity during pregnancy were independent risk factors for poor surgical results (all P |
| doi_str_mv | 10.1371/journal.pone.0286976 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2831773674</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A755350385</galeid><doaj_id>oai_doaj_org_article_4235a2ed32784f18aefc31c6be1422e9</doaj_id><sourcerecordid>A755350385</sourcerecordid><originalsourceid>FETCH-LOGICAL-c642t-80241d1feb863088551b98ae743d7908e3e195a0c65abaebbffb41ff394d58603</originalsourceid><addsrcrecordid>eNqNk0uP0zAQxyMEYpfCN0AQCQnBocWPOHFOaFXxqLTSSryOWI4zTl25cdd2Fvj2uG121aA9oBwc27_5z8MzWfYcowWmFX63cYPvpV3sXA8LRHhZV-WD7BzXlMxLgujDk_-z7EkIG4QY5WX5ODujFa3Tjp9nP5euD9EPKpq-y53Odx5ak3Y3kG9dCzbXzudxDXkYfGeUtDloDSoeWBkN9DHkv0xc58qCjrk1u1z2bbqzMsLT7JGWNsCzcZ1l3z9--Lb8PL-8-rRaXlzOVVmQOOeIFLjFGhpeUsQ5Y7ipuYSqoG1VIw4UcM0kUiWTjYSm0bopsNa0LlrGS0Rn2cuj7s66IMbSBEE4xVVFy6Qzy1ZHonVyI3bebKX_I5w04nDgfCekjyYlIQpCmSTQUlLxQuMUh1YUq7IBXBACddJ6P3obmi20KtXASzsRnd70Zi06dyMwopgito_3zajg3fUAIYqtCQqslT244RA4YRWh6aFm2at_0PvTG6lOpgxMr11yrPai4qJijCafnCVqcQ-Vvha2RqVG0iadTwzeTgwSE-F37OQQglh9_fL_7NWPKfv6hF2DtHEdnB2iSe04BYsjqLwLwYO-qzJGYj8Ht9UQ-zkQ4xwksxenL3RndNv49C-E9wJ5</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2831773674</pqid></control><display><type>article</type><title>Constructing of predictive model for the surgical effect of patients with cleft lip and palate</title><source>PubMed (Medline)</source><source>Public Library of Science</source><source>Directory of Open Access Journals</source><source>Free Full-Text Journals in Chemistry</source><source>EZB Electronic Journals Library</source><creator>Liu, Na ; Yang, Jingyuan ; Tan, Fang ; Zhu, Haijian</creator><contributor>Ashaat, Engy Asem</contributor><creatorcontrib>Liu, Na ; Yang, Jingyuan ; Tan, Fang ; Zhu, Haijian ; Ashaat, Engy Asem</creatorcontrib><description>To explore effective factors of surgical effect for patients with cleft lip and palate, and to construct the predictive model of surgical effect, which provide reference for improving the effect of cleft lip and palate surgery.
This study has been ethically reviewed and approved by the Medical Ethics Committee of Guiyang Stomatological Hospital before the study began.A total of 997 cases of cleft lip and palate surgical treatment in Guiyang Stomatological Hospital from 2015 to 2020 were collected. Logistic regression analysis was used to analyze the factors influencing the surgical outcome, and a score system was established by assigning values to the influencing factors using the nomogram. Data of 110 patients were verified, and decision curve analysis was used to evaluate the predicted results.
Logistic regression analysis showed that the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition during pregnancy and labor intensity during pregnancy were independent risk factors for poor surgical results (all P<0.05). The predictive model was built by including the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition and labor intensity during pregnancy into the predictive scoring system. The critical value was 273, the area under ROC curve (AUC) was 0.733(95%CI:0.704~0.76), the sensitivity was 89.57%, and the specificity was 48.14%.When the external validation data of 110 patients were brought into the score, the AUC of poor diagnostic value reached 74.5%, P<0.05, which was close to the modeling accuracy of 73.3%.
This study constructed a predictive model of surgical effect for patients with cleft lip and palate, which can be used for the clinical prediction of cleft lip and palate patients in Guizhou Province.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0286976</identifier><identifier>PMID: 37390058</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Biology and Life Sciences ; Birth defects ; Breast milk ; Breastfeeding & lactation ; Care and treatment ; Cleft lip ; Cleft lip/palate ; Cleft palate ; Decision analysis ; Diagnosis ; Ethics ; Hospitals ; Labor ; Medicine and Health Sciences ; Methods ; Model accuracy ; Modelling ; Multivariate analysis ; Nomograms ; Nomographs ; Nutrition ; Obstetrics ; Patients ; Physical Sciences ; Prediction models ; Pregnancy ; Regression analysis ; Research and Analysis Methods ; Risk factors ; Software ; Statistical analysis ; Surgery ; Surgical outcomes</subject><ispartof>PloS one, 2023-06, Vol.18 (6), p.e0286976-e0286976</ispartof><rights>Copyright: © 2023 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 Liu et al 2023 Liu et al</rights><rights>2023 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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><cites>FETCH-LOGICAL-c642t-80241d1feb863088551b98ae743d7908e3e195a0c65abaebbffb41ff394d58603</cites><orcidid>0000-0001-9808-4801</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10313050/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10313050/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2100,2926,23864,27922,27923,53789,53791,79370,79371</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37390058$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Ashaat, Engy Asem</contributor><creatorcontrib>Liu, Na</creatorcontrib><creatorcontrib>Yang, Jingyuan</creatorcontrib><creatorcontrib>Tan, Fang</creatorcontrib><creatorcontrib>Zhu, Haijian</creatorcontrib><title>Constructing of predictive model for the surgical effect of patients with cleft lip and palate</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>To explore effective factors of surgical effect for patients with cleft lip and palate, and to construct the predictive model of surgical effect, which provide reference for improving the effect of cleft lip and palate surgery.
This study has been ethically reviewed and approved by the Medical Ethics Committee of Guiyang Stomatological Hospital before the study began.A total of 997 cases of cleft lip and palate surgical treatment in Guiyang Stomatological Hospital from 2015 to 2020 were collected. Logistic regression analysis was used to analyze the factors influencing the surgical outcome, and a score system was established by assigning values to the influencing factors using the nomogram. Data of 110 patients were verified, and decision curve analysis was used to evaluate the predicted results.
Logistic regression analysis showed that the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition during pregnancy and labor intensity during pregnancy were independent risk factors for poor surgical results (all P<0.05). The predictive model was built by including the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition and labor intensity during pregnancy into the predictive scoring system. The critical value was 273, the area under ROC curve (AUC) was 0.733(95%CI:0.704~0.76), the sensitivity was 89.57%, and the specificity was 48.14%.When the external validation data of 110 patients were brought into the score, the AUC of poor diagnostic value reached 74.5%, P<0.05, which was close to the modeling accuracy of 73.3%.
This study constructed a predictive model of surgical effect for patients with cleft lip and palate, which can be used for the clinical prediction of cleft lip and palate patients in Guizhou Province.</description><subject>Biology and Life Sciences</subject><subject>Birth defects</subject><subject>Breast milk</subject><subject>Breastfeeding & lactation</subject><subject>Care and treatment</subject><subject>Cleft lip</subject><subject>Cleft lip/palate</subject><subject>Cleft palate</subject><subject>Decision analysis</subject><subject>Diagnosis</subject><subject>Ethics</subject><subject>Hospitals</subject><subject>Labor</subject><subject>Medicine and Health Sciences</subject><subject>Methods</subject><subject>Model accuracy</subject><subject>Modelling</subject><subject>Multivariate analysis</subject><subject>Nomograms</subject><subject>Nomographs</subject><subject>Nutrition</subject><subject>Obstetrics</subject><subject>Patients</subject><subject>Physical Sciences</subject><subject>Prediction models</subject><subject>Pregnancy</subject><subject>Regression analysis</subject><subject>Research and Analysis Methods</subject><subject>Risk factors</subject><subject>Software</subject><subject>Statistical analysis</subject><subject>Surgery</subject><subject>Surgical outcomes</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk0uP0zAQxyMEYpfCN0AQCQnBocWPOHFOaFXxqLTSSryOWI4zTl25cdd2Fvj2uG121aA9oBwc27_5z8MzWfYcowWmFX63cYPvpV3sXA8LRHhZV-WD7BzXlMxLgujDk_-z7EkIG4QY5WX5ODujFa3Tjp9nP5euD9EPKpq-y53Odx5ak3Y3kG9dCzbXzudxDXkYfGeUtDloDSoeWBkN9DHkv0xc58qCjrk1u1z2bbqzMsLT7JGWNsCzcZ1l3z9--Lb8PL-8-rRaXlzOVVmQOOeIFLjFGhpeUsQ5Y7ipuYSqoG1VIw4UcM0kUiWTjYSm0bopsNa0LlrGS0Rn2cuj7s66IMbSBEE4xVVFy6Qzy1ZHonVyI3bebKX_I5w04nDgfCekjyYlIQpCmSTQUlLxQuMUh1YUq7IBXBACddJ6P3obmi20KtXASzsRnd70Zi06dyMwopgito_3zajg3fUAIYqtCQqslT244RA4YRWh6aFm2at_0PvTG6lOpgxMr11yrPai4qJijCafnCVqcQ-Vvha2RqVG0iadTwzeTgwSE-F37OQQglh9_fL_7NWPKfv6hF2DtHEdnB2iSe04BYsjqLwLwYO-qzJGYj8Ht9UQ-zkQ4xwksxenL3RndNv49C-E9wJ5</recordid><startdate>20230630</startdate><enddate>20230630</enddate><creator>Liu, Na</creator><creator>Yang, Jingyuan</creator><creator>Tan, Fang</creator><creator>Zhu, Haijian</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9808-4801</orcidid></search><sort><creationdate>20230630</creationdate><title>Constructing of predictive model for the surgical effect of patients with cleft lip and palate</title><author>Liu, Na ; Yang, Jingyuan ; Tan, Fang ; Zhu, Haijian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c642t-80241d1feb863088551b98ae743d7908e3e195a0c65abaebbffb41ff394d58603</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Biology and Life Sciences</topic><topic>Birth defects</topic><topic>Breast milk</topic><topic>Breastfeeding & lactation</topic><topic>Care and treatment</topic><topic>Cleft lip</topic><topic>Cleft lip/palate</topic><topic>Cleft palate</topic><topic>Decision analysis</topic><topic>Diagnosis</topic><topic>Ethics</topic><topic>Hospitals</topic><topic>Labor</topic><topic>Medicine and Health Sciences</topic><topic>Methods</topic><topic>Model accuracy</topic><topic>Modelling</topic><topic>Multivariate analysis</topic><topic>Nomograms</topic><topic>Nomographs</topic><topic>Nutrition</topic><topic>Obstetrics</topic><topic>Patients</topic><topic>Physical Sciences</topic><topic>Prediction models</topic><topic>Pregnancy</topic><topic>Regression analysis</topic><topic>Research and Analysis Methods</topic><topic>Risk factors</topic><topic>Software</topic><topic>Statistical analysis</topic><topic>Surgery</topic><topic>Surgical outcomes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Na</creatorcontrib><creatorcontrib>Yang, Jingyuan</creatorcontrib><creatorcontrib>Tan, Fang</creatorcontrib><creatorcontrib>Zhu, Haijian</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale in Context: Opposing Viewpoints</collection><collection>Gale in Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology 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>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>Biological Sciences</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</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>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Na</au><au>Yang, Jingyuan</au><au>Tan, Fang</au><au>Zhu, Haijian</au><au>Ashaat, Engy Asem</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Constructing of predictive model for the surgical effect of patients with cleft lip and palate</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2023-06-30</date><risdate>2023</risdate><volume>18</volume><issue>6</issue><spage>e0286976</spage><epage>e0286976</epage><pages>e0286976-e0286976</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>To explore effective factors of surgical effect for patients with cleft lip and palate, and to construct the predictive model of surgical effect, which provide reference for improving the effect of cleft lip and palate surgery.
This study has been ethically reviewed and approved by the Medical Ethics Committee of Guiyang Stomatological Hospital before the study began.A total of 997 cases of cleft lip and palate surgical treatment in Guiyang Stomatological Hospital from 2015 to 2020 were collected. Logistic regression analysis was used to analyze the factors influencing the surgical outcome, and a score system was established by assigning values to the influencing factors using the nomogram. Data of 110 patients were verified, and decision curve analysis was used to evaluate the predicted results.
Logistic regression analysis showed that the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition during pregnancy and labor intensity during pregnancy were independent risk factors for poor surgical results (all P<0.05). The predictive model was built by including the number of surgeries, surgical methods, breast milk, prenatal examination, nutrition and labor intensity during pregnancy into the predictive scoring system. The critical value was 273, the area under ROC curve (AUC) was 0.733(95%CI:0.704~0.76), the sensitivity was 89.57%, and the specificity was 48.14%.When the external validation data of 110 patients were brought into the score, the AUC of poor diagnostic value reached 74.5%, P<0.05, which was close to the modeling accuracy of 73.3%.
This study constructed a predictive model of surgical effect for patients with cleft lip and palate, which can be used for the clinical prediction of cleft lip and palate patients in Guizhou Province.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>37390058</pmid><doi>10.1371/journal.pone.0286976</doi><tpages>e0286976</tpages><orcidid>https://orcid.org/0000-0001-9808-4801</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2023-06, Vol.18 (6), p.e0286976-e0286976 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2831773674 |
| source | PubMed (Medline); Public Library of Science; Directory of Open Access Journals; Free Full-Text Journals in Chemistry; EZB Electronic Journals Library |
| subjects | Biology and Life Sciences Birth defects Breast milk Breastfeeding & lactation Care and treatment Cleft lip Cleft lip/palate Cleft palate Decision analysis Diagnosis Ethics Hospitals Labor Medicine and Health Sciences Methods Model accuracy Modelling Multivariate analysis Nomograms Nomographs Nutrition Obstetrics Patients Physical Sciences Prediction models Pregnancy Regression analysis Research and Analysis Methods Risk factors Software Statistical analysis Surgery Surgical outcomes |
| title | Constructing of predictive model for the surgical effect of patients with cleft lip and palate |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T16%3A58%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Constructing%20of%20predictive%20model%20for%20the%20surgical%20effect%20of%20patients%20with%20cleft%20lip%20and%20palate&rft.jtitle=PloS%20one&rft.au=Liu,%20Na&rft.date=2023-06-30&rft.volume=18&rft.issue=6&rft.spage=e0286976&rft.epage=e0286976&rft.pages=e0286976-e0286976&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0286976&rft_dat=%3Cgale_plos_%3EA755350385%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2831773674&rft_id=info:pmid/37390058&rft_galeid=A755350385&rft_doaj_id=oai_doaj_org_article_4235a2ed32784f18aefc31c6be1422e9&rfr_iscdi=true |