Loading…
Development and validation of a nomogram for predicting Mycoplasmapneumoniae pneumonia in adults
The study aimed to explore predictors of Mycoplasma pneumoniae pneumonia (MPP) in adults and develop a nomogram predictive model in order to identify high-risk patients early. We retrospectively analysed the clinical data of a total of 337 adult patients with community-acquired pneumonia (CAP) and d...
Saved in:
Published in: | Scientific reports 2022-12, Vol.12 (1), p.21859 |
---|---|
Main Authors: | , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | cdi_FETCH-LOGICAL-p157t-9dae10d9f3a5cd917651c0d0af643b25b66a2ada97c09daf698220f474be98a13 |
container_end_page | |
container_issue | 1 |
container_start_page | 21859 |
container_title | Scientific reports |
container_volume | 12 |
creator | Ren, Yuan Wang, Yan Liang, Ruifeng Hao, Binwei Wang, Hongxia Yuan, Jianwei Wang, Lin Guo, Zhizun Zhang, Jianwei |
description | The study aimed to explore predictors of
Mycoplasma pneumoniae pneumonia
(MPP) in adults and develop a nomogram predictive model in order to identify high-risk patients early. We retrospectively analysed the clinical data of a total of 337 adult patients with community-acquired pneumonia (CAP) and divided them into MPP and non-MPP groups according to whether they were infected with MP. Univariate and multivariate logistic regression analyses were used to screen independent predictors of MPP in adults and to developed a nomogram model. Receiver operating characteristic (ROC) curve, calibration curve, concordance index (C-index), and decision curve analysis (DCA) were used for the validation of the evaluation model. Finally, the nomogram was further evaluated by internal verification. Age, body temperature, dry cough, dizziness, CRP and tree-in-bud sign were independent predictors of MPP in adults
(P
|
doi_str_mv | 10.1038/s41598-022-26565-5 |
format | article |
fullrecord | <record><control><sourceid>proquest_sprin</sourceid><recordid>TN_cdi_proquest_journals_2755190621</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2755190621</sourcerecordid><originalsourceid>FETCH-LOGICAL-p157t-9dae10d9f3a5cd917651c0d0af643b25b66a2ada97c09daf698220f474be98a13</originalsourceid><addsrcrecordid>eNpFkE1LxDAQhoMguKz7BzwFPEfz0aTNUdZPULzoOc42ydKlTWLSLvjv7bqic5k5PMzL-yB0wegVo6K5LhWTuiGUc8KVVJLIE7TgtJKEC87P0KqUHZ1Hcl0xvUAft27v-pgGF0YMweI99J2FsYsBR48BhzjEbYYB-5hxys527diFLX75amPqoQyQgpuGGDpw-O_EXcBgp34s5-jUQ1_c6ncv0fv93dv6kTy_Pjytb55JYrIeibbgGLXaC5Ct1axWkrXUUvCqEhsuN0oBBwu6bunMeqUbzqmv6mrjdANMLNHl8W_K8XNyZTS7OOUwRxpeS8k0VfxAiSNVUp5buPxPMWoOBs3RoJkNmh-DRopv4rBnjA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2755190621</pqid></control><display><type>article</type><title>Development and validation of a nomogram for predicting Mycoplasmapneumoniae pneumonia in adults</title><source>Publicly Available Content (ProQuest)</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><source>Springer Nature - nature.com Journals - Fully Open Access</source><creator>Ren, Yuan ; Wang, Yan ; Liang, Ruifeng ; Hao, Binwei ; Wang, Hongxia ; Yuan, Jianwei ; Wang, Lin ; Guo, Zhizun ; Zhang, Jianwei</creator><creatorcontrib>Ren, Yuan ; Wang, Yan ; Liang, Ruifeng ; Hao, Binwei ; Wang, Hongxia ; Yuan, Jianwei ; Wang, Lin ; Guo, Zhizun ; Zhang, Jianwei</creatorcontrib><description>The study aimed to explore predictors of
Mycoplasma pneumoniae pneumonia
(MPP) in adults and develop a nomogram predictive model in order to identify high-risk patients early. We retrospectively analysed the clinical data of a total of 337 adult patients with community-acquired pneumonia (CAP) and divided them into MPP and non-MPP groups according to whether they were infected with MP. Univariate and multivariate logistic regression analyses were used to screen independent predictors of MPP in adults and to developed a nomogram model. Receiver operating characteristic (ROC) curve, calibration curve, concordance index (C-index), and decision curve analysis (DCA) were used for the validation of the evaluation model. Finally, the nomogram was further evaluated by internal verification. Age, body temperature, dry cough, dizziness, CRP and tree-in-bud sign were independent predictors of MPP in adults
(P
<
0.05
). The nomogram showed high accuracy with C-index of 0.836 and well-fitted calibration curves in both the training and validation sets. The area under the receiver operating curve (AUROC) was 0.829 (95% CI 0.774–0.883) for the training set and 0.847 (95% CI 0.768–0.925) for the validation set. This nomogram prediction model can accurately predict the risk of MPP occurrence in adults, which helps clinicians identify high-risk patients at an early stage and make drug selection and clinical decisions.</description><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-022-26565-5</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>692/308 ; 692/499 ; 692/53 ; 692/699 ; 692/700 ; Body temperature ; Calibration ; Cough ; Humanities and Social Sciences ; multidisciplinary ; Nomograms ; Pneumonia ; Prediction models ; Risk groups ; Science ; Science (multidisciplinary)</subject><ispartof>Scientific reports, 2022-12, Vol.12 (1), p.21859</ispartof><rights>The Author(s) 2022</rights><rights>The Author(s) 2022. 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><cites>FETCH-LOGICAL-p157t-9dae10d9f3a5cd917651c0d0af643b25b66a2ada97c09daf698220f474be98a13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2755190621/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2755190621?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Ren, Yuan</creatorcontrib><creatorcontrib>Wang, Yan</creatorcontrib><creatorcontrib>Liang, Ruifeng</creatorcontrib><creatorcontrib>Hao, Binwei</creatorcontrib><creatorcontrib>Wang, Hongxia</creatorcontrib><creatorcontrib>Yuan, Jianwei</creatorcontrib><creatorcontrib>Wang, Lin</creatorcontrib><creatorcontrib>Guo, Zhizun</creatorcontrib><creatorcontrib>Zhang, Jianwei</creatorcontrib><title>Development and validation of a nomogram for predicting Mycoplasmapneumoniae pneumonia in adults</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><description>The study aimed to explore predictors of
Mycoplasma pneumoniae pneumonia
(MPP) in adults and develop a nomogram predictive model in order to identify high-risk patients early. We retrospectively analysed the clinical data of a total of 337 adult patients with community-acquired pneumonia (CAP) and divided them into MPP and non-MPP groups according to whether they were infected with MP. Univariate and multivariate logistic regression analyses were used to screen independent predictors of MPP in adults and to developed a nomogram model. Receiver operating characteristic (ROC) curve, calibration curve, concordance index (C-index), and decision curve analysis (DCA) were used for the validation of the evaluation model. Finally, the nomogram was further evaluated by internal verification. Age, body temperature, dry cough, dizziness, CRP and tree-in-bud sign were independent predictors of MPP in adults
(P
<
0.05
). The nomogram showed high accuracy with C-index of 0.836 and well-fitted calibration curves in both the training and validation sets. The area under the receiver operating curve (AUROC) was 0.829 (95% CI 0.774–0.883) for the training set and 0.847 (95% CI 0.768–0.925) for the validation set. This nomogram prediction model can accurately predict the risk of MPP occurrence in adults, which helps clinicians identify high-risk patients at an early stage and make drug selection and clinical decisions.</description><subject>692/308</subject><subject>692/499</subject><subject>692/53</subject><subject>692/699</subject><subject>692/700</subject><subject>Body temperature</subject><subject>Calibration</subject><subject>Cough</subject><subject>Humanities and Social Sciences</subject><subject>multidisciplinary</subject><subject>Nomograms</subject><subject>Pneumonia</subject><subject>Prediction models</subject><subject>Risk groups</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNpFkE1LxDAQhoMguKz7BzwFPEfz0aTNUdZPULzoOc42ydKlTWLSLvjv7bqic5k5PMzL-yB0wegVo6K5LhWTuiGUc8KVVJLIE7TgtJKEC87P0KqUHZ1Hcl0xvUAft27v-pgGF0YMweI99J2FsYsBR48BhzjEbYYB-5hxys527diFLX75amPqoQyQgpuGGDpw-O_EXcBgp34s5-jUQ1_c6ncv0fv93dv6kTy_Pjytb55JYrIeibbgGLXaC5Ct1axWkrXUUvCqEhsuN0oBBwu6bunMeqUbzqmv6mrjdANMLNHl8W_K8XNyZTS7OOUwRxpeS8k0VfxAiSNVUp5buPxPMWoOBs3RoJkNmh-DRopv4rBnjA</recordid><startdate>20221217</startdate><enddate>20221217</enddate><creator>Ren, Yuan</creator><creator>Wang, Yan</creator><creator>Liang, Ruifeng</creator><creator>Hao, Binwei</creator><creator>Wang, Hongxia</creator><creator>Yuan, Jianwei</creator><creator>Wang, Lin</creator><creator>Guo, Zhizun</creator><creator>Zhang, Jianwei</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</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>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>Q9U</scope></search><sort><creationdate>20221217</creationdate><title>Development and validation of a nomogram for predicting Mycoplasmapneumoniae pneumonia in adults</title><author>Ren, Yuan ; Wang, Yan ; Liang, Ruifeng ; Hao, Binwei ; Wang, Hongxia ; Yuan, Jianwei ; Wang, Lin ; Guo, Zhizun ; Zhang, Jianwei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p157t-9dae10d9f3a5cd917651c0d0af643b25b66a2ada97c09daf698220f474be98a13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>692/308</topic><topic>692/499</topic><topic>692/53</topic><topic>692/699</topic><topic>692/700</topic><topic>Body temperature</topic><topic>Calibration</topic><topic>Cough</topic><topic>Humanities and Social Sciences</topic><topic>multidisciplinary</topic><topic>Nomograms</topic><topic>Pneumonia</topic><topic>Prediction models</topic><topic>Risk groups</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ren, Yuan</creatorcontrib><creatorcontrib>Wang, Yan</creatorcontrib><creatorcontrib>Liang, Ruifeng</creatorcontrib><creatorcontrib>Hao, Binwei</creatorcontrib><creatorcontrib>Wang, Hongxia</creatorcontrib><creatorcontrib>Yuan, Jianwei</creatorcontrib><creatorcontrib>Wang, Lin</creatorcontrib><creatorcontrib>Guo, Zhizun</creatorcontrib><creatorcontrib>Zhang, Jianwei</creatorcontrib><collection>SpringerOpen</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)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</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>ProQuest Science Journals</collection><collection>Biological Science Database</collection><collection>Publicly Available Content (ProQuest)</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 Basic</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ren, Yuan</au><au>Wang, Yan</au><au>Liang, Ruifeng</au><au>Hao, Binwei</au><au>Wang, Hongxia</au><au>Yuan, Jianwei</au><au>Wang, Lin</au><au>Guo, Zhizun</au><au>Zhang, Jianwei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development and validation of a nomogram for predicting Mycoplasmapneumoniae pneumonia in adults</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><date>2022-12-17</date><risdate>2022</risdate><volume>12</volume><issue>1</issue><spage>21859</spage><pages>21859-</pages><eissn>2045-2322</eissn><abstract>The study aimed to explore predictors of
Mycoplasma pneumoniae pneumonia
(MPP) in adults and develop a nomogram predictive model in order to identify high-risk patients early. We retrospectively analysed the clinical data of a total of 337 adult patients with community-acquired pneumonia (CAP) and divided them into MPP and non-MPP groups according to whether they were infected with MP. Univariate and multivariate logistic regression analyses were used to screen independent predictors of MPP in adults and to developed a nomogram model. Receiver operating characteristic (ROC) curve, calibration curve, concordance index (C-index), and decision curve analysis (DCA) were used for the validation of the evaluation model. Finally, the nomogram was further evaluated by internal verification. Age, body temperature, dry cough, dizziness, CRP and tree-in-bud sign were independent predictors of MPP in adults
(P
<
0.05
). The nomogram showed high accuracy with C-index of 0.836 and well-fitted calibration curves in both the training and validation sets. The area under the receiver operating curve (AUROC) was 0.829 (95% CI 0.774–0.883) for the training set and 0.847 (95% CI 0.768–0.925) for the validation set. This nomogram prediction model can accurately predict the risk of MPP occurrence in adults, which helps clinicians identify high-risk patients at an early stage and make drug selection and clinical decisions.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><doi>10.1038/s41598-022-26565-5</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2045-2322 |
ispartof | Scientific reports, 2022-12, Vol.12 (1), p.21859 |
issn | 2045-2322 |
language | eng |
recordid | cdi_proquest_journals_2755190621 |
source | Publicly Available Content (ProQuest); PubMed Central; Free Full-Text Journals in Chemistry; Springer Nature - nature.com Journals - Fully Open Access |
subjects | 692/308 692/499 692/53 692/699 692/700 Body temperature Calibration Cough Humanities and Social Sciences multidisciplinary Nomograms Pneumonia Prediction models Risk groups Science Science (multidisciplinary) |
title | Development and validation of a nomogram for predicting Mycoplasmapneumoniae pneumonia in adults |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T00%3A47%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_sprin&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Development%20and%20validation%20of%20a%20nomogram%20for%20predicting%20Mycoplasmapneumoniae%20pneumonia%20in%20adults&rft.jtitle=Scientific%20reports&rft.au=Ren,%20Yuan&rft.date=2022-12-17&rft.volume=12&rft.issue=1&rft.spage=21859&rft.pages=21859-&rft.eissn=2045-2322&rft_id=info:doi/10.1038/s41598-022-26565-5&rft_dat=%3Cproquest_sprin%3E2755190621%3C/proquest_sprin%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-p157t-9dae10d9f3a5cd917651c0d0af643b25b66a2ada97c09daf698220f474be98a13%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2755190621&rft_id=info:pmid/&rfr_iscdi=true |