Loading…
New predictive equations for estimating resting energy expenditure in subjects with normal weight and overweight
•Indirect calorimetry is considered the reference method for the measurement of resting energy expenditure (REE).•Predictive equations are commonly used as an alternative method for estimating REE.•New REE equations with bioimpedance analysis (BIA) variables for subjects with normal weight and overw...
Saved in:
| Published in: | Nutrition (Burbank, Los Angeles County, Calif.) Los Angeles County, Calif.), 2021-04, Vol.84, p.111105-111105, Article 111105 |
|---|---|
| Main Authors: | , , , , , , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Citations: | Items that this one cites Items that cite this one |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | cdi_FETCH-LOGICAL-c424t-ed364a8df5affbcc6d3d54951c974f8769f2384acb197cf257da628be4eedcd13 |
|---|---|
| cites | cdi_FETCH-LOGICAL-c424t-ed364a8df5affbcc6d3d54951c974f8769f2384acb197cf257da628be4eedcd13 |
| container_end_page | 111105 |
| container_issue | |
| container_start_page | 111105 |
| container_title | Nutrition (Burbank, Los Angeles County, Calif.) |
| container_volume | 84 |
| creator | Marra, Maurizio Sammarco, Rosa Cioffi, Iolanda Morlino, Delia Di Vincenzo, Olivia Speranza, Enza Pasanisi, Fabrizio |
| description | •Indirect calorimetry is considered the reference method for the measurement of resting energy expenditure (REE).•Predictive equations are commonly used as an alternative method for estimating REE.•New REE equations with bioimpedance analysis (BIA) variables for subjects with normal weight and overweight.•The equation with raw BIA variables showed the highest accuracy at individual level.
The aim of this study was to develop and validate new predictive equations for estimating resting energy expenditure (REE) in subjects with normal weight and overweight, considering anthropometric parameters as well as raw variables from bioimpedance analysis (BIA).
Adult participants with normal weight and overweight were recruited and randomly split into calibration and validation groups. Indirect calorimetry (IC) and BIA were performed in all subjects. New predictive equations were developed using the following models: model 1 with age, weight, stature, and body mass index (BMI) as predictors; and model 2: model 1 + raw BIA variables (bioimpedance index and phase angle). The accuracy of the new equations at both the group (bias) and individual (within ±10%) levels was tested in the validation group. Three published predictive equations were also compared, with the REE values measured by IC.
A total of 2483 adults were included for developing and validating the new equations. All selected formulas, including the new ones, showed a bias of |
| doi_str_mv | 10.1016/j.nut.2020.111105 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2480271408</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0899900720303889</els_id><sourcerecordid>2480271408</sourcerecordid><originalsourceid>FETCH-LOGICAL-c424t-ed364a8df5affbcc6d3d54951c974f8769f2384acb197cf257da628be4eedcd13</originalsourceid><addsrcrecordid>eNp9kUGPFCEQhYnRuOPqD_BiSLx46RFouoF4MpvVNdnoRc-EhmKWzgz0QveM--9l0quHPcileMlXL5X3EHpLyZYS2n8ct3GZt4ywqusj3TO0oVK0DWWcP0cbIpVqFCHiAr0qZSSEUNWrl-iibbkQVW3Q9B1OeMrggp3DETDcL2YOKRbsU8ZQ5nCoOu5wPv_rhAh594Dh9wTRhXnJgEPEZRlGsHPBpzDf4ZjywezxCcLubsYmOpyOkFf5Gr3wZl_gzeO8RL--XP-8umluf3z9dvX5trGc8bkB1_bcSOc74_1gbe9a13HVUasE91L0yrNWcmMHqoT1rBPO9EwOwAGcdbS9RB9W3ymn-6Uerw-hWNjvTYS0FM24JExQTmRF3z9Bx7TkWK_TrCOUC9lLXim6UjanUjJ4PeUaTn7QlOhzHXrUtQ59rkOvddSdd4_Oy3AA92_jb_4V-LQCUKM4Bsi62ADR1j5yzVO7FP5j_wdBaZ1t</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2501478684</pqid></control><display><type>article</type><title>New predictive equations for estimating resting energy expenditure in subjects with normal weight and overweight</title><source>Elsevier</source><creator>Marra, Maurizio ; Sammarco, Rosa ; Cioffi, Iolanda ; Morlino, Delia ; Di Vincenzo, Olivia ; Speranza, Enza ; Pasanisi, Fabrizio</creator><creatorcontrib>Marra, Maurizio ; Sammarco, Rosa ; Cioffi, Iolanda ; Morlino, Delia ; Di Vincenzo, Olivia ; Speranza, Enza ; Pasanisi, Fabrizio</creatorcontrib><description>•Indirect calorimetry is considered the reference method for the measurement of resting energy expenditure (REE).•Predictive equations are commonly used as an alternative method for estimating REE.•New REE equations with bioimpedance analysis (BIA) variables for subjects with normal weight and overweight.•The equation with raw BIA variables showed the highest accuracy at individual level.
The aim of this study was to develop and validate new predictive equations for estimating resting energy expenditure (REE) in subjects with normal weight and overweight, considering anthropometric parameters as well as raw variables from bioimpedance analysis (BIA).
Adult participants with normal weight and overweight were recruited and randomly split into calibration and validation groups. Indirect calorimetry (IC) and BIA were performed in all subjects. New predictive equations were developed using the following models: model 1 with age, weight, stature, and body mass index (BMI) as predictors; and model 2: model 1 + raw BIA variables (bioimpedance index and phase angle). The accuracy of the new equations at both the group (bias) and individual (within ±10%) levels was tested in the validation group. Three published predictive equations were also compared, with the REE values measured by IC.
A total of 2483 adults were included for developing and validating the new equations. All selected formulas, including the new ones, showed a bias of <5% in estimating REE at the group level. Accuracy at the individual level was slightly higher for the new equations, especially for the equation based on raw BIA variables (men = 70.3%; women = 72.3%).
Compared to the equations in the literature, the new equations showed good accuracy at both the group and individual levels, with a slight improvement in individual accuracy for the formula including raw BIA variables. However, future research is required to verify the role of the raw BIA variables in predicting REE in subjects with normal weight and overweight.</description><identifier>ISSN: 0899-9007</identifier><identifier>EISSN: 1873-1244</identifier><identifier>DOI: 10.1016/j.nut.2020.111105</identifier><identifier>PMID: 33477001</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Accuracy ; Age ; Bias ; Bioimpedance analysis ; Body composition ; Body mass index ; Body size ; Body weight ; Calibration ; Calorimetry ; Carbon dioxide ; Clinical medicine ; Energy ; Energy expenditure ; Estimation ; Formulas (mathematics) ; Indirect calorimetry ; Mathematical models ; Men ; Normal weight ; Overweight ; Phase angle ; Predictive equations ; Resting energy expenditure ; Sexes ; Variables ; Womens health</subject><ispartof>Nutrition (Burbank, Los Angeles County, Calif.), 2021-04, Vol.84, p.111105-111105, Article 111105</ispartof><rights>2020 The Author(s)</rights><rights>Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.</rights><rights>2020. The Author(s)</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c424t-ed364a8df5affbcc6d3d54951c974f8769f2384acb197cf257da628be4eedcd13</citedby><cites>FETCH-LOGICAL-c424t-ed364a8df5affbcc6d3d54951c974f8769f2384acb197cf257da628be4eedcd13</cites><orcidid>0000-0002-1408-209X ; 0000-0002-3258-7374 ; 0000-0002-3241-1897 ; 0000-0003-4224-7821</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33477001$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Marra, Maurizio</creatorcontrib><creatorcontrib>Sammarco, Rosa</creatorcontrib><creatorcontrib>Cioffi, Iolanda</creatorcontrib><creatorcontrib>Morlino, Delia</creatorcontrib><creatorcontrib>Di Vincenzo, Olivia</creatorcontrib><creatorcontrib>Speranza, Enza</creatorcontrib><creatorcontrib>Pasanisi, Fabrizio</creatorcontrib><title>New predictive equations for estimating resting energy expenditure in subjects with normal weight and overweight</title><title>Nutrition (Burbank, Los Angeles County, Calif.)</title><addtitle>Nutrition</addtitle><description>•Indirect calorimetry is considered the reference method for the measurement of resting energy expenditure (REE).•Predictive equations are commonly used as an alternative method for estimating REE.•New REE equations with bioimpedance analysis (BIA) variables for subjects with normal weight and overweight.•The equation with raw BIA variables showed the highest accuracy at individual level.
The aim of this study was to develop and validate new predictive equations for estimating resting energy expenditure (REE) in subjects with normal weight and overweight, considering anthropometric parameters as well as raw variables from bioimpedance analysis (BIA).
Adult participants with normal weight and overweight were recruited and randomly split into calibration and validation groups. Indirect calorimetry (IC) and BIA were performed in all subjects. New predictive equations were developed using the following models: model 1 with age, weight, stature, and body mass index (BMI) as predictors; and model 2: model 1 + raw BIA variables (bioimpedance index and phase angle). The accuracy of the new equations at both the group (bias) and individual (within ±10%) levels was tested in the validation group. Three published predictive equations were also compared, with the REE values measured by IC.
A total of 2483 adults were included for developing and validating the new equations. All selected formulas, including the new ones, showed a bias of <5% in estimating REE at the group level. Accuracy at the individual level was slightly higher for the new equations, especially for the equation based on raw BIA variables (men = 70.3%; women = 72.3%).
Compared to the equations in the literature, the new equations showed good accuracy at both the group and individual levels, with a slight improvement in individual accuracy for the formula including raw BIA variables. However, future research is required to verify the role of the raw BIA variables in predicting REE in subjects with normal weight and overweight.</description><subject>Accuracy</subject><subject>Age</subject><subject>Bias</subject><subject>Bioimpedance analysis</subject><subject>Body composition</subject><subject>Body mass index</subject><subject>Body size</subject><subject>Body weight</subject><subject>Calibration</subject><subject>Calorimetry</subject><subject>Carbon dioxide</subject><subject>Clinical medicine</subject><subject>Energy</subject><subject>Energy expenditure</subject><subject>Estimation</subject><subject>Formulas (mathematics)</subject><subject>Indirect calorimetry</subject><subject>Mathematical models</subject><subject>Men</subject><subject>Normal weight</subject><subject>Overweight</subject><subject>Phase angle</subject><subject>Predictive equations</subject><subject>Resting energy expenditure</subject><subject>Sexes</subject><subject>Variables</subject><subject>Womens health</subject><issn>0899-9007</issn><issn>1873-1244</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kUGPFCEQhYnRuOPqD_BiSLx46RFouoF4MpvVNdnoRc-EhmKWzgz0QveM--9l0quHPcileMlXL5X3EHpLyZYS2n8ct3GZt4ywqusj3TO0oVK0DWWcP0cbIpVqFCHiAr0qZSSEUNWrl-iibbkQVW3Q9B1OeMrggp3DETDcL2YOKRbsU8ZQ5nCoOu5wPv_rhAh594Dh9wTRhXnJgEPEZRlGsHPBpzDf4ZjywezxCcLubsYmOpyOkFf5Gr3wZl_gzeO8RL--XP-8umluf3z9dvX5trGc8bkB1_bcSOc74_1gbe9a13HVUasE91L0yrNWcmMHqoT1rBPO9EwOwAGcdbS9RB9W3ymn-6Uerw-hWNjvTYS0FM24JExQTmRF3z9Bx7TkWK_TrCOUC9lLXim6UjanUjJ4PeUaTn7QlOhzHXrUtQ59rkOvddSdd4_Oy3AA92_jb_4V-LQCUKM4Bsi62ADR1j5yzVO7FP5j_wdBaZ1t</recordid><startdate>202104</startdate><enddate>202104</enddate><creator>Marra, Maurizio</creator><creator>Sammarco, Rosa</creator><creator>Cioffi, Iolanda</creator><creator>Morlino, Delia</creator><creator>Di Vincenzo, Olivia</creator><creator>Speranza, Enza</creator><creator>Pasanisi, Fabrizio</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RQ</scope><scope>7RV</scope><scope>7TS</scope><scope>7U7</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AN0</scope><scope>ASE</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FPQ</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K6X</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-1408-209X</orcidid><orcidid>https://orcid.org/0000-0002-3258-7374</orcidid><orcidid>https://orcid.org/0000-0002-3241-1897</orcidid><orcidid>https://orcid.org/0000-0003-4224-7821</orcidid></search><sort><creationdate>202104</creationdate><title>New predictive equations for estimating resting energy expenditure in subjects with normal weight and overweight</title><author>Marra, Maurizio ; Sammarco, Rosa ; Cioffi, Iolanda ; Morlino, Delia ; Di Vincenzo, Olivia ; Speranza, Enza ; Pasanisi, Fabrizio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c424t-ed364a8df5affbcc6d3d54951c974f8769f2384acb197cf257da628be4eedcd13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Age</topic><topic>Bias</topic><topic>Bioimpedance analysis</topic><topic>Body composition</topic><topic>Body mass index</topic><topic>Body size</topic><topic>Body weight</topic><topic>Calibration</topic><topic>Calorimetry</topic><topic>Carbon dioxide</topic><topic>Clinical medicine</topic><topic>Energy</topic><topic>Energy expenditure</topic><topic>Estimation</topic><topic>Formulas (mathematics)</topic><topic>Indirect calorimetry</topic><topic>Mathematical models</topic><topic>Men</topic><topic>Normal weight</topic><topic>Overweight</topic><topic>Phase angle</topic><topic>Predictive equations</topic><topic>Resting energy expenditure</topic><topic>Sexes</topic><topic>Variables</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Marra, Maurizio</creatorcontrib><creatorcontrib>Sammarco, Rosa</creatorcontrib><creatorcontrib>Cioffi, Iolanda</creatorcontrib><creatorcontrib>Morlino, Delia</creatorcontrib><creatorcontrib>Di Vincenzo, Olivia</creatorcontrib><creatorcontrib>Speranza, Enza</creatorcontrib><creatorcontrib>Pasanisi, Fabrizio</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Career & Technical Education Database</collection><collection>Nursing & Allied Health Database</collection><collection>Physical Education Index</collection><collection>Toxicology Abstracts</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</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>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>British Nursing Database</collection><collection>British Nursing Index</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>British Nursing Index (BNI) (1985 to Present)</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>British Nursing Index</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>PML(ProQuest Medical Library)</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</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><collection>MEDLINE - Academic</collection><jtitle>Nutrition (Burbank, Los Angeles County, Calif.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Marra, Maurizio</au><au>Sammarco, Rosa</au><au>Cioffi, Iolanda</au><au>Morlino, Delia</au><au>Di Vincenzo, Olivia</au><au>Speranza, Enza</au><au>Pasanisi, Fabrizio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New predictive equations for estimating resting energy expenditure in subjects with normal weight and overweight</atitle><jtitle>Nutrition (Burbank, Los Angeles County, Calif.)</jtitle><addtitle>Nutrition</addtitle><date>2021-04</date><risdate>2021</risdate><volume>84</volume><spage>111105</spage><epage>111105</epage><pages>111105-111105</pages><artnum>111105</artnum><issn>0899-9007</issn><eissn>1873-1244</eissn><abstract>•Indirect calorimetry is considered the reference method for the measurement of resting energy expenditure (REE).•Predictive equations are commonly used as an alternative method for estimating REE.•New REE equations with bioimpedance analysis (BIA) variables for subjects with normal weight and overweight.•The equation with raw BIA variables showed the highest accuracy at individual level.
The aim of this study was to develop and validate new predictive equations for estimating resting energy expenditure (REE) in subjects with normal weight and overweight, considering anthropometric parameters as well as raw variables from bioimpedance analysis (BIA).
Adult participants with normal weight and overweight were recruited and randomly split into calibration and validation groups. Indirect calorimetry (IC) and BIA were performed in all subjects. New predictive equations were developed using the following models: model 1 with age, weight, stature, and body mass index (BMI) as predictors; and model 2: model 1 + raw BIA variables (bioimpedance index and phase angle). The accuracy of the new equations at both the group (bias) and individual (within ±10%) levels was tested in the validation group. Three published predictive equations were also compared, with the REE values measured by IC.
A total of 2483 adults were included for developing and validating the new equations. All selected formulas, including the new ones, showed a bias of <5% in estimating REE at the group level. Accuracy at the individual level was slightly higher for the new equations, especially for the equation based on raw BIA variables (men = 70.3%; women = 72.3%).
Compared to the equations in the literature, the new equations showed good accuracy at both the group and individual levels, with a slight improvement in individual accuracy for the formula including raw BIA variables. However, future research is required to verify the role of the raw BIA variables in predicting REE in subjects with normal weight and overweight.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>33477001</pmid><doi>10.1016/j.nut.2020.111105</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-1408-209X</orcidid><orcidid>https://orcid.org/0000-0002-3258-7374</orcidid><orcidid>https://orcid.org/0000-0002-3241-1897</orcidid><orcidid>https://orcid.org/0000-0003-4224-7821</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0899-9007 |
| ispartof | Nutrition (Burbank, Los Angeles County, Calif.), 2021-04, Vol.84, p.111105-111105, Article 111105 |
| issn | 0899-9007 1873-1244 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2480271408 |
| source | Elsevier |
| subjects | Accuracy Age Bias Bioimpedance analysis Body composition Body mass index Body size Body weight Calibration Calorimetry Carbon dioxide Clinical medicine Energy Energy expenditure Estimation Formulas (mathematics) Indirect calorimetry Mathematical models Men Normal weight Overweight Phase angle Predictive equations Resting energy expenditure Sexes Variables Womens health |
| title | New predictive equations for estimating resting energy expenditure in subjects with normal weight and overweight |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T14%3A15%3A50IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=New%20predictive%20equations%20for%20estimating%20resting%20energy%20expenditure%20in%20subjects%20with%20normal%20weight%20and%20overweight&rft.jtitle=Nutrition%20(Burbank,%20Los%20Angeles%20County,%20Calif.)&rft.au=Marra,%20Maurizio&rft.date=2021-04&rft.volume=84&rft.spage=111105&rft.epage=111105&rft.pages=111105-111105&rft.artnum=111105&rft.issn=0899-9007&rft.eissn=1873-1244&rft_id=info:doi/10.1016/j.nut.2020.111105&rft_dat=%3Cproquest_cross%3E2480271408%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c424t-ed364a8df5affbcc6d3d54951c974f8769f2384acb197cf257da628be4eedcd13%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2501478684&rft_id=info:pmid/33477001&rfr_iscdi=true |