Handgrip strength measurement as a predictor of hospitalization costs
Background: Undernutrition status at hospital admission is related to increased hospital costs. Handgrip strength (HGS) is an indicator of undernutrition, but the ability of HGS to predict hospitalization costs has yet to be studied. Objective: To explore whether HGS measurement at hospital admissio...
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Veröffentlicht in: | European journal of clinical nutrition 2015-02, Vol.69 (2), p.187-192 |
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description | Background:
Undernutrition status at hospital admission is related to increased hospital costs. Handgrip strength (HGS) is an indicator of undernutrition, but the ability of HGS to predict hospitalization costs has yet to be studied.
Objective:
To explore whether HGS measurement at hospital admission can predict patient's hospitalization costs.
Subjects/Methods:
A prospective study was conducted in a university hospital. Inpatient's (
n
=637) HGS and undernutrition status by Patient-Generated Subjective Global Assessment were ascertained. Multivariable linear regression analysis, computing HGS quartiles by sex (reference: fourth quartile, highest), was conducted in order to identify the independent predictors of hospitalization costs. Costs were evaluated through percentage deviation from the mean cost, after adjustment for patients' characteristics, disease severity and undernutrition status.
Results:
Being in the first or second HGS quartiles at hospital admission increased patient's hospitalization costs, respectively, by 17.5% (95% confidence interval: 2.7–32.3) and 21.4% (7.5–35.3), which translated into an increase from €375 (58–692) to €458 (161–756). After the additional adjustment for undernutrition status, being in the first or second HGS quartiles had, respectively, an economic impact of 16.6% (1.9–31.2) and 20.0% (6.2–33.8), corresponding to an increase in hospitalization expenditure from €356 (41–668) to €428 (133–724).
Conclusions:
Low HGS at hospital admission is associated with increased hospitalization costs of between 16.6 and 20.0% after controlling for possible confounders, including undernutrition status. HGS is an inexpensive, noninvasive and easy-to-use method that has clinical potential to predict hospitalization costs. |
doi_str_mv | 10.1038/ejcn.2014.242 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_1652460338</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A400415473</galeid><sourcerecordid>A400415473</sourcerecordid><originalsourceid>FETCH-LOGICAL-c659t-5c6b8b0e5259ebea63be9c8dbef0bb77eff5687dadc0cabb386ba56ad1f8e5383</originalsourceid><addsrcrecordid>eNp9ks1v1DAQxS1ERbeFI1cUCQlxydaJv5JjVRWKVIlLe7ZsZ5L1KrGD7Rzgr8eB0hYUIR9Gsn_z_DTzEHpb4X2FSXMBR-P2Na7ovqb1C7SrqOAl4xS_RDvcMloSjMUpOovxiDMlRP0KndaM8LYheIeub5TrhmDnIqYAbkiHYgIVlwATuFSoWKhiDtBZk3wofF8cfJxtUqP9oZL1rjA-pvganfRqjPDmoZ6j-0_Xd1c35e3Xz1-uLm9Lw1mbSma4bjQGVrMWNChONLSm6TT0WGshoO8Zb0SnOoON0po0XCvGVVf1DTDSkHP08bfuHPy3BWKSk40GxlE58EuUFWc15Zj8Qt__gx79Elx2J2tCKl4LTNn_qKyFW0FFVnukBjWCtK73KSizfi0vKca0YlSsVLlBDeAgqNE76G2-_ovfb_D5dDBZs9nw4VnDAdSYDtGPy7qHuOnEBB9jgF7OwU4qfJcVlmtq5JoauaZG5tRk_t3DFBY9QfdI_4nJk9WYn9wA4dmYNhV_Ar_9yho</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1650974703</pqid></control><display><type>article</type><title>Handgrip strength measurement as a predictor of hospitalization costs</title><source>MEDLINE</source><source>Springer Online Journals</source><source>EZB Electronic Journals Library</source><creator>Guerra, R S ; Amaral, T F ; Sousa, A S ; Pichel, F ; Restivo, M T ; Ferreira, S ; Fonseca, I</creator><creatorcontrib>Guerra, R S ; Amaral, T F ; Sousa, A S ; Pichel, F ; Restivo, M T ; Ferreira, S ; Fonseca, I</creatorcontrib><description>Background:
Undernutrition status at hospital admission is related to increased hospital costs. Handgrip strength (HGS) is an indicator of undernutrition, but the ability of HGS to predict hospitalization costs has yet to be studied.
Objective:
To explore whether HGS measurement at hospital admission can predict patient's hospitalization costs.
Subjects/Methods:
A prospective study was conducted in a university hospital. Inpatient's (
n
=637) HGS and undernutrition status by Patient-Generated Subjective Global Assessment were ascertained. Multivariable linear regression analysis, computing HGS quartiles by sex (reference: fourth quartile, highest), was conducted in order to identify the independent predictors of hospitalization costs. Costs were evaluated through percentage deviation from the mean cost, after adjustment for patients' characteristics, disease severity and undernutrition status.
Results:
Being in the first or second HGS quartiles at hospital admission increased patient's hospitalization costs, respectively, by 17.5% (95% confidence interval: 2.7–32.3) and 21.4% (7.5–35.3), which translated into an increase from €375 (58–692) to €458 (161–756). After the additional adjustment for undernutrition status, being in the first or second HGS quartiles had, respectively, an economic impact of 16.6% (1.9–31.2) and 20.0% (6.2–33.8), corresponding to an increase in hospitalization expenditure from €356 (41–668) to €428 (133–724).
Conclusions:
Low HGS at hospital admission is associated with increased hospitalization costs of between 16.6 and 20.0% after controlling for possible confounders, including undernutrition status. HGS is an inexpensive, noninvasive and easy-to-use method that has clinical potential to predict hospitalization costs.</description><identifier>ISSN: 0954-3007</identifier><identifier>EISSN: 1476-5640</identifier><identifier>DOI: 10.1038/ejcn.2014.242</identifier><identifier>PMID: 25369830</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>692/700 ; 692/700/2814 ; Adult ; Aged ; Aged, 80 and over ; Clinical Nutrition ; Confidence intervals ; Costs ; Economic aspects ; Economic impact ; Economics ; Epidemiology ; Female ; Grip strength ; Hand Strength ; Hands ; Health care costs ; Hospital Costs ; Hospitalization ; Hospitalization - economics ; Humans ; Impact analysis ; Inpatients ; Internal Medicine ; Linear Models ; Male ; Malnutrition ; Malnutrition - diagnosis ; Malnutrition - economics ; Measurement ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; Middle Aged ; Muscular system ; Nutrition Assessment ; Nutritional Status ; original-article ; Patient admissions ; Patients ; Prospective Studies ; Public Health ; Quartiles ; Regression analysis ; Statistical analysis ; Undernutrition ; Young Adult</subject><ispartof>European journal of clinical nutrition, 2015-02, Vol.69 (2), p.187-192</ispartof><rights>Macmillan Publishers Limited 2015</rights><rights>COPYRIGHT 2015 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group Feb 2015</rights><rights>Macmillan Publishers Limited 2015.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c659t-5c6b8b0e5259ebea63be9c8dbef0bb77eff5687dadc0cabb386ba56ad1f8e5383</citedby><cites>FETCH-LOGICAL-c659t-5c6b8b0e5259ebea63be9c8dbef0bb77eff5687dadc0cabb386ba56ad1f8e5383</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/ejcn.2014.242$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/ejcn.2014.242$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,41486,42555,51317</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25369830$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Guerra, R S</creatorcontrib><creatorcontrib>Amaral, T F</creatorcontrib><creatorcontrib>Sousa, A S</creatorcontrib><creatorcontrib>Pichel, F</creatorcontrib><creatorcontrib>Restivo, M T</creatorcontrib><creatorcontrib>Ferreira, S</creatorcontrib><creatorcontrib>Fonseca, I</creatorcontrib><title>Handgrip strength measurement as a predictor of hospitalization costs</title><title>European journal of clinical nutrition</title><addtitle>Eur J Clin Nutr</addtitle><addtitle>Eur J Clin Nutr</addtitle><description>Background:
Undernutrition status at hospital admission is related to increased hospital costs. Handgrip strength (HGS) is an indicator of undernutrition, but the ability of HGS to predict hospitalization costs has yet to be studied.
Objective:
To explore whether HGS measurement at hospital admission can predict patient's hospitalization costs.
Subjects/Methods:
A prospective study was conducted in a university hospital. Inpatient's (
n
=637) HGS and undernutrition status by Patient-Generated Subjective Global Assessment were ascertained. Multivariable linear regression analysis, computing HGS quartiles by sex (reference: fourth quartile, highest), was conducted in order to identify the independent predictors of hospitalization costs. Costs were evaluated through percentage deviation from the mean cost, after adjustment for patients' characteristics, disease severity and undernutrition status.
Results:
Being in the first or second HGS quartiles at hospital admission increased patient's hospitalization costs, respectively, by 17.5% (95% confidence interval: 2.7–32.3) and 21.4% (7.5–35.3), which translated into an increase from €375 (58–692) to €458 (161–756). After the additional adjustment for undernutrition status, being in the first or second HGS quartiles had, respectively, an economic impact of 16.6% (1.9–31.2) and 20.0% (6.2–33.8), corresponding to an increase in hospitalization expenditure from €356 (41–668) to €428 (133–724).
Conclusions:
Low HGS at hospital admission is associated with increased hospitalization costs of between 16.6 and 20.0% after controlling for possible confounders, including undernutrition status. HGS is an inexpensive, noninvasive and easy-to-use method that has clinical potential to predict hospitalization costs.</description><subject>692/700</subject><subject>692/700/2814</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Clinical Nutrition</subject><subject>Confidence intervals</subject><subject>Costs</subject><subject>Economic aspects</subject><subject>Economic impact</subject><subject>Economics</subject><subject>Epidemiology</subject><subject>Female</subject><subject>Grip strength</subject><subject>Hand Strength</subject><subject>Hands</subject><subject>Health care costs</subject><subject>Hospital Costs</subject><subject>Hospitalization</subject><subject>Hospitalization - economics</subject><subject>Humans</subject><subject>Impact analysis</subject><subject>Inpatients</subject><subject>Internal Medicine</subject><subject>Linear Models</subject><subject>Male</subject><subject>Malnutrition</subject><subject>Malnutrition - diagnosis</subject><subject>Malnutrition - economics</subject><subject>Measurement</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolic Diseases</subject><subject>Middle Aged</subject><subject>Muscular system</subject><subject>Nutrition Assessment</subject><subject>Nutritional Status</subject><subject>original-article</subject><subject>Patient admissions</subject><subject>Patients</subject><subject>Prospective Studies</subject><subject>Public Health</subject><subject>Quartiles</subject><subject>Regression analysis</subject><subject>Statistical analysis</subject><subject>Undernutrition</subject><subject>Young Adult</subject><issn>0954-3007</issn><issn>1476-5640</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9ks1v1DAQxS1ERbeFI1cUCQlxydaJv5JjVRWKVIlLe7ZsZ5L1KrGD7Rzgr8eB0hYUIR9Gsn_z_DTzEHpb4X2FSXMBR-P2Na7ovqb1C7SrqOAl4xS_RDvcMloSjMUpOovxiDMlRP0KndaM8LYheIeub5TrhmDnIqYAbkiHYgIVlwATuFSoWKhiDtBZk3wofF8cfJxtUqP9oZL1rjA-pvganfRqjPDmoZ6j-0_Xd1c35e3Xz1-uLm9Lw1mbSma4bjQGVrMWNChONLSm6TT0WGshoO8Zb0SnOoON0po0XCvGVVf1DTDSkHP08bfuHPy3BWKSk40GxlE58EuUFWc15Zj8Qt__gx79Elx2J2tCKl4LTNn_qKyFW0FFVnukBjWCtK73KSizfi0vKca0YlSsVLlBDeAgqNE76G2-_ovfb_D5dDBZs9nw4VnDAdSYDtGPy7qHuOnEBB9jgF7OwU4qfJcVlmtq5JoauaZG5tRk_t3DFBY9QfdI_4nJk9WYn9wA4dmYNhV_Ar_9yho</recordid><startdate>20150201</startdate><enddate>20150201</enddate><creator>Guerra, R S</creator><creator>Amaral, T F</creator><creator>Sousa, A S</creator><creator>Pichel, F</creator><creator>Restivo, M T</creator><creator>Ferreira, S</creator><creator>Fonseca, I</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7RV</scope><scope>7TK</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</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>ATCPS</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>GUQSH</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</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></search><sort><creationdate>20150201</creationdate><title>Handgrip strength measurement as a predictor of hospitalization costs</title><author>Guerra, R S ; Amaral, T F ; Sousa, A S ; Pichel, F ; Restivo, M T ; Ferreira, S ; Fonseca, I</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c659t-5c6b8b0e5259ebea63be9c8dbef0bb77eff5687dadc0cabb386ba56ad1f8e5383</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>692/700</topic><topic>692/700/2814</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Clinical Nutrition</topic><topic>Confidence intervals</topic><topic>Costs</topic><topic>Economic aspects</topic><topic>Economic impact</topic><topic>Economics</topic><topic>Epidemiology</topic><topic>Female</topic><topic>Grip strength</topic><topic>Hand Strength</topic><topic>Hands</topic><topic>Health care costs</topic><topic>Hospital Costs</topic><topic>Hospitalization</topic><topic>Hospitalization - economics</topic><topic>Humans</topic><topic>Impact analysis</topic><topic>Inpatients</topic><topic>Internal Medicine</topic><topic>Linear Models</topic><topic>Male</topic><topic>Malnutrition</topic><topic>Malnutrition - diagnosis</topic><topic>Malnutrition - economics</topic><topic>Measurement</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolic Diseases</topic><topic>Middle Aged</topic><topic>Muscular system</topic><topic>Nutrition Assessment</topic><topic>Nutritional Status</topic><topic>original-article</topic><topic>Patient admissions</topic><topic>Patients</topic><topic>Prospective Studies</topic><topic>Public Health</topic><topic>Quartiles</topic><topic>Regression analysis</topic><topic>Statistical analysis</topic><topic>Undernutrition</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guerra, R S</creatorcontrib><creatorcontrib>Amaral, T F</creatorcontrib><creatorcontrib>Sousa, A S</creatorcontrib><creatorcontrib>Pichel, F</creatorcontrib><creatorcontrib>Restivo, M T</creatorcontrib><creatorcontrib>Ferreira, S</creatorcontrib><creatorcontrib>Fonseca, I</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest - Health & Medical Complete保健、医学与药学数据库</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>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>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</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>Research Library Prep</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>ProQuest 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>European journal of clinical nutrition</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guerra, R S</au><au>Amaral, T F</au><au>Sousa, A S</au><au>Pichel, F</au><au>Restivo, M T</au><au>Ferreira, S</au><au>Fonseca, I</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Handgrip strength measurement as a predictor of hospitalization costs</atitle><jtitle>European journal of clinical nutrition</jtitle><stitle>Eur J Clin Nutr</stitle><addtitle>Eur J Clin Nutr</addtitle><date>2015-02-01</date><risdate>2015</risdate><volume>69</volume><issue>2</issue><spage>187</spage><epage>192</epage><pages>187-192</pages><issn>0954-3007</issn><eissn>1476-5640</eissn><abstract>Background:
Undernutrition status at hospital admission is related to increased hospital costs. Handgrip strength (HGS) is an indicator of undernutrition, but the ability of HGS to predict hospitalization costs has yet to be studied.
Objective:
To explore whether HGS measurement at hospital admission can predict patient's hospitalization costs.
Subjects/Methods:
A prospective study was conducted in a university hospital. Inpatient's (
n
=637) HGS and undernutrition status by Patient-Generated Subjective Global Assessment were ascertained. Multivariable linear regression analysis, computing HGS quartiles by sex (reference: fourth quartile, highest), was conducted in order to identify the independent predictors of hospitalization costs. Costs were evaluated through percentage deviation from the mean cost, after adjustment for patients' characteristics, disease severity and undernutrition status.
Results:
Being in the first or second HGS quartiles at hospital admission increased patient's hospitalization costs, respectively, by 17.5% (95% confidence interval: 2.7–32.3) and 21.4% (7.5–35.3), which translated into an increase from €375 (58–692) to €458 (161–756). After the additional adjustment for undernutrition status, being in the first or second HGS quartiles had, respectively, an economic impact of 16.6% (1.9–31.2) and 20.0% (6.2–33.8), corresponding to an increase in hospitalization expenditure from €356 (41–668) to €428 (133–724).
Conclusions:
Low HGS at hospital admission is associated with increased hospitalization costs of between 16.6 and 20.0% after controlling for possible confounders, including undernutrition status. HGS is an inexpensive, noninvasive and easy-to-use method that has clinical potential to predict hospitalization costs.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>25369830</pmid><doi>10.1038/ejcn.2014.242</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; Springer Online Journals; EZB Electronic Journals Library |
subjects | 692/700 692/700/2814 Adult Aged Aged, 80 and over Clinical Nutrition Confidence intervals Costs Economic aspects Economic impact Economics Epidemiology Female Grip strength Hand Strength Hands Health care costs Hospital Costs Hospitalization Hospitalization - economics Humans Impact analysis Inpatients Internal Medicine Linear Models Male Malnutrition Malnutrition - diagnosis Malnutrition - economics Measurement Medicine Medicine & Public Health Metabolic Diseases Middle Aged Muscular system Nutrition Assessment Nutritional Status original-article Patient admissions Patients Prospective Studies Public Health Quartiles Regression analysis Statistical analysis Undernutrition Young Adult |
title | Handgrip strength measurement as a predictor of hospitalization costs |
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