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The Ten-Year Risk Prediction for Cardiovascular Disease for Malaysian Adults Using the Laboratory-Based and Office-Based (Globorisk) Prediction Model
Background and Objectives: Globorisk is a well-validated risk prediction model that predicts cardiovascular disease (CVD) in the national population of all countries. We aim to apply the Globorisk calculator and provide the overall, sex-specific, ethnic-specific, region-specific, and state-specific...
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Published in: | Medicina (Kaunas, Lithuania) Lithuania), 2022-05, Vol.58 (5), p.656 |
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description | Background and Objectives: Globorisk is a well-validated risk prediction model that predicts cardiovascular disease (CVD) in the national population of all countries. We aim to apply the Globorisk calculator and provide the overall, sex-specific, ethnic-specific, region-specific, and state-specific 10-year risk for CVD among Malaysian adults. Materials and Methods: Using Malaysia’s risk factor levels and CVD event rates, we calculated the laboratory-based and office-based risk scores to predict the 10-year risk for fatal CVD and fatal plus non-fatal CVD for the Malaysian adult population. We analysed data from 8253 participants from the 2015 nationwide Malaysian National Health and Morbidity Survey (NHMS 2015). The average risk for the 10-year fatal and fatal plus non-fatal CVD was calculated, and participants were further grouped into four categories: low risk ( |
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We aim to apply the Globorisk calculator and provide the overall, sex-specific, ethnic-specific, region-specific, and state-specific 10-year risk for CVD among Malaysian adults. Materials and Methods: Using Malaysia’s risk factor levels and CVD event rates, we calculated the laboratory-based and office-based risk scores to predict the 10-year risk for fatal CVD and fatal plus non-fatal CVD for the Malaysian adult population. We analysed data from 8253 participants from the 2015 nationwide Malaysian National Health and Morbidity Survey (NHMS 2015). The average risk for the 10-year fatal and fatal plus non-fatal CVD was calculated, and participants were further grouped into four categories: low risk (<10% risk for CVD), high risk A (≥10%), high risk B (≥20%), and high risk C (≥30%). Results: Results were reported for all participants and were then stratified by sex, ethnicity, region, and state. The average risks for laboratory-based fatal CVD, laboratory-based fatal plus non-fatal CVD, and office-based fatal plus non-fatal CVD were 0.07 (SD = 0.10), 0.14 (SD = 0.12), and 0.11 (SD = 0.09), respectively. Conclusions: There were substantial differences in terms of the sex-, ethnicity- and state-specific Globorisk risk scores obtained.</description><identifier>ISSN: 1648-9144</identifier><identifier>ISSN: 1010-660X</identifier><identifier>EISSN: 1648-9144</identifier><identifier>DOI: 10.3390/medicina58050656</identifier><identifier>PMID: 35630073</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Adult ; Age ; Asian People ; Blood pressure ; Blood tests ; Body mass index ; Cardiovascular disease ; Cardiovascular Diseases - epidemiology ; Cholesterol ; Datasets ; Diabetes ; Fatalities ; Female ; Globorisk ; Glucose ; Heart attacks ; Humans ; Laboratories ; Malaysia ; Male ; Population ; Public health ; Risk Factors ; Stroke ; ten-year risk prediction ; Womens health</subject><ispartof>Medicina (Kaunas, Lithuania), 2022-05, Vol.58 (5), p.656</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 by the authors. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c420t-e5260420035491f0ad5116b7f4297cde1e8b42335aae3d0eff20cbcc0af9a64e3</citedby><cites>FETCH-LOGICAL-c420t-e5260420035491f0ad5116b7f4297cde1e8b42335aae3d0eff20cbcc0af9a64e3</cites><orcidid>0000-0002-3708-0628</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2670332887/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2670332887?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35630073$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Che Nawi, Che Muhammad Nur Hidayat</creatorcontrib><creatorcontrib>Omar, Mohd Azahadi</creatorcontrib><creatorcontrib>Keegan, Thomas</creatorcontrib><creatorcontrib>Yu, Yong-Poh</creatorcontrib><creatorcontrib>Musa, Kamarul Imran</creatorcontrib><title>The Ten-Year Risk Prediction for Cardiovascular Disease for Malaysian Adults Using the Laboratory-Based and Office-Based (Globorisk) Prediction Model</title><title>Medicina (Kaunas, Lithuania)</title><addtitle>Medicina (Kaunas)</addtitle><description>Background and Objectives: Globorisk is a well-validated risk prediction model that predicts cardiovascular disease (CVD) in the national population of all countries. We aim to apply the Globorisk calculator and provide the overall, sex-specific, ethnic-specific, region-specific, and state-specific 10-year risk for CVD among Malaysian adults. Materials and Methods: Using Malaysia’s risk factor levels and CVD event rates, we calculated the laboratory-based and office-based risk scores to predict the 10-year risk for fatal CVD and fatal plus non-fatal CVD for the Malaysian adult population. We analysed data from 8253 participants from the 2015 nationwide Malaysian National Health and Morbidity Survey (NHMS 2015). The average risk for the 10-year fatal and fatal plus non-fatal CVD was calculated, and participants were further grouped into four categories: low risk (<10% risk for CVD), high risk A (≥10%), high risk B (≥20%), and high risk C (≥30%). Results: Results were reported for all participants and were then stratified by sex, ethnicity, region, and state. The average risks for laboratory-based fatal CVD, laboratory-based fatal plus non-fatal CVD, and office-based fatal plus non-fatal CVD were 0.07 (SD = 0.10), 0.14 (SD = 0.12), and 0.11 (SD = 0.09), respectively. Conclusions: There were substantial differences in terms of the sex-, ethnicity- and state-specific Globorisk risk scores obtained.</description><subject>Adult</subject><subject>Age</subject><subject>Asian People</subject><subject>Blood pressure</subject><subject>Blood tests</subject><subject>Body mass index</subject><subject>Cardiovascular disease</subject><subject>Cardiovascular Diseases - epidemiology</subject><subject>Cholesterol</subject><subject>Datasets</subject><subject>Diabetes</subject><subject>Fatalities</subject><subject>Female</subject><subject>Globorisk</subject><subject>Glucose</subject><subject>Heart attacks</subject><subject>Humans</subject><subject>Laboratories</subject><subject>Malaysia</subject><subject>Male</subject><subject>Population</subject><subject>Public health</subject><subject>Risk Factors</subject><subject>Stroke</subject><subject>ten-year risk prediction</subject><subject>Womens health</subject><issn>1648-9144</issn><issn>1010-660X</issn><issn>1648-9144</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkktv1DAQgCMEoqVw54QscSmHgB9x4lyQygKl0lZFaHvgZE3s8dZLGrd2Uml_CP8Xb3eptj15NP7m82OmKN4y-lGIln66RuuNH0AqKmkt62fFIasrVbasqp7vxQfFq5RWlAouG_6yOBCyFpQ24rD4u7hCssCh_I0QyS-f_pCfcWMdfRiIC5HMIFof7iCZqc_IV58QEt5vnUMP6-RhICd26sdELpMflmTMyjl0IcIY4rr8knFLYLDkwjlvcJc4Pu1DZvKJH_aPPA8W-9fFCwd9wje79ai4_P5tMftRzi9Oz2Yn89JUnI4lSl7THFEhq5Y5ClYyVneNq3jbGIsMVVdxISQACkvROU5NZwwF10JdoTgqzrZeG2Clb6K_hrjWAby-T4S41BBHb3rUoBpnsAWKCivRiM7atmONMB0qy2qZXZ-3rpupy30xOIwR-kfSxzuDv9LLcKdzg4RSPAuOd4IYbidMo772yWDfw4BhSprXDeOK01Zl9P0TdBWmOOSv2lBUCK5Ukym6pUwMKUV0D5dhVG_mRz-dn1zybv8RDwX_B0b8A0kbxPQ</recordid><startdate>20220512</startdate><enddate>20220512</enddate><creator>Che Nawi, Che Muhammad Nur Hidayat</creator><creator>Omar, Mohd Azahadi</creator><creator>Keegan, Thomas</creator><creator>Yu, Yong-Poh</creator><creator>Musa, Kamarul Imran</creator><general>MDPI AG</general><general>MDPI</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>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-3708-0628</orcidid></search><sort><creationdate>20220512</creationdate><title>The Ten-Year Risk Prediction for Cardiovascular Disease for Malaysian Adults Using the Laboratory-Based and Office-Based (Globorisk) Prediction Model</title><author>Che Nawi, Che Muhammad Nur Hidayat ; Omar, Mohd Azahadi ; Keegan, Thomas ; Yu, Yong-Poh ; Musa, Kamarul Imran</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c420t-e5260420035491f0ad5116b7f4297cde1e8b42335aae3d0eff20cbcc0af9a64e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adult</topic><topic>Age</topic><topic>Asian People</topic><topic>Blood pressure</topic><topic>Blood tests</topic><topic>Body mass index</topic><topic>Cardiovascular disease</topic><topic>Cardiovascular Diseases - epidemiology</topic><topic>Cholesterol</topic><topic>Datasets</topic><topic>Diabetes</topic><topic>Fatalities</topic><topic>Female</topic><topic>Globorisk</topic><topic>Glucose</topic><topic>Heart attacks</topic><topic>Humans</topic><topic>Laboratories</topic><topic>Malaysia</topic><topic>Male</topic><topic>Population</topic><topic>Public health</topic><topic>Risk Factors</topic><topic>Stroke</topic><topic>ten-year risk prediction</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Che Nawi, Che Muhammad Nur Hidayat</creatorcontrib><creatorcontrib>Omar, Mohd Azahadi</creatorcontrib><creatorcontrib>Keegan, Thomas</creatorcontrib><creatorcontrib>Yu, Yong-Poh</creatorcontrib><creatorcontrib>Musa, Kamarul Imran</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>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</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>ProQuest Central</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 Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</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>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Medicina (Kaunas, Lithuania)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Che Nawi, Che Muhammad Nur Hidayat</au><au>Omar, Mohd Azahadi</au><au>Keegan, Thomas</au><au>Yu, Yong-Poh</au><au>Musa, Kamarul Imran</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Ten-Year Risk Prediction for Cardiovascular Disease for Malaysian Adults Using the Laboratory-Based and Office-Based (Globorisk) Prediction Model</atitle><jtitle>Medicina (Kaunas, Lithuania)</jtitle><addtitle>Medicina (Kaunas)</addtitle><date>2022-05-12</date><risdate>2022</risdate><volume>58</volume><issue>5</issue><spage>656</spage><pages>656-</pages><issn>1648-9144</issn><issn>1010-660X</issn><eissn>1648-9144</eissn><abstract>Background and Objectives: Globorisk is a well-validated risk prediction model that predicts cardiovascular disease (CVD) in the national population of all countries. We aim to apply the Globorisk calculator and provide the overall, sex-specific, ethnic-specific, region-specific, and state-specific 10-year risk for CVD among Malaysian adults. Materials and Methods: Using Malaysia’s risk factor levels and CVD event rates, we calculated the laboratory-based and office-based risk scores to predict the 10-year risk for fatal CVD and fatal plus non-fatal CVD for the Malaysian adult population. We analysed data from 8253 participants from the 2015 nationwide Malaysian National Health and Morbidity Survey (NHMS 2015). The average risk for the 10-year fatal and fatal plus non-fatal CVD was calculated, and participants were further grouped into four categories: low risk (<10% risk for CVD), high risk A (≥10%), high risk B (≥20%), and high risk C (≥30%). Results: Results were reported for all participants and were then stratified by sex, ethnicity, region, and state. The average risks for laboratory-based fatal CVD, laboratory-based fatal plus non-fatal CVD, and office-based fatal plus non-fatal CVD were 0.07 (SD = 0.10), 0.14 (SD = 0.12), and 0.11 (SD = 0.09), respectively. Conclusions: There were substantial differences in terms of the sex-, ethnicity- and state-specific Globorisk risk scores obtained.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>35630073</pmid><doi>10.3390/medicina58050656</doi><orcidid>https://orcid.org/0000-0002-3708-0628</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Age Asian People Blood pressure Blood tests Body mass index Cardiovascular disease Cardiovascular Diseases - epidemiology Cholesterol Datasets Diabetes Fatalities Female Globorisk Glucose Heart attacks Humans Laboratories Malaysia Male Population Public health Risk Factors Stroke ten-year risk prediction Womens health |
title | The Ten-Year Risk Prediction for Cardiovascular Disease for Malaysian Adults Using the Laboratory-Based and Office-Based (Globorisk) Prediction Model |
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