{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T17:11:11Z","timestamp":1788887471765,"version":"build-2803163510"},"reference-count":16,"publisher":"Ovid Technologies (Wolters Kluwer Health)","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"abstract":"\n Background:<\/jats:title>\n We aimed to compare performance of three cardiovascular disease (CVD) risk estimation tools; the World Health Organization\/International Society of Hypertension (WHO\/ISH) risk prediction tool, the American College of Cardiology\/American Heart Association Atherosclerotic Cardiovascular Disease (ACC\/AHA ASCVD) Risk Estimator, and Framingham risk score (FRS) in estimating the risk of fatal and nonfatal cardiovascular events.<\/jats:p>\n <\/jats:sec>\n \n Methods:<\/jats:title>\n We conducted a prospective, observational, hospital-based study involving 200 high-risk study participants, who visited a non-communicable disease clinic in a tertiary care hospital in eastern India. The 10-year CVD risk was estimated using the ACC\/AHA ASCVD Risk Estimator, FRS, and the WHO\/ISH risk prediction tool. We used kappa statistics to determine agreement among these CVD risk estimators.<\/jats:p>\n <\/jats:sec>\n \n Results:<\/jats:title>\n \n The mean (SD) age of study participants was 54.07 (9.15) years, and the majority (63.5%) were males. About 96% of the participants were diabetic, 33.5% were hypertensive, and 16% were current smokers. About 18%, 20.5%, and 0.5% were classified as high-risk using the ACC\/AHA ASCVD Risk Estimator, FRS, and WHO\/ISH risk tools, respectively. The agreement was moderate between the ASCVD risk estimator and FRS (Kappa 0.541,\n P<\/jats:italic>\n < 0.001) and fair between the ASCVD risk Estimator and WHO\/ISH (Kappa 0.305,\n P<\/jats:italic>\n < 0.001) and between FRS and WHO\/ISH (Kappa 0.314,\n P<\/jats:italic>\n < 0.001).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions:<\/jats:title>\n A higher level of agreement was found between FRS and ASCVD risk scores compared to the WHO-ISH risk score. The WHO-ISH risk score identified most study participants in the lower-risk category, contrary to the FRS and ASCVD risk scores.<\/jats:p>\n <\/jats:sec>","DOI":"10.4103\/ijpvm.ijpvm_400_25","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T09:00:29Z","timestamp":1788253229000},"update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["Performance of Cardiovascular Disease (CVD) Risk Assessment Tools in Clinical Practice - Agreement Between Different CVD Risk Scores Among Patients Attending NCD Clinic in a Tertiary Care Setting: A Prospective Observational Study"],"prefix":"10.4103","volume":"17","author":[{"given":"Debkumar","family":"Pal","sequence":"first","affiliation":[{"name":"Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Snehapriya","family":"Suresh","sequence":"additional","affiliation":[{"name":"Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A.","family":"Priyadharshini","sequence":"additional","affiliation":[{"name":"Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kajal","family":"Das","sequence":"additional","affiliation":[{"name":"Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priyamadhaba","family":"Behera","sequence":"additional","affiliation":[{"name":"Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manish","family":"Taywade","sequence":"additional","affiliation":[{"name":"Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Binod Kumar","family":"Patro","sequence":"additional","affiliation":[{"name":"Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,8]]},"reference":[{"key":"R3-20260908","doi-asserted-by":"crossref","first-page":"23248","DOI":"10.3402\/gha.v7.23248","article-title":"Understanding epidemiological transition in India","volume":"7","author":"Yadav","year":"2014","journal-title":"Glob Health 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