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Ten-Year Cardiovascular Risk as Predicted by the QRISK®3 Calculator in Diabetic Patients Attending a Tertiary Care Teaching Hospital in Central India and Its Application to Stratify Statin Over-Users and Under-Users

Background: Cardiovascular disease (CVD) is an important cause of morbidity and mortality in diabetic patients. As such, risk stratification is essential to identify the risk factors of CVD and provide early intervention. The QRISK(®)3 tool, recommended by the National Institute for Health and Care...

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Detalles Bibliográficos
Autores principales: Chandrawanshi, Varnan, Gaikwad, Nitin R, Keche, Yogendra, Wasnik, Preetam, Dhaneria, Suryaprakash
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10653549/
https://www.ncbi.nlm.nih.gov/pubmed/38021672
http://dx.doi.org/10.7759/cureus.47213
Descripción
Sumario:Background: Cardiovascular disease (CVD) is an important cause of morbidity and mortality in diabetic patients. As such, risk stratification is essential to identify the risk factors of CVD and provide early intervention. The QRISK(®)3 tool, recommended by the National Institute for Health and Care Excellence (NICE) guidelines, has the option to choose the patient’s ethnicity, which is not available in other tools. However, there is a paucity of data regarding the use of this tool in the Indian population. Therefore, this study was planned to predict 10-year CVD risk using the QRISK(®)3 tool and to determine statin eligibility in diabetic patients. Methods: We enrolled diabetic patients visiting our general medicine outpatient department and diabetic clinic in the study. We collected data from clinical and prescription records, as well as through patient interviews. We analyzed the data to determine the 10-year CVD risk using the QRISK(®)3 risk tool, which is available online. A cut-off QRISK score of 10%, as recommended by the NICE guidelines (2014), was used to stratify patients as “over-users” and “under-users.” We also analyzed the data to determine any correlation between other risk factors and QRISK scores. Results: Of the 134 diabetic patients recruited in this study, 43 (32.09%) had a CVD risk score of <10%, of which 16 (37.21%) were categorized as “over-users.” Of the patients, 91 had a CVD risk score of ≥10%, of which 17 (18.68%) were categorized as “under-users.” Risk factors showing a positive correlation with QRISK score included duration of diabetes, age, blood pressure treatment, waist circumference, and non-high-density lipoprotein cholesterol level. Conclusion: QRISK score can be useful to predict 10-year CVD risk in the Indian population and to stratify patients as statin over-users and under-users. This tool can be used in the Indian set-up to identify potential candidates for statin initiation.