Determining cardiovascular risk in patients with unattributed chest pain in UK primary care: an electronic health record study

被引:3
作者
Jordan, Kelvin P. [1 ]
Rathod-Mistry, Trishna [1 ,2 ]
van der Windt, Danielle A. [1 ]
Bailey, James [1 ]
Chen, Ying [1 ,3 ]
Clarson, Lorna [1 ]
Denaxas, Spiros [4 ,5 ]
Hayward, Richard A. [1 ]
Hemingway, Harry [4 ,6 ]
Kyriacou, Theocharis [7 ]
Mamas, Mamas A. [8 ]
机构
[1] Keele Univ, Sch Med, David Weatherall Bldg, Univ Rd, Keele ST5 5BG, Staffs, England
[2] Univ Oxford, Ctr Stat Med, Nuffield Dept Orthopaed Rheumatol & Musculoskelet, Windmill Rd, Oxford OX3 7LD, England
[3] Xian Jiaotong Liverpool Univ, Wisdom Lake Acad Pharm, Suzhou 215123, Jiangsu, Peoples R China
[4] UCL, Inst Hlth Informat, 222 Euston Rd, London NW1 2DA, England
[5] UCL, Hlth Data Res UK, 222 Euston Rd, London NW1 2DA, England
[6] Univ Coll London Hosp, Biomed Res Ctr, Natl Inst Hlth Res, Maple House 1st floor, 149 Tottenham Court Rd, London W1T 7DN, England
[7] Keele Univ, Sch Comp & Math, Keele ST5 5AA, Staffs, England
[8] Keele Univ, Sch Med, Keele Cardiovasc Res Grp, David Weatherall Bldg, Univ Rd, Keele ST5 5BG, Staffs, England
关键词
Chest pain; Cardiovascular disease; Primary health care; Risk; Electronic health records; Epidemiology; CORONARY-HEART-DISEASE; VALIDATION;
D O I
10.1093/eurjpc/zwad055
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Aims Most adults presenting in primary care with chest pain symptoms will not receive a diagnosis ('unattributed' chest pain) but are at increased risk of cardiovascular events. To assess within patients with unattributed chest pain, risk factors for cardiovascular events and whether those at greatest risk of cardiovascular disease can be ascertained by an existing general population risk prediction model or by development of a new model. Methods and results The study used UK primary care electronic health records from the Clinical Practice Research Datalink linked to admitted hospitalizations. Study population was patients aged 18 plus with recorded unattributed chest pain 2002-2018. Cardiovascular risk prediction models were developed with external validation and comparison of performance to QRISK3, a general population risk prediction model. There were 374 917 patients with unattributed chest pain in the development data set. The strongest risk factors for cardiovascular disease included diabetes, atrial fibrillation, and hypertension. Risk was increased in males, patients of Asian ethnicity, those in more deprived areas, obese patients, and smokers. The final developed model had good predictive performance (external validation c-statistic 0.81, calibration slope 1.02). A model using a subset of key risk factors for cardiovascular disease gave nearly identical performance. QRISK3 underestimated cardiovascular risk. Conclusion Patients presenting with unattributed chest pain are at increased risk of cardiovascular events. It is feasible to accurately estimate individual risk using routinely recorded information in the primary care record, focusing on a small number of risk factors. Patients at highest risk could be targeted for preventative measures. Lay Summary It is known that patients with chest pain without a recognized cause are at increased risk of future cardiovascular events (for example, heart disease) and so this study aimed to find out whether those patients at greatest risk could be determined using information in their health records.It is possible to accurately estimate a person's risk of future cardiovascular events using the information entered into their health records, and this risk can be estimated using only a small number of factors.Patients at highest risk could now be targeted for management to help prevent future cardiovascular events.
引用
收藏
页码:1151 / 1161
页数:11
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