Prioritising cardiovascular disease risk assessment to high risk individuals based on primary care records.
Prioritising cardiovascular disease risk assessment to high risk individuals based on primary care records.
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DOI：
10.1371/journal.pone.0292240
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发表时间：
2023
期刊：
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
--
作者：
提供定量证据，系统性地优先考虑个体进行全面正式的心血管疾病（CVD）风险评估，使用初级保健记录和一种具有年龄和性别特异性风险阈值的新型工具（eHEART）。eHEART是使用里程碑考克斯模型对来自临床实践研究数据链的1，642，498名个体的CVD事件进行的，并重复测量传统CVD风险预测因子。使用来自英国生物银行的119，137名个体，我们模拟了使用eHEART启动指南推荐的他汀类药物治疗的影响，年龄和性别特异性优先级阈值对应于5%的假阴性率，以优先考虑英格兰人群中40 - 69岁的成年人，邀请他们参加正式的CVD风险评估。对所有成年人进行正式的CVD风险评估将分别确定76%和49%的男性和女性未来CVD事件，93名（95% CI：90，95）男性和279名（95% CI：259，297）女性需要接受筛查（NNS）以预防一次CVD事件。相比之下，如果eHEART首先用于对个体进行正式的CVD风险评估，我们将分别确定男性和女性未来事件的73%和47%，男性和女性的NNS分别为75（95% CI：72，77）和162（95% CI：150，172）。将特定年龄和性别的优先级阈值替换为10%的阈值，可识别的事件减少约10%。使用具有年龄和性别特异性阈值的优先级工具可能会导致更有效的CVD评估计划，而预防新CVD事件的有效性仅略有降低。
To provide quantitative evidence for systematically prioritising individuals for full formal cardiovascular disease (CVD) risk assessment using primary care records with a novel tool (eHEART) with age- and sex- specific risk thresholds. eHEART was derived using landmark Cox models for incident CVD with repeated measures of conventional CVD risk predictors in 1,642,498 individuals from the Clinical Practice Research Datalink. Using 119,137 individuals from UK Biobank, we modelled the implications of initiating guideline-recommended statin therapy using eHEART with age- and sex-specific prioritisation thresholds corresponding to 5% false negative rates to prioritise adults aged 40–69 years in a population in England for invitation to a formal CVD risk assessment. Formal CVD risk assessment on all adults would identify 76% and 49% of future CVD events amongst men and women respectively, and 93 (95% CI: 90, 95) men and 279 (95% CI: 259, 297) women would need to be screened (NNS) to prevent one CVD event. In contrast, if eHEART was first used to prioritise individuals for formal CVD risk assessment, we would identify 73% and 47% of future events amongst men and women respectively, and a NNS of 75 (95% CI: 72, 77) men and 162 (95% CI: 150, 172) women. Replacing the age- and sex-specific prioritisation thresholds with a 10% threshold identify around 10% less events. The use of prioritisation tools with age- and sex-specific thresholds could lead to more efficient CVD assessment programmes with only small reductions in effectiveness at preventing new CVD events.
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影响因子：
105.7
作者：
Chamnan, Parinya;Simmons, Rebecca K.;Griffin, Simon J.
通讯作者：
Griffin, Simon J.
影响因子：
105.7
作者：
Hippisley-Cox, Julia;Coupland, Carol;Brindle, Peter
通讯作者：
Brindle, Peter
DOI：
10.1056/nejmoa1107477
发表时间：
2012-10-04
期刊：
The New England journal of medicine
影响因子：
--
作者：
Emerging Risk Factors Collaboration;Kaptoge S;Di Angelantonio E;Pennells L;Wood AM;White IR;Gao P;Walker M;Thompson A;Sarwar N;Caslake M;Butterworth AS;Amouyel P;Assmann G;Bakker SJ;Barr EL;Barrett-Connor E;Benjamin EJ;Björkelund C;Brenner H;Brunner E;Clarke R;Cooper JA;Cremer P;Cushman M;Dagenais GR;D'Agostino RB Sr;Dankner R;Davey-Smith G;Deeg D;Dekker JM;Engström G;Folsom AR;Fowkes FG;Gallacher J;Gaziano JM;Giampaoli S;Gillum RF;Hofman A;Howard BV;Ingelsson E;Iso H;Jørgensen T;Kiechl S;Kitamura A;Kiyohara Y;Koenig W;Kromhout D;Kuller LH;Lawlor DA;Meade TW;Nissinen A;Nordestgaard BG;Onat A;Panagiotakos DB;Psaty BM;Rodriguez B;Rosengren A;Salomaa V;Kauhanen J;Salonen JT;Shaffer JA;Shea S;Ford I;Stehouwer CD;Strandberg TE;Tipping RW;Tosetto A;Wassertheil-Smoller S;Wennberg P;Westendorp RG;Whincup PH;Wilhelmsen L;Woodward M;Lowe GD;Wareham NJ;Khaw KT;Sattar N;Packard CJ;Gudnason V;Ridker PM;Pepys MB;Thompson SG;Danesh J
通讯作者：
Danesh J
影响因子：
37.8
作者：
Lloyd-Jones, Donald M.
通讯作者：
Lloyd-Jones, Donald M.
影响因子：
1.9
作者：
LAIRD, NM;WARE, JH
通讯作者：
WARE, JH