BMC Med:QRISK3 or CRISK?两种心血管风险预测工具谁优谁劣

2022-05-15 医路坦克 MedSci原创 发表于加利福尼亚

心血管疾病(CVD)是全球主要的死亡原因,估计每年造成1,790万人死亡,这项研究的目的是推导和验证竞争风险模型(Crisk)来预测心血管事件,并将其与QRISK3进行比较。

血管疾病(CVD)是全球主要的死亡原因,估计每年造成1,790万人死亡,并且是50岁以上人群残疾调整寿命的头号原因。风险预测工具是指南推荐的,目的是针对他汀类药物的启动,为超过指定预测风险阈值的人提供心血管疾病的一级预防。随着时间的推移,风险阈值也有所下降,越来越多的证据表明他汀类药物对心血管疾病一级预防有效。

这项研究的目的是推导和验证竞争风险模型(Crisk)来预测心血管事件,并将其与QRISK3进行比较。

我们使用临床实践研究数据链(CPRD)GOLD中与英国相关的初级保健数据来识别年龄在25-84岁之间、以前没有接受过心血管疾病或他汀类药物治疗的人群,我们使用与QRISK3相同的协变量,单独使用Fine-Gray竞争风险模型(CRISK)和Charlson共病评分(CRISK-CCI)作为非心血管死亡的额外预测因子。在一个单独的验证队列中,我们检查了与QRISK3相比的区分和校准。重新分类分析检查了推荐治疗的患者数量和为防止新的心血管事件而需要治疗(NNT)的估计数量。

实验队列包括989,732名和494,865名女性和946,784名和473,392名男性。CRISK和CRISK-CCI的总体辨别力都很好,与QRISK3相似(女性的C-统计量分别为0.863/0.864/0.863;男性的分别为0.833/0.819/0.832)。CRISK和CRISK-CCI校准总体上和在年轻人中都是非常好的。尽管比QRISK3表现得更好,但CRISK-CCI在老年人和多病患者中预测过高,而CRISK-CCI表现最好。CRISK-CCI重新分类的人群比例因QRISK3风险评分类别而异,0.7-9.7%的女性和2.8-25.2%的男性重新分类为高风险,21.0-69.1%的女性和27.1-57.4%的男性重新分类为低风险。总体而言,CRISK-CCI推荐的治疗人数较少,估计NNT的风险阈值较低,为10%。被重新归类为高风险的患者更年轻,SBP更低,BMI更高,更有可能吸烟。

CRISK和CRISK-CCI的表现好于QRISK3。CRISK-CCI建议接受治疗的人数更少,与QRISK3相比,预防新的CVD事件的NNT更低。对于心血管疾病的初级预防和治疗建议,应推荐CRISK模型。

QRISK3:10年心血管风险预测模型(QRISK3-2018)

文献来源:Livingstone SJ,  Guthrie B,  Donnan PT,  Predictive performance of a competing risk cardiovascular prediction tool CRISK compared to QRISK3 in older people and those with comorbidity: population cohort study.BMC Med 2022 May 04;20(1)

 

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    2023-09-26 1dea4a7em68(暂无匿称)

    谢谢分享

    0

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    2022-05-16 ms6000001791212108

    学习了

    0

  5. [GetPortalCommentsPageByObjectIdResponse(id=2159799, encodeId=e9442159e9977, content=谢谢分享, beContent=null, objectType=article, channel=null, level=null, likeNumber=23, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://cdnapi.center.medsci.cn/medsci/head/2018/02/23/914ab8c212b86139546fc16eed98b36f.jpg, createdBy=90821711402, createdName=1dea4a7em68(暂无匿称), createdTime=Tue Sep 26 13:00:55 CST 2023, time=2023-09-26, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=2082594, encodeId=b6c4208259418, content=<a href='/topic/show?id=56658981223' target=_blank style='color:#2F92EE;'>#血管风险#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=36, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=89812, encryptionId=56658981223, topicName=血管风险)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=a12645, createdName=智智灵药, createdTime=Sat Jun 25 21:20:25 CST 2022, time=2022-06-25, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1975196, encodeId=084e19e519636, content=<a href='/topic/show?id=f145355379' target=_blank style='color:#2F92EE;'>#BMC#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=39, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=3553, encryptionId=f145355379, topicName=BMC)], attachment=null, authenticateStatus=null, createdAvatar=https://thirdqq.qlogo.cn/qqapp/101173734/363C99735735B7F4CB11D5F78F580525/100, createdBy=aab22500211, createdName=ms3025846204744509, createdTime=Wed Jun 29 00:20:25 CST 2022, time=2022-06-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1219977, encodeId=64de12199e7cd, content=学习了, beContent=null, objectType=article, channel=null, level=null, likeNumber=43, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=e3e76499938, createdName=ms6000001791212108, createdTime=Mon May 16 11:46:24 CST 2022, time=2022-05-16, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1219894, encodeId=ec4e121989465, content=学习一下, beContent=null, objectType=article, channel=null, level=null, likeNumber=43, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=b7a31928393, createdName=学医无涯, createdTime=Mon May 16 06:09:29 CST 2022, time=2022-05-16, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1486008, encodeId=1b9f148600829, content=<a href='/topic/show?id=2c62100911a3' target=_blank style='color:#2F92EE;'>#风险预测#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=46, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=100911, encryptionId=2c62100911a3, topicName=风险预测)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=e31a8064712, createdName=12498ebem21暂无昵称, createdTime=Sat May 14 14:20:25 CST 2022, time=2022-05-14, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1611593, encodeId=24371611593ea, content=<a href='/topic/show?id=eb6b1145939' target=_blank style='color:#2F92EE;'>#Med#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=23, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=11459, encryptionId=eb6b1145939, topicName=Med)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=552a19396740, createdName=ms3994565386320060, createdTime=Sat May 14 14:20:25 CST 2022, time=2022-05-14, status=1, ipAttribution=)]
    2022-05-16 学医无涯

    学习一下

    0

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