心房颤动患者预后评分系统的构建和比较

黄佳琦; 钟理; 张志辉; 邬娜; 吴龙; 向颖; 李成英; 李亚斐

doi:10.16462/j.cnki.zhjbkz.2020.04.020

心房颤动患者预后评分系统的构建和比较

doi: 10.16462/j.cnki.zhjbkz.2020.04.020

黄佳琦¹,
钟理²,
张志辉³,
邬娜¹,
吴龙¹,
向颖¹,
李成英¹,
李亚斐^1, ,

1.
400038 重庆, 陆军军医大学军事预防医学系军队流行病学教研室
2.
401120 重庆, 重庆医科大学附属第三医院心血管疾病中心
3.
400038 重庆, 陆军军医大学西南医院心内科

基金项目: 国家自然科学基金青年科学基金项目(81502883)

详细信息

通讯作者:
李亚斐, E-mail:liyafei2008@hotmail.com

中图分类号: R181.23;R541.7+5
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出版历程
- 收稿日期: 2019-09-14
- 修回日期: 2020-01-09
- 刊出日期: 2020-04-10

Construction and comparative analysis of prognostic scoring system in patients with atrial fibrillation

1.
Department of Epidemiology, College of Preventive Medicine, Army Medical University, Chongqing 400038, China
2.
Cardiovascular Disease Center, Third Affiliated Hospital of Chongqing Medical University, Chongqing 401120, China
3.
Department of Cardiology, Southwest Hospital, Army Medical University, Chongqing 400038, China

Funds: Project of Youth Science Foundation of National Natural Science Foundation of China(81502883)

More Information

Corresponding author: LI Ya-fei, E-mail:liyafei2008@hotmail.com

摘要

摘要: 目的构建心房颤动人群预后预测工具, 并对其预测能力进行比较评估。方法连续性纳入275例新发心房颤动患者, 随访终点包括卒中和全因死亡。收集相关基线资料, 检测患者基线血浆N末端B型利钠肽原(N-terminal pro B-type natriuretic peptide, NT-proBNP)、高敏肌钙蛋白T(high-sensitivity cardiac troponin T, hs-cTnT)、生长分化因子15(growth differentiation factor-15, GDF-15)浓度。运用Cox比例风险模型构建卒中和死亡风险评分系统。应用C-统计量和校准图比较评分系统的预测能力。结果多因素Cox回归显示, 糖尿病、短暂性脑缺血发作(transient ischemic attack, TIA)、卒中史、血浆NT-proBNP浓度与心房颤动患者卒中风险独立相关; 年龄、心衰史、血浆hs-cTnT和GDF-15浓度与心房颤动患者全因死亡风险独立相关。我们构建的卒中风险评分系统预测能力与国外年龄、生物标志物和临床病史(age, biomarker, clinical history, ABC)卒中评分以及CHA2DS2-VASc评分相当, 死亡风险评分系统与国外ABC死亡评分相当, 优于CHA2DS2-VASc评分。结论本研究构建的心房颤动患者卒中和死亡风险预测评分系统表现出较好的预测性能, 此评分系统的列线图可望作为临床决策的辅助工具。
- 房颤 /
- ABC评分 /
- 预后 /
- 风险评估 /
- 列线图
Abstract: Objective To construct a score system for predicting the prognosis of atrial fibrillation(AF) in China, and to compare its predictive ability. Methods A total of 275 patients with new-onset AF were continuously enrolled in the study. The outcome events of follow-up included stroke and all-cause mortality. Prognostic-related epidemiological and clinical information were collected. The blood concentration of N-terminal B-type natriuretic peptide(NT-proBNP), high-sensitivity troponin T(hs-cTnT) and growth differentiation factor(GDF)-15 were detected. A Cox proportional hazards regression model was used to develop novel risk scoring system. C-statistics and calibration plots were used to estimate and compare the predictive ability of risk scores. Results Multivariate Cox regression analysis showed that history of diabetes, history of transient ischemic attack, history of stroke and plasma level of NT-proBNP were independently associated with the risk of stroke. Age, history of heart failure, plasma level of hs-cTnT and GDF-15 were independent risk factors of all-cause mortality. The C-statistic of the stroke-risk score was similar to that of the CHA2 DS2-VASc score and ABC(age, biomarker, clinical history)-stroke score; the C-statistic of the death-risk score was similar to that of ABC-death score and significantly higher than that of the CHA2 DS2-VASc score. Conclusions The stroke and death risk scoring system of atrial fibrillation patients constructed in this study showed a good predictive performance. The nomograms of these scoring systems are expected to be auxiliary tools for clinical decision-making.
- Atrial fibrillation /
- ABC scores /
- Prognosis /
- Risk stratification /
- Nomogram

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图 1 各评分系统校准图、本研究构建风险评分系统组间累积事件发生率及列线图

注:(A和B)卒中和死亡风险各评分系统间一致性比较，越接近斜率为1的虚线表示其一致性越高; (C和D)本研究构建的评分系统亚组的终点事件累积卒中风险; (E和F)本研究构建房颤患者卒中和死亡风险预测列线图。列线图中针对每个预后参数，读取顶部0~10标度上分配的“评分值”，相加得到评分总值。找出“评分总值”轴上的数字，查询相应的1年和3年风险事件发生率; 预后参数(糖尿病史、TIA、卒中史、心衰史)坐标轴0表示无该疾病病史，1表示有该疾病病史; ln_NT_pro BNP:NT-pro BNP(pg/ml)的自然对数值; ln_hs_c Tn T:hs-c Tn T(ng/L)的自然对数值; ln_GDF_15:GDF-15(pg/ml)的自然对数值。

Figure 1. Calibration plots, cumulative event rates for endpoints according to the risk categories and nomogram of the scoring systems constructed in this study

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表 1 房颤人群基线资料

Table 1. Baseline characteristics of atrial fibrillation patients

变量	总体(N=275)
随访时间(月)	27(24, 31)
死亡人数	28(4.60/100人年)
卒中人数	25(4.33/100人年)
年龄(岁)	67(59, 74)
女性	127(46.18%)
BMI(kg/m²)	23.9(22, 26.4)
文化程度
初中及以下	224(81.45%)
高中及以上	51(18.55%)
人均收入(万元/年)
< 2.5	136(49.45%)
≥2.5	139(50.55%)
房颤类型
阵发性	91(33.09%)
慢性	184(66.91%)
吸烟	43(15.64%)
饮酒	57(20.73%)
合并疾病史
高血压	146(53.09%)
糖尿病	58(21.09%)
血脂异常	27(9.81%)
冠心病	115(41.82%)
心肌病	32(11.64%)
心衰	91(33.09%)
TIA	10(3.64%)
血管性疾病	18(6.55%)
卒中史	31(11.27%)
药物使用
抗心律失常药物	138(50.18%)
ACEI	96(34.91%)
ARB	28(10.18%)
β受体阻滞剂	113(41.09%)
华法林	88(32.00%)
他汀药	134(48.73%)
风险评分
CHA2DS2-VASc	3(1, 4)
国外ABC死亡评分	1.69(0.86, 3.63)
国外ABC卒中评分	1.14(0.82, 1.70)
生物标志物
NT-proBNP (pg/ml)	1 079.00(465.40, 1 994.00)
hs-cTnT (ng/L)	10.00(7.00, 18.00)
GDF-15 (pg/ml)	1 017.60(743.99, 1 460.14)
注:定量资料采用中位数(四分位数间距)表示; 体重指数(body mass index, BMI); 血管紧张素转化酶抑制剂(angiotensin-converting enzyme inhibitor, ACEI); 血管紧张素Ⅱ受体阻滞剂(angiotensin receptor blocker, ARB)。

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表 2 基线资料和生物标志物与房颤患者终点事件关联的Cox回归分析

Table 2. Cox regression analysis of correlation between baseline characteristics and biomarkers with endpoints in patients with AF

变量	单因素分析		多因素分析
变量	HR(95% CI)值	P值	HR(95% CI)值	P值
卒中
年龄(岁)	1.05(1.00~1.10)	0.032	1.03(0.98~1.07)	0.256
糖尿病	3.12(1.41~6.85)	0.005	2.39(1.07~5.35)	0.034
TIA	4.11(1.22~13.87)	0.023	3.85(1.11~13.29)	0.033
卒中史	2.90(1.14~7.35)	0.025	3.13(1.19~8.20)	0.020
CHA2DS2-VASc	1.47(1.16~1.85)	0.001	0.95(0.62~1.46)	0.811
生物标志物
ln_NT-proBNP	1.39(0.99~1.96)	0.055	1.49(1.01~2.18)	0.044
ln_hs-cTnT	1.16(0.89~1.50)	0.279	1.03(0.73~1.45)	0.883
ln_GDF-15	2.07(1.00~4.28)	0.050	1.34(0.56~3.22)	0.513
全因死亡
年龄(岁)	1.10(1.05~1.15)	< 0.001	3.35(1.39~8.08)	0.041
房颤类型
阵发性	1.00		1.00
慢性	2.36(0.90~6.20)	0.082	1.65(0.62~4.37)	0.320
心衰史	6.59(2.80~15.50)	< 0.001	3.47(1.43~8.43)	0.006
CHA2DS2-VASc	1.40(1.12~1.74)	0.002	0.92(0.62~1.37)	0.686
生物标志物
ln_NT-proBNP	2.42(1.69~3.45)	< 0.001	1.28(0.79~2.06)	0.315
ln_hs-cTnT	1.58(1.34~1.87)	< 0.001	1.45(1.17~1.80)	0.001
ln_GDF-15	5.22(2.78~9.79)	< 0.001	2.77(1.38~5.58)	0.004
注:把单因素Cox回归中P < 0.10的变量纳入多因素Cox回归分析。

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表 3 各评分的C-统计量比较

Table 3. C-statistic of the scoring systems in comparison with the CHA2DS2-VASc score and ABC risk scores

变量	C-统计量(95% CI)值	Z值	P值	C-统计量变化量(95% CI)值	Z值	P值
卒中
CHA₂DS₂-VASc	0.72(0.64~0.80)	5.56	< 0.001	-0.04(-0.05~0.11)^a	0.57	0.567^a
国外ABC卒中评分	0.75(0.66~0.83)	5.72	< 0.001	-0.02 (-0.04~0.08)^b	-0.70	0.485^b
卒中风险评分系统	0.77(0.69~0.85)	6.76	< 0.001	0.05 (-0.03~0.11)^c	-1.36	0.174^c
全因死亡
CHA₂DS₂-VASc	0.68(0.61~0.76)	4.56	< 0.001	-0.15 (0.04~0.25)^a	2.89	0.004^a
国外ABC死亡评分	0.83(0.75~0.91)	8.43	< 0.001	-0.04 (-0.02~0.09)^d	-1.45	0.146^d
死亡风险评分系统	0.87(0.81~0.92)	13.42	< 0.001	0.18 (0.10~0.26)^e	4.37	< 0.001^e
注:^a:CHA₂DS₂-VASc评分与国外ABC卒中或死亡评分比较, ^b:国外ABC卒中评分与卒中风险评分系统比较, ^c:卒中风险评分系统与CHA₂DS₂-VASc评分比较; ^d:国外ABC死亡评分与死亡风险评分系统比较, ^e:死亡风险评分系统与CHA₂DS₂-VASc评分比较。

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