稳定型冠心病患者心脏康复的风险分层模型

doi:10.3969/j.issn.1006-9771.2021.07.014

Abstract

Abstract:

Objective To create a prediction model that could be used to stratify the risk of cardiac rehabilitation in patients with stable coronary artery disease by using test data based on cardiopulmonary exercise testing (CPET) and general clinical data.

Methods A total of 114 patients with stable coronary artery disease were consecutively enrolled from the Cardiology Coronary Artery Disease Database of our hospital from December, 2014 to December, 2018, all the patients underwent CPET before coronary angiography. LASSO was used for feature selection. A nomogram was formulated based on the results of multivariate Logistic regression analysis using the RMS package of R. The predictive power was assessed with Receiver Operating Characteristic Curve.

Results Seven predictors were identified based on LASSO: coronary angiography results, the maximum value of ventilatory equivalent for carbon dioxide (EqCO₂max), lymphocyte count, fasting blood glucose levels, cardiac muscle enzyme positivity, blood homocysteine and blood urea nitrogen levels. Combined with clinical experience and weighting analysis, the final four factors were included for Logistic regression modeling: coronary angiography results, EqCO₂max, lymphocyte count and fasting blood glucose levels. The area under the curve was 0.875 for the model.

Conclusion EqCO₂max and lymphocyte count are key predictors for stable coronary heart disease and can be used to identify patients at high risk for cardiac rehabilitation. A risk stratification model based on CPET and laboratory tests can be used to assess risk stratification for cardiac rehabilitation in patients with stable coronary artery disease.

Key words: coronary artery disease, Cardiopulmonary Exercise Test, cardiac rehabilitation

CLC Number:

R541.4

ZHENG Zhi-chang,YUAN Wei,LIN Wei,LIU Jie,WANG Xiao-rong,YANG Wei,YU Hai-tao,XUE Song,WANG Ya-min,TANG Li,WANG Guo-dong. A Risk Prediction Model for Cardiac Rehabilitation in Patients with Stable Coronary Artery Disease[J]. 《Chinese Journal of Rehabilitation Theory and Practice》, 2021, 27(7): 819-828.

Figures/Tables 9

References 35

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项目	风险分层		t/χ²值	P值
项目	低危组(n = 100)	高危组(n = 14)	t/χ²值	P值
年龄(岁)	59.490±7.543	60.210±8.210	-0.333	0.740
性别(n)			5.363	0.021
男	53	12
女	47	2
体质量指数(kg/m²)	26.288±3.384	25.179±1.882	1.197	0.234
高血压病史(n)	65	12	2.404	0.121
糖尿病史(n)	35	4	0.225	0.635
高血脂病史(n)	66	11	0.885	0.347
卒中病史(n)	4	1	0.289	0.591
吸烟(n)			6.805	0.078
不吸烟	58	5
吸烟、已戒	17	1
吸烟、未戒	25	8
饮酒(n)			6.325	0.097
不饮酒	64	6
饮酒、已戒	10	0
饮酒、未戒	26	8

实验室检查	风险分层		t/Z/χ²值	P值
实验室检查	低危组(n = 100)	高危组(n = 14)	t/Z/χ²值	P值
白细胞(×10⁹ /L)	6.410±1.615	7.00(4.750, 8.000)	-0.457	0.648
中性粒细胞(×10⁹ /L)	4.155±1.398	4.941±3.075	-1.639	0.104
淋巴细胞(×10⁹ /L)	1.811±0.607	1.496±0.409	1.871	0.020
红细胞(×10¹² /L)	4.770±1.214	4.50(4.000, 5.000)	-0.852	0.394
血小板(×10⁹ /L)	223.390±50.789	215.710±58.950	0.519	0.605
总胆固醇(mmol/L)	4.130±0.895	4.290±1.267	-0.577	0.565
甘油三酯(mmol/L)	1.630±1.253	1.400(1.000, 2.000)	-0.216	0.829
低密度脂蛋白胆固醇(mmol/L)	2.460±0.731	2.570±0.852	-0.524	0.602
高密度脂蛋白胆固醇(mmol/L)	1.120±0.409	1.000(0.900, 1.100)	-0.346	0.729
空腹血糖(mmol/L)	5.970±1.766	7.210±3.401	-2.153	0.033
超敏C反应蛋白 (mg/dL)	0.530±0.429	0.200(0.100, 0.625)	-0.757	0.449
同型半胱氨酸 (μmol/L)	12.480±4.631	16.710±12.003	-2.484	0.014
尿素氮(mmol/L)	5.320±1.377	5.860±1.956	-1.293	0.199
肌酐(μmol/L)	68.410±16.261	72.790±28.110	-0.850	0.397
尿酸(μmol/L)	331.540±100.749	345.140±119.413	-0.462	0.645
CK-MB阳性(n)	0	3	15.001	0.006
造影结果(n)			7.602	0.006
阴性	37	0
阳性	63	14

CPET	风险分层		t/Z值	P值
CPET	低危组(n = 100)	高危组(n = 14)	t/Z值	P值
Loadmax (W)	99.910±31.455	102.930±24.550	-0.344	0.731
VEmax (L/min)	47.910±13.419	52.070±11.552	-1.103	0.272
AT (ml/min)	879.430±215.891	937.860±238.943	-0.936	0.351
VO₂max (ml/min)	1341.000±343.888	1339.430±259.536	0.016	0.987
HRmax (次/min)	160±8	159±8	0.890	0.375
VO₂/HR (ml/次)	10.959±2.362	11.471±2.176	-0.765	0.446
VCO₂max (ml/min)	1508.780±451.536	1532.50±371.499	-0.188	0.851
EqCO₂max	30.689±3.803	33.343±4.770	-2.368	0.020
EqCO₂-AT	31.050±4.498	32.570±4.327	-1.191	0.236
RER	1.117±0.090	1.150(1.107, 1.203)	-1.270	0.204

A Risk Prediction Model for Cardiac Rehabilitation in Patients with Stable Coronary Artery Disease

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