Risk factors of recurrence of acute ischemic stroke and construction of a nomogram model for predicting the recurrence risk based on Lasso Regression

doi:10.12122/j.issn.1673-4254.2024.12.13

Abstract

Abstract:

Objective To investigate the risk factors of recurrence of acute ischemic stroke (AIS) within 1 year and establish a nomogram model for predicting the recurrence risk. Methods This study was conducted in two cohorts of AIS patients (≤7 days) hospitalized in Dongzhimen Hospital (modeling set) and Fangshan Hospital (validation set) from March, 2021 to March, 2022. Lasso regression analysis was used to identify the important predictive factors for AIS recurrence within 1 year, and multivariate Logistic regression analysis was performed to analyze the independent factors affecting AIS recurrence. The recurrence risk prediction nomogram model was constructed using R studio, and its discriminating power and calibration were assessed using ROC curve analysis and Hosmer-Lemeshow goodness-of-fit test. Results The modeling and validation sets contained 28 cases (15.22%) and 21 cases (15.00%) of AIS recurrence, respectively. In the modeling set, compared with the non-relapse group, the recurrence group had higher proportions of patients with age >65 years, diabetes, arrhythmia, constipation after stroke, and FBG >7.5 and significantly higher levels of NLR, UREA, Cr, HbA1c, FIB and TT (P<0.05). Multivariate Logistic regression analysis showed that an age >65 years, arrhythmia, constipation after stroke, FBG >7.5, NLR and Cr were all independent risk factors of AIS recurrence (P<0.05). Hosmer-Lemeshow goodness-of-fit test and calibration curve analysis showed that the risk prediction model had good fitting between the modeling set and the verification set. The ROC curve showed that for predicting AIS recurrence within 1 year, the AUC of the predictive model was 0.857 (95%CI: 0.782-0.932) in the modeling set and 0.679 (95%CI: 0.563-0.794) in the validation set. Conclusion The nomogram model established based on age >65 years, arrhythmia, constipation after stroke, FBG >7.5, NLR and Cr has a good predictive value for AIS recurrence within 1 year.

Key words: ischemic stroke, recurrence, influencing factors, predictive model, Lasso regression

Jiaxin JIN, Pengzhen MA, Eryu WANG, Yingzhen XIE. Risk factors of recurrence of acute ischemic stroke and construction of a nomogram model for predicting the recurrence risk based on Lasso Regression[J]. Journal of Southern Medical University, 2024, 44(12): 2375-2381.

Figures/Tables 6

References 47

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Characteristics	Recurrence group (n=28)	Non-recurrence group (n=156)	t/χ² /Z	P
Gender(n)			0.000	0.992
Male	19	106
Female	9	50
Age>65 years [n (%)]	22 (78.6%)	72 (46.2%)	9.984	0.002
Smoking [n (%)]	12 (42.9%)	78 (50.0%)	0.485	0.486
Alcohol abuse [n (%)]	7 (25.0%)	65 (41.7%)	2.769	0.096
Stroke [n (%)]	7 (25.0%)	42 (26.9%)	0.045	0.832
HBP [n (%)]	19 (67.9%)	116 (74.4%)	0.514	0.474
DM [n (%)]	20 (71.4%)	71 (45.5%)	6.378	0.012
CHD [n (%)]	14 (50.0%)	51 (32.7%)	3.113	0.078
Arrhythmia [n (%)]	10 (35.7%)	26 (16.7%)	5.473	0.019
Hyperlipemia [n (%)]	11 (39.3%)	87 (55.8%)	2.591	0.107
Hyperuricemia [n (%)]	7 (25.0%)	36 (23.1%)	0.049	0.825
Atherosclerosis [n (%)]	21 (75.0%)	134 (85.9%)	2.123	0.161
Constipation after stroke [n (%)]	15 (53.6%)	38 (24.4%)	9.825	0.002
Anxiety state [n (%)]	8 (28.6%)	22 (14.1%)	3.642	0.090
Family history of stroke [n (%)]	7 (25.0%)	41 (26.3%)	0.020	0.887
Family history of HBP [n (%)]	11 (39.3%)	44 (28.2%)	1.391	0.238
Family history of CHD [n (%)]	4 (14.3%)	19 (12.2%)	0.096	0.756
NIHSS (Mean±SD)	4.18±4.68	3.31±3.25	-0.726	0.468
CISS [n (%)]
LAA	11 (39.3%)	60 (38.5%)	2.478	0.479
CS	3 (10.7%)	7 (4.5%)
PAD	12 (42.9%)	82 (52.6%)
UE	2 (7.1%)	7 (4.5%)
WBC (×10⁹/L, Mean±SD)	8.03±3.72	7.41±2.14	-0.528	0.597
NE (×10⁹/L, Mean±SD)	5.84±3.39	5.07±1.89	-1.152	0.249
LY (×10⁹/L, Mean±SD)	1.57±0.78	1.71±0.66	-1.372	0.170
CRP (mg/L, Mean±SD)	8.66±24.46	2.02±4.59	-0.596	0.551
NLR (Mean±SD)	4.51±3.58	3.39±1.93	-2.104	0.035
PNR (Mean±SD)	43.36±16.23	50.62±21.05	-1.534	0.125
SII (Mean±SD)	1094.18±1207.77	778.59±508.24	-1.303	0.193
TyG (Mean±SD)	1.77±0.77	1.61±0.73	-1.403	0.161
FBG>7.5 (mmol/L)	16 (57.1%)	39 (25%)	11.704	<0.001
UREA (mmol/L, Mean±SD)	6.20±1.97	5.19±1.62	-2.848	0.044
Cr (μmol/L, Mean±SD)	78.50±23.32	67.50±15.50	-2.198	0.028
ALP (U/L, Mean±SD)	85.90±24.46	78.93±21.82	-1.486	0.137
TC (mmol/L, Mean±SD)	4.39±1.25	4.49±1.04	-0.450	0.653
TG (mmol/L, Mean±SD)	1.52±0.69	1.80±1.10	-0.698	0.485
HDL-C (mmol/L, Mean±SD)	1.05±0.21	1.07±0.26	-0.245	0.807
LDL-C (mmol/L, Mean±SD)	2.69±0.94	2.73±0.78	-0.219	0.827
Hcy (μmol/L, Mean±SD)	15.18±7.20	17.91±14.06	-0.511	0.610
HbA1c (%, Mean±SD)	7.35±1.61	6.70±1.38	-2.090	0.037
APTT (S, Mean±SD)	30.45±2.20	30.02±4.59	-1.725	0.085
FIB (g/L, Mean±SD)	3.40±0.64	3.47±4.40	-2.048	0.041
TT (S, Mean±SD)	15.24±1.26	15.23±6.38	-2.265	0.023
D-D (μg/L, Mean±SD)	206.64±226.89	166.19±278.68	-1.883	0.060

Characteristics	Recurrence group (n=28)	Non-recurrence group (n=156)	t/χ² /Z	P
Gender(n)			0.000	0.992
Male	19	106
Female	9	50
Age>65 years [n (%)]	22 (78.6%)	72 (46.2%)	9.984	0.002
Smoking [n (%)]	12 (42.9%)	78 (50.0%)	0.485	0.486
Alcohol abuse [n (%)]	7 (25.0%)	65 (41.7%)	2.769	0.096
Stroke [n (%)]	7 (25.0%)	42 (26.9%)	0.045	0.832
HBP [n (%)]	19 (67.9%)	116 (74.4%)	0.514	0.474
DM [n (%)]	20 (71.4%)	71 (45.5%)	6.378	0.012
CHD [n (%)]	14 (50.0%)	51 (32.7%)	3.113	0.078
Arrhythmia [n (%)]	10 (35.7%)	26 (16.7%)	5.473	0.019
Hyperlipemia [n (%)]	11 (39.3%)	87 (55.8%)	2.591	0.107
Hyperuricemia [n (%)]	7 (25.0%)	36 (23.1%)	0.049	0.825
Atherosclerosis [n (%)]	21 (75.0%)	134 (85.9%)	2.123	0.161
Constipation after stroke [n (%)]	15 (53.6%)	38 (24.4%)	9.825	0.002
Anxiety state [n (%)]	8 (28.6%)	22 (14.1%)	3.642	0.090
Family history of stroke [n (%)]	7 (25.0%)	41 (26.3%)	0.020	0.887
Family history of HBP [n (%)]	11 (39.3%)	44 (28.2%)	1.391	0.238
Family history of CHD [n (%)]	4 (14.3%)	19 (12.2%)	0.096	0.756
NIHSS (Mean±SD)	4.18±4.68	3.31±3.25	-0.726	0.468
CISS [n (%)]
LAA	11 (39.3%)	60 (38.5%)	2.478	0.479
CS	3 (10.7%)	7 (4.5%)
PAD	12 (42.9%)	82 (52.6%)
UE	2 (7.1%)	7 (4.5%)
WBC (×10⁹/L, Mean±SD)	8.03±3.72	7.41±2.14	-0.528	0.597
NE (×10⁹/L, Mean±SD)	5.84±3.39	5.07±1.89	-1.152	0.249
LY (×10⁹/L, Mean±SD)	1.57±0.78	1.71±0.66	-1.372	0.170
CRP (mg/L, Mean±SD)	8.66±24.46	2.02±4.59	-0.596	0.551
NLR (Mean±SD)	4.51±3.58	3.39±1.93	-2.104	0.035
PNR (Mean±SD)	43.36±16.23	50.62±21.05	-1.534	0.125
SII (Mean±SD)	1094.18±1207.77	778.59±508.24	-1.303	0.193
TyG (Mean±SD)	1.77±0.77	1.61±0.73	-1.403	0.161
FBG>7.5 (mmol/L)	16 (57.1%)	39 (25%)	11.704	<0.001
UREA (mmol/L, Mean±SD)	6.20±1.97	5.19±1.62	-2.848	0.044
Cr (μmol/L, Mean±SD)	78.50±23.32	67.50±15.50	-2.198	0.028
ALP (U/L, Mean±SD)	85.90±24.46	78.93±21.82	-1.486	0.137
TC (mmol/L, Mean±SD)	4.39±1.25	4.49±1.04	-0.450	0.653
TG (mmol/L, Mean±SD)	1.52±0.69	1.80±1.10	-0.698	0.485
HDL-C (mmol/L, Mean±SD)	1.05±0.21	1.07±0.26	-0.245	0.807
LDL-C (mmol/L, Mean±SD)	2.69±0.94	2.73±0.78	-0.219	0.827
Hcy (μmol/L, Mean±SD)	15.18±7.20	17.91±14.06	-0.511	0.610
HbA1c (%, Mean±SD)	7.35±1.61	6.70±1.38	-2.090	0.037
APTT (S, Mean±SD)	30.45±2.20	30.02±4.59	-1.725	0.085
FIB (g/L, Mean±SD)	3.40±0.64	3.47±4.40	-2.048	0.041
TT (S, Mean±SD)	15.24±1.26	15.23±6.38	-2.265	0.023
D-D (μg/L, Mean±SD)	206.64±226.89	166.19±278.68	-1.883	0.060

Variate	β	SE	Wald χ²	OR (95% CI)	P
Age>65 years	1.374	0.571	5.790	3.951 (1.290-12.098)	0.016
Arrhythmia	1.208	0.568	4.526	3.348 (1.100-10.194)	0.033
Constipation after stroke	1.325	0.504	6.913	3.762 (1.401-10.101)	0.009
NLR	0.219	0.088	6.186	1.244 (1.047-1.479)	0.013
FBG>7.5	1.851	0.533	12.069	1.035 (1.008-1.063)	<0.001
Cr	0.034	0.014	6.374	6.366 (2.241-18.088)	0.012

Variate	β	SE	Wald χ²	OR (95% CI)	P
Age>65 years	1.374	0.571	5.790	3.951 (1.290-12.098)	0.016
Arrhythmia	1.208	0.568	4.526	3.348 (1.100-10.194)	0.033
Constipation after stroke	1.325	0.504	6.913	3.762 (1.401-10.101)	0.009
NLR	0.219	0.088	6.186	1.244 (1.047-1.479)	0.013
FBG>7.5	1.851	0.533	12.069	1.035 (1.008-1.063)	<0.001
Cr	0.034	0.014	6.374	6.366 (2.241-18.088)	0.012

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[11]	SU Xiaofeng, HAN Jiming, GAO Yinghui, FAN Li, HE Zijun, ZHAO Zhe, LIN Junlin, GUO Jingjing, CHEN Kaibing, GAOYan, LIU lin. A long-term ischemic stroke risk score model in patients aged 60 years and older with obstructive sleep apnea: a multicenter prospective cohort study [J]. Journal of Southern Medical University, 2022, 42(3): 338-346.
[12]	LIU Jin, YANG Yanling, YAN Ke, ZHU Cairong, JIANG Min. Development and validation of nomograms for predicting stroke recurrence after first-episode ischemic stroke [J]. Journal of Southern Medical University, 2022, 42(1): 130-136.
[13]	ZHANG Haijie, YIN Fu, CHEN Menglin, QI Anqi, YANG Liyang, CUI Weiwei, YANG Shanshan, WEN Ge. Predicting postoperative recurrence of stage I-III renal clear cell carcinoma based on preoperative CT radiomics feature nomogram [J]. Journal of Southern Medical University, 2021, 41(9): 1358-1365.
[14]	LIN Yidie, ZHANG Baiyang, HU Meijing, XU Minghan, QIN Chengjie, ZHU Cairong. Causal relationship between physical exercise and risk of ischemic stroke recurrence based on the potential outcome theory [J]. Journal of Southern Medical University, 2021, 41(8): 1191-1197.
[15]	. Relapse of ankylosing spondylitis and its predictors after withdrawal of tumor necrosis factor-α inhibitors: a 52-week follow-up study [J]. Journal of Southern Medical University, 2021, 41(5): 633-639.