Risk factors for relapse and nomogram for relapse probability prediction in patients with minor ischemic stroke

Table 1 Clinical characteristics of the patients

		Derivation cohort (n = 796)			Validation cohort (n = 448)
		Favorable outcome	Unfavorable outcome	P	Favorable outcome	Unfavorable outcome	P
		n = 750	n = 46		n = 423	n = 25
Age, median (IQR)		63 (52, 71)	64.5 (59, 72)	0.26	63 (52, 70)	69 (62, 75)	0.03
Sex				0.87			0.01
	Female	217 (28.9%)	14 (30.4%)		132 (31.2%)	2 (8.0%)
	Male	533 (71.1%)	32 (69.6%)		291 (68.8%)	23 (92.0%)
Hypertension		469 (62.5%)	26 (56.5%)	0.44	261 (61.7%)	17 (68.0%)	0.67
Diabetes		229 (30.5%)	18 (39.1%)	0.25	99 (23.4%)	3 (12.0%)	0.23
FPG, median (IQR)		5.6 (5, 7.33)	5.915 (4.66, 7.22)	0.67	5.41 (4.89, 6.65)	4.85 (4.57, 5.45)	0.02
Cardiopathy		59 (7.9%)	7 (15.2%)	0.09	40 (9.5%)	7 (28.0%)	< 0.01
Smoking		188 (25.1%)	15 (32.6%)	0.29	100 (23.6%)	11 (44.0%)	0.03
UA, median (IQR)		298 (243, 359)	280 (179, 332)	0.04	306 (238, 364)	298 (179, 354)	0.61
UN, median (IQR)		5.3 (4.48, 6.54)	4.82 (3.81, 6.36)	0.11	5.5 (4.38, 6.98)	5.8 (3.81, 6.3)	0.34
Hcy, median (IQR)		13.96 (11.07, 19.03)	13.56 (10.01, 18.4)	0.33	14.04 (10.53, 17.6)	16.43 (10.01, 26.82)	0.18
CRP, median (IQR)		1.415 (0.51, 6.13)	1.325 (0.6, 3.9)	0.58	1.62 (0.56, 4.7)	1.56 (0.89, 3.57)	0.94
TC, median (IQR)		4.435 (3.84, 5.2)	4.89 (3.96, 5.36)	0.08	4.4 (3.89, 5.04)	5.02 (3.49, 5.75)	0.16
TG, median (IQR)		1.52 (1.08, 2.12)	1.72 (1.32, 2.45)	0.09	1.47 (1.06, 2.05)	1.38 (0.89, 1.86)	0.46
LDLC, median (IQR)		2.615 (2.04, 3.25)	3.15 (2.34, 3.52)	0.03	2.57 (2.14, 3.19)	3.26 (2.3, 3.71)	0.04
Stable plaques		288 (38.4%)	18 (39.1%)	1.00	147 (34.8%)	6 (24.0%)	0.39
Vulnerable plaque		400 (53.3%)	21 (45.7%)	0.36	217 (51.3%)	10 (40.0%)	0.31
Alcohol drinking		256 (34.1%)	18 (39.1%)	0.52	131 (31.0%)	11 (44.0%)	0.19
HDLC, median (IQR)		1.1 (0.94, 1.36)	1.145 (0.9, 1.28)	0.56	1.12 (0.95, 1.37)	1.14 (1.05, 1.46)	0.47
APOA, median (IQR)		1.35 (1.21, 1.55)	1.415 (1.19, 1.58)	0.56	1.35 (1.22, 1.54)	1.46 (1.19, 1.53)	0.47
APOB, median (IQR)		0.925 (0.73, 1.09)	1.1 (0.84, 1.22)	< 0.01	0.91 (0.73, 1.08)	1 (0.75, 1.16)	0.46
LP(a), median (IQR)		208.5 (112, 340)	173.5 (124, 371)	0.78	187 (106, 329)	151 (129, 371)	0.99
Cr, median (IQR)		55.65 (14.72, 72.1)	65.1 (48.6, 80)	< 0.01	55.9 (14.7, 69.8)	70.2 (48.8, 78.3)	0.01
STBL, median (IQR)		17.985 (11.7, 58)	15.11 (11.5, 19.03)	0.02	17.23 (11.7, 60.2)	14.86 (11.5, 17.3)	0.19
Ferritin, median (IQR)		220.85 (136.59, 324.3)	255.57 (218.1, 426.1)	< 0.01	207.18 (131.2, 318.78)	252.2 (191.83, 350.6)	0.09
GHb, median (IQR)		6.66 (5.82, 7.94)	7.18 (6.3, 9.09)	0.14	5.82 (4.68, 7.4)	5.91 (4.53, 6.72)	0.33
SBP, median (IQR)		142 (130, 158)	147 (139, 163)	0.08	140 (129, 155)	140 (120, 154)	0.49
DBP, median (IQR)		82 (75, 92)	84.5 (80, 90)	0.48	82 (75, 91)	89 (81, 90)	0.28

IQR: Interquartile range; FPG: Fasting plasma glucose; UA: Uric acid; UN: Urea nitrogen; Hcy: Homocysteine; CRP: C-reactive protein; TC: Total cholesterol; TG: Triglyceride; LDLC: Clow-density lipoprotein cholesterol; HDLC: High-density lipoprotein cholesterol; APOA: Apolipoprotein A; APOB: Apolipoprotein B; LP(a): Lipoproteins a; Cr: Creatinine; STBL: Serum total bilirubin; GHb: Glycosylated hemoglobin; SBP: Systolic blood pressure; DBP: Diastolic blood pressure.

Table 2 Univariate and multivariate logistic regression analyses for outcomes

	Univariate analysis			Multivariate analysis
	OR	95%CI	P	OR	95%CI	P
Age	1.027	0.994-1.060	0.109	1.014	0.987-1.043	0.315
Sex	0.853	0.364-1.998	0.714	–
Hypertension	0.633	0.311-1.290	0.208	–
Diabetes	1.550	0.668-3.597	0.308	–
FPG	0.896	0.741-1.084	0.260	–
Cardiopathy	2.087	0.803-5.422	0.131	2.021	0.816-5.003	0.128
Smoking	1.375	0.588-3.217	0.462	–
Uric acid	0.997	0.994-1.001	0.179	0.997	0.993-0.999	0.038
UN	0.877	0.715-1.076	0.207	–
Homocysteine	0.994	0.958-1.031	0.751	–
CRP	0.995	0.972-1.018	0.642	–
TC	0.997	0.968-1.027	0.833	–
TG	1.000	0.896-1.116	0.996	–
LDLC	1.037	0.878-1.225	0.665	–
Vulnerable plaque	0.620	0.244-1.576	0.315	–
Stable plaque	0.634	0.250-1.606	0.337	–
Alcohol drinking	0.983	0.443-2.181	0.967	–
HDLC	0.745	0.245-2.265	0.604	–
APOA	1.061	0.646-1.742	0.815	–
APOB	0.981	0.750-1.283	0.891	–
LP a	1.000	0.999-1.001	0.929	–
Cr	1.001	0.992-1.010	0.851	–
STBL	0.975	0.956-0.995	0.013	0.973	0.956-0.990	0.002
Ferritin	1.003	1.001-1.005	0.001	1.004	1.002-1.006	< 0.001
GHb	1.067	0.843-1.352	0.588	–
SBP	1.012	0.995-1.031	0.169	1.012	0.999-1.025	0.071
DBP	1.007	0.978-1.037	0.633	–

FPG: Fasting plasma glucose; UN: Urea nitrogen; Hcy: Homocysteine; CRP: C-reactive protein; TC: Total cholesterol; TG: Triglyceride; LDLC: Clow-density lipoprotein cholesterol; HDLC: High-density lipoprotein cholesterol; APOA: Apolipoprotein A; APOB: Apolipoprotein B; LP(a): Lipoproteins a; Cr: Creatinine; STBL: Serum total bilirubin; GHb: Glycosylated hemoglobin; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; OR: Odds ratio; CI: Confidence of interval.

Table 3 Summary of the confusion matrix for the training dataset and testing dataset

		Actual outcome		Actual outcome
		No relapse during hospitalization	Relapse during hospitalization	No relapse during hospitalization	Relapse during hospitalization
Predicted outcome	No relapse during hospitalization	750	45	423	25
	Relapse during hospitalization	0	1	0	0

The rows in the confusion matrix correspond to what the logistic algorithm predicted and the columns correspond to the known truth. There are only two categories to choose from: “No relapse during hospitalization” or “Relapse during hospitalization”. Then, the top left corner contains true negatives. The true positives are situated at the bottom right-hand corner. The confusion matrix of the model in the derivation cohort is shown in the figure, with an error rate of 0.057; the confusion matrix of the model in the validation cohort is presented in the figure with an error rate of 0.056.