Application of principal component analysis and logistic regression model in lupus nephritis patients with clinical hypothyroidism

Huang, Ting; Li, Jiarong; Zhang, Weiru

doi:10.1186/s12874-020-00989-x

Table 2 Component loadings

From: Application of principal component analysis and logistic regression model in lupus nephritis patients with clinical hypothyroidism

	PC₁	PC₂	PC₃	PC₄	PC₅	PC₆	PC₇	PC₈	PC₉
WBC	.020	−.023	.469	.094	−.006	.035	−.021	−.041	.084
HB	−.067	.206	.080	.018	−.024	−.097	.070	.179	.118
PLT	−.002	.105	.004	−.009	.129	−.237	−.075	.261	.054
N	.032	−.041	.471	.064	.009	.023	.007	−.109	.052
L	−.092	−.053	−.009	.017	−.017	.121	−.058	.405	.042
TP	.063	.366	−.022	.067	−.028	.128	−.017	−.008	−.015
ALB	.064	.405	−.058	−.077	−.122	.013	.007	−.048	.001
GLB	.031	.143	.026	.182	.083	.182	−.033	.037	−.023
Scr	.347	.092	−.029	−.108	.019	.039	−.009	−.079	−.137
BUN	.299	.055	.052	−.142	.033	.021	−.011	−.074	.069
UA	.311	.068	.084	.028	.028	.071	.027	.004	−.002
TG	.203	.060	.006	.138	−.109	−.015	.080	.068	−.005
TC	.159	.097	−.114	−.076	−.054	−.012	.030	.442	−.152
HDL	−.021	−.023	.057	−.315	.084	.178	.042	.185	−.152
LDL	.080	.135	.021	.000	−.140	−.273	.354	−.167	.245
HDLTC	−.147	−.021	.102	−.234	−.009	.225	.014	−.103	−.045
ESR	−.028	−.047	−.010	.128	.339	−.115	−.063	.119	−.036
CRP	.051	−.035	.056	−.104	.442	−.114	.114	−.242	−.157
C3	.060	.257	−.029	−.107	.063	−.141	−.008	.040	−.174
C4	−.035	−.021	−.011	.108	.060	−.429	−.027	−.118	.017
IgG	.057	.107	.012	.104	−.014	.289	−.052	−.010	−.019
IgA	−.021	−.099	−.013	−.186	.461	.020	.008	.025	.151
IgM	−.109	−.099	.130	.459	−.100	.080	.031	−.025	−.195
Anti-dsDNA antibodies	−.023	−.056	−.081	−.121	.138	.016	−.090	.163	.289
Anti-Sm antibodies	.035	.004	−.010	−.059	.004	.028	.488	−.039	−.078
Anti-SSA antibodies	.016	−.010	.001	−.060	−.018	.038	−.006	.088	.147
Anti-SSB antibodies	−.010	.013	−.037	−.018	−.051	−.053	.061	−.062	−.057
Anti-U1RNP antibodies	−.023	−.037	.000	−.021	.057	−.008	.444	−.027	−.045
Anti-RNP antibodies	−.020	.003	.093	−.057	−.035	−.036	.000	−.051	.579

Loading pattern of the thirty clinical values on the nine main principal components. The loadings of the variables most relevant for the component interpretation are bolded

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