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. 2022 Oct 14;12:173. doi: 10.1186/s13578-022-00863-x

Table 2.

Independent metabolic signature selection using LASSO

Terms Coefficient (β) HR Frequency
LASSO based signature selection for death
 Dulcitol 0.22 1.25 200
 4-Acetamidobutyric acid 0.29 1.34 200
 N6-succinyl adenosine 0.05 1.05 195
 l-Cystine 0.08 1.08 191
 β-Pseudouridine 0.05 1.05 173
 2-(Dimethylamino) guanosine 0.02 1.02 137
 Kynurenine 0.04 1.04 43
 3,3ʹ,5-Triiodo-l-thyronine − 0.12 0.89 43
 d-Sorbitol 0.04 1.04 21
 DL-P-hydroxyphenyllactic acid 0.02 1.03 21
Phenyllactate (PLA) 0.01 1.01 11
 Cyclic AMP 0.02 1.02 5
 S-(5-Adenosy)-l-homocysteine 0.02 1.02 2
LASSO based signature selection for MACE
 4-Acetamidobutyric acid 0.06 1.06 200
 l-Cystine 0.06 1.06 200
 l-Tryptophan − 0.24 0.79 200
 Dulcitol 0.10 1.10 200
 5-Methyluridine 0.28 1.33 200
 Kynurenine 0.22 1.25 200
 Phenyllactate (PLA) 0.10 1.11 200
 LysoPC 20:2 − 0.51 0.60 200
 d-Sorbitol 0.02 1.02 199
 LysoPC 20:1 − 0.04 0.96 193
 N6-succinyl adenosine − 0.01 0.99 2

The regression coefficients were calculated by averaging the coefficients obtained from tenfold cross-validation lasso Cox regression with 200 repeats, adjusted for 17 main clinical confounders. The confounders included age, sex, AST, eGFR, DM, HyperT, CHOL, HDLC, PPI, ACEI, BB, CCB, current smoking, family history of CVD, SYNTAX, SBP, and GLUC. The variables that appear zero times were removed and the variables left were further selected to develop a predictive model, abbreviations are as in Table 1