scholarly journals Association of cystatin C levels with metabolic syndrome incidence: a nested case-control study with propensity score matching

2021 ◽  
Vol 49 (1) ◽  
pp. 030006052098631
Author(s):  
Tengfei Yang ◽  
Dongmei Pei
Keyword(s):  
Metabolic Syndrome ◽  
Propensity Score ◽  
Physical Examination ◽  
Propensity Score Matching ◽  
Case Control Study ◽  
Case Control ◽  
Chinese Adults ◽  
Biochemical Profiles ◽  
Nested Case Control ◽  
Control Study

Objective Metabolic syndrome (MetS) involves multiple metabolic disorders and seriously affects human health. Identification of key biological factors associated with MetS incidence is therefore important. We explored the association between MetS and the biochemical profiles of Chinese adults in Shenyang City in a nested case-control study. Methods We included adult participants who underwent physical examination at our hospital for 2 consecutive years. Participants’ biochemical profiles and other MetS components were tested and monitored continuously. Propensity score matching was used to adjust confounding factors between participants with and without MetS. We analyzed the association between incidence of MetS and the biochemical profiles of participants. Results Of 5702 participants who underwent physical examination between 1 January 2017 and 1 December 2018, 538 had confirmed newly developed MetS. After successfully matching 436 pairs of participants, mean cystatin C (Cys-C) level was significantly higher in the MetS group than in the non-MetS group. Logistic regression analysis indicated that age (years) and γ-glutamate transpeptidase, creatinine, uric acid, and Cys-C levels were significantly associated with MetS incidence; among these, the odds ratio of Cys-C was highest (3.03; 95% confidence interval, 1.02–9.00). Conclusions Cys-C levels were significantly associated with the incidence of MetS among Chinese adults.

scholarly journals A novel association of CCDC80 with gestational diabetes mellitus in pregnant women: a propensity score analysis from a case-control study

2019 ◽  
Author(s):  
Lei Liu ◽  
Jiajin Hu ◽  
Ningning Wang ◽  
Yang Liu ◽  
Xiaotong Wei ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Propensity Score ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Pregnant Women ◽  
Propensity Score Matching ◽  
Case Control Study ◽  
Case Control ◽  
Regression Analyses ◽  
Control Study

Abstract Background: Gestational diabetes mellitus (GDM) is a growing global epidemic. Our study aims to confirm the association between circulatory coiled-coil domain-containing 80 (CCDC80) in pregnant women with GDM, to investigate the discriminatory power of CCDC80 on GDM, and to explore the relationships between this molecular level and clinical cardiometabolic parameters. Methods: A 1:2 matched case-control study with 61 GDM patients and 122 controls was conducted using a propensity score matching protocol. All participants were screened from a multicenter prospective pre-birth cohort: Born in Shenyang Cohort Study (BISCS). During 24 and 28 weeks of gestation, follow-up individuals underwent an oral glucose tolerance test (OGTT) and blood sampling for cardiometabolic characterization. Results: Following propensity score matching adjustment for clinical variables, including maternal age, gestational age, body mass index, SBP and DBP, plasma CCDC80 levels were significantly decreased in patients with GDM when compared with controls (0.25±0.10 vs. 0.31±0.12 ng/ml, P =0.003). Conditional multi-logistic regression analyses after adjustments for potential confounding factors revealed that CCDC80 was a strong and independent protective factor for GDM (ORs <1). In addition, the results of the ROC analysis indicated the CCDC80 exhibited the capability to identify pregnant women with GDM (AUC=0.633). Finally, multivariate regression analyses showed that CCDC80 levels were positively associated with AST, monoamine oxidase, complement C1q, LDL-C, apolipoprotein A1and B, and negatively associated with blood glucose levels at 1 h post- OGTT. Conclusions: Biomarker CCDC80 could be of great value for the development of prediction, diagnosis and therapeutic strategies against GDM in pregnant women.

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