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Marieke S Velema, Evie J M Linssen, Ad R M M Hermus, Hans J M M Groenewoud, Gert-Jan van der Wilt, Antonius E van Herwaarden, Jacques W M Lenders, Henri J L M Timmers and Jaap Deinum

used a CT scan for this purpose. Statistical analysis In order to identify factors that could predict the presence of PA, we performed multivariable binary logistic regression analysis with a diagnosis of PA as dependent variable. All candidate

Open access

Hongyan Wang, Bin Wu, Zichuan Yao, Xianqing Zhu, Yunzhong Jiang and Song Bai

logistic regression model. If the penalization coefficient lambda (λ) is large, there is no effect on the estimated regression parameters, but as the λ gets smaller, some coefficients may be shrunk toward zero. We then selected the optimal λ in the LASSO

Open access

Silan Zheng, Meifeng Tong, Lianqin Dong, Chunmin Du, Xin Zheng, Liying Wang, Peiying Huang, Wei Liu, Mingzhu Lin and Changqin Liu

lipid profiles and HOMA-IR. Multivariate logistic regression analysis was used to calculate adjusted odds ratios (ORs) and 95% CIs of LAP, WC and BMI for HS in different models with adjustment for potential confounders. All P values are two-sided and

Open access

June Young Choi, Jin Wook Yi, Jun Hyup Lee, Ra-Yeong Song, Hyeongwon Yu, Hyungju Kwon, Young Jun Chai, Su-jin Kim and Kyu Eun Lee

univariable and multivariable logistic regression analyses to assess the relationship between VDR expression and clinicopathologic variables. Backward selection method was used in both linear and logistic regression for multiple model fitting. Kaplan

Open access

Akinori Sairaku, Yukiko Nakano, Yuko Uchimura, Takehito Tokuyama, Hiroshi Kawazoe, Yoshikazu Watanabe, Hiroya Matsumura and Yasuki Kihara

were adjusted for potential confounders by using logistic regression models. Factors with an independent association with a mean LA pressure of >18 mmHg was also determined using multiple logistic analyses. All statistical analyses were performed using

Open access

Mabel E Bohórquez, Ana P Estrada, Jacob Stultz, Ruta Sahasrabudhe, John Williamson, Paul Lott, Carlos S Duque, Jorge Donado, Gilbert Mateus, Fernando Bolaños, Alejandro Vélez, Magdalena Echeverry and Luis G Carvajal-Carmona

E (rs10787491, rs932650) and two downstream of G534E (rs10885478, rs1885434), were genotyped in five G534E heterozygous individuals for haplotype analysis. Statistical analysis All genotype frequencies and association testing using logistic

Open access

Jie Shi, Zhen Yang, Yixin Niu, Weiwei Zhang, Ning Lin, Xiaoyong Li, Hongmei Zhang, Hongxia Gu, Jie Wen, Guang Ning, Li Qin and Qing Su

: 74.5% vs 69.3% vs 59.0%, P  < 0.001). We used multivariate logistic regression models, with the lowest tertile group (T1) as a reference, to evaluate the association between thigh circumference and risk of incident hypertension. As is shown in

Open access

Karim Gariani, Pedro Marques-Vidal, Gérard Waeber, Peter Vollenweider and François R Jornayvaz

T2DM or IR was modeled using logistic regression. Results were expressed as odds ratio (OR) and (95% confidence interval) using the first quartile as reference. Two multivariable models were applied: the first one adjusted on age and gender; the

Open access

A V Dreval, I V Trigolosova, I V Misnikova, Y A Kovalyova, R S Tishenina, I A Barsukov, A V Vinogradova and B H R Wolffenbuttel

-test or Mann–Whitney U test was used. The differences were considered statistically significant at P <0.05. Logistic regression analysis using a multinomial logit model was used to identify risk factors for diabetes or ECMDs. The independent

Open access

Xiangyu Gao, Wanwan Sun, Yi Wang, Yawen Zhang, Rumei Li, Jinya Huang and Yehong Yang

, they were allowed to become categorical variables. The relationships between islet autoantibodies and clinical features were performed using Spearman correlation analysis. Furthermore, unconditional logistic regression analyses (also called binary